Tech workers are largely insulated from the impact of AI, but the technology is beginning to automate an array of tasks.

That's according to new research from Hays, shows that pay for technology workers in the UK remains competitive, in particular for contractors and specialists working in security, the cloud and DevOps.

The research comes as tech giants continue to rack up serious layoffs, raising questions about whether those cuts are down to wider economic issues, disruption from AI, or the use of AI as a smokescreen to hide unnecessary cutbacks.

Hays' research found that UK technical roles are showing only moderate exposure to AI impact.

The study scored AI impact on different roles by considering the level of disruption, ranging from tasks largely unaffected by AI, to AI influencing some tasks but not fundamentally changing work, to skills enhanced – or replaced – by the technology.

Measuring the impact of AI on jobs

Most technical roles in the UK ranged around the 50 point mark out of 100, which equates to moderate exposure, with some tasks automated and upskilling necessary in some cases. A score in the 40-point range refers to minor AI influence, with a few tasks shifting but core work staying largely the same.

Cloud engineers scored just 45/100, software engineers and software developers were each rated 56/100, while test analysts had a significantly higher AI impact rating, at 66/100.

"The findings of our report clearly show that AI isn’t replacing human talent but amplifying it," said David Curtis, STEM Senior Managing Director, Hays UK&I. "

As automation accelerates routine tasks, the roles that thrive are those grounded in judgement, coordination, and strategic oversight."

Project managers and change managers both posted one of the lowest AI impact scores in the UK at 22/100, highlighting the importance of soft skills and people skills. That said, the lowest score was network engineers, at just 2/100 – showing humans are still vital for physical infrastructure.

"For professionals, this creates significant opportunities to build future‑ready careers by developing adaptable, strategic and tech‑augmented skill sets," Curtis said.

"For organizations, the findings underline the growing importance of continuous development and flexible workforce strategies."

Tech salaries in the UK

When it comes to pay, Hays said the UK isn't the top paying market, but "remains competitively positioned", with the UK ranking in the top half for salaries across most job categories for permanent employees.

The highest average salaries in the UK were Solutions Architect (£84,249), Security Engineer (£75,702), and DevOps Engineer (£67,532).

Just two roles languished in the bottom half for UK salaries: RPA engineer, which was ranked 18th out of 34 countries, and Project Managers, ranked 18th.

The contractor market was similar, ranking in the top half of day rates for most roles.

Java developers and cloud engineers were the most competitive in the UK, ranking 3rd and 5th globally, with average day rates of £695 and £684 respectively.

That said, the top highest paying countries for permanent tech employees were the US, Switzerland, Denmark, the UAE, and Saudi Arabia. For contractors, the highest-paying markets are Switzerland, Denmark, Australia, Germany, and Japan.

Hays noted that wages in the UK reflected market dynamics rather than any impact from AI, with pay influenced by budget structures and skill supply versus demand.

"To remain competitive, the UK must continue to position itself as an attractive destination for the world’s best tech talent," Curtis said.

"That means ensuring wages and benefits remain attractive, but also creating an environment where innovation, skills development and career progression can accelerate. In a global market defined by rapid technological change, competitiveness is measured not only by pay, but by how effectively a country supports and invests in its people.”

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Sana from Workday provides four key functions within the Workday platform: ‘find’, ‘act’, ‘build’, and ‘automate’ – but the company says human workers are still a core part of the process.

‘Find’ lets workers answer organizational-specific questions drawn from their Workday data, such as vacation policy or queries about ongoing customer campaigns, while ‘act’ leans more heavily on Sana’s AI agent functionality to update documents and populate fields on an employee’s behalf.

For example, a user could ask for Sana from Workday to update a client’s contract value, which it could then do in the relevant system without the employee needing to leave the chat window.

‘Build’ and ‘automate’ are more akin to vibe coding, in that they allow users to create dashboards and summaries from Workday data, or to construct multi-step workflows for agents. Examples include creating an agent that automatically reviews one’s email inbox for receipts and combines them into a report for manual review.

Workday also announced the Sana Self-Service Agent, which automates HR and finance tasks such as filing expenses, verifying pay cheques, or changing worker schedules based on live data.

Sana Enterprise lets businesses connect this conversational AI experience to their third-party enterprise apps. At launch, this includes connectors for Atlassian Confluence, Box, Gmail, Google Drive, Jira, Microsoft Outlook Email, Notion, Salesforce, ServiceNow, SharePoint, Slack, and Zoom.

“AI only works in the enterprise when it’s connected to trusted, deterministic systems, and that hybrid architecture is exactly what Workday is building,” said Aneel Bhusri, co-founder, CEO and chair at Workday.

“Sana is what brings it all together. It’s not just a new Workday experience – it’s a powerful way for people to search, reason, and orchestrate work across the enterprise.”

In response to an ITPro question on whether AI hallucinations are still a concern, Gerrit Kazmaier, president, Product and Technology at Workday, said that hallucinations are “a feature, not a bug” in consumer-facing LLMs but they’re something to entirely avoid in enterprise AI.

“Our value add, the value add of Workday, what we are engineering here at Workday, is actually building AI systems that put nondeterministic AI on enterprise rails,” he said.

“So running them repeatedly, safely, securely governed, and basically engineering the hallucinations away through clean data and through safeguarding.”

How Sana from Workdays automates core tasks

Workday acquired Sana Labs in November 2025 for approximately $1.1 billion (£830 million). At the time, the company highlighted how Sana’s enterprise knowledge would help to build a horizontal layer across enterprises that connects data and workflows.

Joel Hellermark, SVP and GM of AI at Workday and founder and CEO at Sana, showed in a demo how Sana from Workday and Sana Enterprise can combine to improve enterprise productivity.

Hellermark showed how he could ask the Sana Notetaker agent to update a customer’s Salesforce entry based on a call he had with them the previous day.

The agent then draws on the transcript from the call, captured by the Sana Notetaker agent, and uses the relevant information to update the Salesforce entry in a single click by the user.

In another example, Hellermark asked Sana to create an expense report based on his inbox, with the agent then able to pull details such as his flight tickets, hotel stay, and team dinner and create a single ‘submit report’ button to send the document into Workday.

On top of the pre-built agents within Sana from Workday, businesses can create their own. Hellermark showed how managers can create custom workflows for an agent to follow each time a new employee is onboarded, for example.

He demonstrated how he could give a new colleague access to a tool simply by asking the agent to do so. In the same vein, he could ask Sana to draft an email to the new employee inquiring about her laptop preferences.

“The big difference between Sana’s connectors and some of these historical connectors that were more enterprise search-like, is that we built them for agents first,” explained Hellermark.

“So this means that we can do write actions and not just read actions into all of these enterprise applications.”

Hellermark added that with Workday’s decades of experience building out strict application permissions and security, paired with Sana’s architecture, agents can accurately capture the correct governance controls to handle enterprise data and only perform authorized actions.

AI replacing human work

Responding to a press question on the organizational value of AI, especially when it comes to HR automation, Bhusri stated that it’s one that “keeps me awake at night”.

“I do think a lot of low level HR work is going to get replaced by agents – there's no way around it,” he said.

‘What the industry needs to own, including Workday and you'll see more from us on this topic, [is] we have to figure out a way to to take care of the employees that are dislocated for no better word on because of AI, we have to come up with a plan for them.”

Bhusri added that Sana is automating manual work, letting businesses do what previously took weeks in minutes, and that while this has obvious value for businesses it will have to be paired with focused support for human roles.

“A big part of what Sana and Workday does with learning is retraining, and we've got to double down on the retraining side,” he added.

“I mean, I hope there's a world where AI is complementary to humans. We have to find a path to that.”

However, Bhusri called out recent claims that AI could replace SaaS applications as “misinformation”.

“There's this idea that AI is going to replace a lot of these applications with things like vibe coding, which I'm a technologist and I've been in this space for a long time, I just don't see that happening.”

Workday’s applications, which cover HR, finance, and payroll, are deterministic – they have a clear start and end point.

“You think about a payroll process: you launch the payroll process, you end the payroll process,” said Bhusri.

“You can't get it mostly right, you have to get it right every time. AI, for all of its power, is really a probabilistic and reasoning engine, and it will help to come up with solutions and answers on what step to take next.”

Bhusri explained that Workday sees AI as an additive technology to these deterministic business processes, rather than something that can or should replace them entirely.

“So the power is really bringing the deterministic enterprise applications like Workday, and our competitors, SAP, Oracle, are in a similar place, with probabilistic reasoning.”

Hellermark noted that although 100% of Sana’s software engineers now use Claude Code, with 80-90% of its code being AI-assisted, the firm is hiring as many software engineers as it can right now.

This “paradox”, he said, feeds into his hope that AI could drive workers to quickly reskill.

“So my hope is that this era will result in the return of the polymath, that will see a renaissance of sorts where people can very quickly upskill into new domains and will remove some of the sort of specialist needs, and people will increasingly become generalists.”

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Autonomous systems in businesses are no longer experimental. Robots now work alongside humans in warehouses, retail stores, and hospitals, frequently deployed and supported by channel partners who never expected to become advisors on fleet operations and security inside customer networks.

This evolution is creating both opportunity and exposure. Robotics-as-a-Service and robotic deployments are becoming part of the managed service stack, yet few frameworks exist to guide customers on how they should be secured, audited, or governed. This raises new questions in the adoption process: “Should I trust it?”, “Who has access to the data?”, and “What happens when something goes wrong?”

When scale expands the attack surface

Automation within customer environments blurs the line between IT and OT (operational technology) responsibilities. Treating them as a shared domain is key to preventing blind spots.

Deploying a robot at one site is manageable for IT and OT groups to handle. Managing hundreds of thousands of robots across multiple retail or logistics locations -- that’s the challenge that customers are facing today. Each new machine deployed adds potential risk to a customer's infrastructure: misconfigured WiFi, outdated firmware, and insecure update channels all present meaningful vulnerabilities.

This is where Robotics-as-a-Service offerings can cover this gap and minimize risk. The robotic provider’s fleet management services should provide each channel partner and customer with:

• Visibility: A complete inventory of devices, software versions, and configurations.
• Integrity: The Robotics-as-a-Service offering should perform updates and end-to-end monitoring for any unauthorized access.
• Agility: Ability to monitor performance and make remote edits for operating within dynamic environments.

Each robot should be designed to operate fully autonomously without requiring broad or sensitive access to customer networks, and should maintain strict security boundaries. This ensures the robot does not introduce new risks for IT and OT teams.

Data governance in motion

Robots challenge traditional data governance programs because of the sheer diversity of information they collect while operating in public and dynamic spaces. A single robot may generate events, points of interest, telemetry, imagery, and mapping data — each with different formats, storage needs, retention profiles, and compliance considerations. Data is often distributed across multiple locations, aggregated at different layers, and subject to handling rules that depend on the specific sensor or subsystem producing it.

For channel partners and customers, the ability to understand these data types, sources, locations, and flows — and ensure they align with relevant frameworks — is foundational to creating trust at scale. Documenting the full data flow is the first step in governing any autonomous system. If you can draw the flow, you can govern and secure it effectively.

From there, security-by-design and least-privilege architecture form the backbone of good governance. These practices ensure that data access is intentional, restricted, and auditable, supporting data quality, transparency, and accountability across the fleet. In robotics, a few principles consistently reinforce trust:

• Purpose limitation: Sensors capture only what is required for navigation, safety, task validation, or product improvement.
• Image anonymization: Any incidental human imagery is blurred before presentation or review.
• Encryption and access control: All data is encrypted in transit and at rest, with access tightly governed by role-based permissions.
• Retention discipline: Data is kept only as long as it provides operational or product value, then securely deleted.

When providers explain these safeguards in plain language, governance becomes an enabler rather than a constraint — and trust becomes a differentiator rather than a hurdle.

Governance as a service differentiator

As deployments grow, governance becomes a competitive edge. Customers no longer just want performance metrics; they want assurance that their automation ecosystem behaves predictably and securely.

Robotics providers should demonstrate that assurance by:

• Providing access to a centralized data governance, privacy, and compliance repository for documentation, such as a Trust Center, that includes diagrams, security controls, and other architectural insights.
• Sharing third-party attestations or certifications, such as UL safety certification for key components and SOC 2 for cloud-based robotic services.
• Offering whitepapers or other published documents that clarify the robotic data flow, including how and where data is processed, transmitted, stored, and for how long.

When you can show exactly how data moves and who can access it, trust stops being an abstract goal and becomes part of your value proposition.

Preparing for a new regulatory landscape

The regulatory landscape for AI and robotics is maturing quickly. In the EU, new risk-based frameworks are formalizing documentation, transparency, and post-deployment monitoring. In the US, state-level obligations for companies using AI and autonomous systems continue to expand, with similar patterns emerging globally.

The best way to stay ahead is to engineer for principles, not headlines. Autonomous systems that already minimize, anonymize, encrypt, and evidence their decisions will adapt naturally as new laws arrive. Document how the system makes decisions—even reactive ones like obstacle avoidance—and make audits part of routine operations rather than exceptional events.

For the channel, readiness isn’t about predicting every regulation. It’s about building around stable, durable principles: minimization, encryption, explainability, and documented accountability. Autonomous systems grounded in these fundamentals can shift with whatever policy comes next.

Trust as operational ROI

Every managed service provider (MSP) knows the cost of an outage or breach. The same applies to autonomous systems. The more predictable and transparent your deployments are, the faster customers will adopt and renew.

Trust reduces friction across every stage of a partnership: procurement, onboarding, compliance, and support. In practice, that makes trust a measurable form of ROI.

The future of robotics in the channel won’t be defined by who moves fastest, but by who moves most responsibly.

Humanoid robots and people will be able to work truly side-by-side this year, according to the CEO of one leading robotics company.

In a discussion at Mobile World Congress (MWC), Peggy Johnson — who stepped in as CEO of Agility Robotics last year — shared what the company's Digit robot was capable of doing now, and what was expected to be achieved in the near future.

Johnson painted a picture of humans and machines working alongside each other without the need to segregate the machines for safety reasons.

The 1.7m-tall, 85kg-heavy Digit robots can currently lift 16kg in weight, with hopes that will increase to 25kg soon, she said. At the moment, that allows them to take on simple tasks in warehousing and logistics, such as collecting an object and moving it into a tray for another robot to take away.

The advent of generative AI allowed companies like Agility to take robotics that previously required heavy programming to be controlled via simple voice commands.

"We're able to overlay AI onto our traditionally controlled robot, and really supercharge its power," she said.

Human in the loop

But, humanoid robots remain limited. Johnson noted that demos of robots doing backflips or making coffee may catch attention, but that requires intense programming.

With automation alone, the reality of what's possible is much more basic — but still useful. She remarked that warehouses can be heavily automated, but still require a human to pick up parts or products and move them to where they're needed.

"We focused on what is actually possible today, and that is simple tasks, [such as] moving materials," she said, adding: "It's able to do work that's repetitive, can be somewhat dull, tasks that generally people don't like — and in fact there's about a million jobs in this space that are open in the US alone, they can't find people to fill these jobs."

Digit is already used in a warehouse facility in Atlanta, Johnson noted. However, she said that robotics can't take on all aspects of a human worker's role.

"It doesn't complain, doesn't fight with its coworkers," she laughed. "It just does the job.”

"It's augmenting somebody, who that was part of their job — for a few hours a day, they've got to move this product, and then they're over here doing something else," she said. Adding it "augments the human in the loop."

Imperfect AI

Notably, Johnson admitted that limitations in AI mean robots still need human colleagues to keep them on track. Johnson demonstrated a Digit robot on stage, telling it verbally via an iPad to pick up an item — a yellow sponge — and place it into a bin.

Slowly, the robot considered the command, before meticulously moving the item.

Even such a simple display could go wrong, she admitted: "It's why you don't want AI to completely control a robot right now."

However, such tasks were previously onerous to achieve, as they required detailed programming — and it's easier to just pick up the sponge yourself at that point. AI controls help avoid that burden, though building a workflow still takes time.

"You can give a command to a machine and it can act upon it," she said. "That's going to change everything."

The demonstration was powered by Google's Gemini 2 model, though Johnson said Agility supported the use of all AI models in its robotics.

"All the models operate slightly differently, and they're all right now building their robotics foundation models, which is why we became agnostic," she explained.

"We just wanted to swap in whichever one is working best for whatever use case."

Safety first

That said, there's much work that needs to be done, Johnson said, before these robots are capable of everything Agility's customers would like them to do.

Indeed, she said customers have said they'd like to be able to send a Digit down to the loading dock to pick up a box and bring it back to a workstation.

Beyond technology challenges, that would mean Digit has to move alongside humans. Right now, robotics must stay inside what's known as a "work cell", a defined space that humans don't enter for their own safety.

"Right now there are no humanoid robots who are certified to operate outside of a protected area," Johnson said, pinning the blame on the technology itself as well as regulators. "The big unlock [of potential for humanoid robots] is coming out of the work cell and being what's called 'cooperatively safe' around humans."

That would mean a Digit would be able to safely walk down to the loading bay, staying a safe distance from humans even if they did something unexpected.

Johnson said Agility would demonstrate robots operating outside of a work cell later this year. She said: "Agility has solved for that. It's a very challenging product problem."

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• What do security pros want from generative AI?

The prospect of mass job cuts linked with artificial intelligence (AI) has been a looming specter in the wake of the recent generative AI boom. 

Concerning Goldman Sachs research published in March warned that up to 300 million jobs could be lost due to the rise of generative AI platforms in the years to come. The study predicted roughly 18% of work could become computerized and that workers in ‘advanced economies’ would bear the brunt of AI-linked job losses. 

Society has long feared AI will pose a threat to jobs and livelihoods; it’s a fear that goes back several decades. But the prophecies never came to pass, and the reality of AI – at least over the last ten years – has been relatively dull.

The recent wave of job losses, however, shows this simply isn’t any longer the case. The threat we’ve shrugged off for being too abstract is finally here, with organizations capitalizing on the power of generative AI tools to deliver cost-savings and “streamline operations”.

Death by a thousand cuts

BT showcased this latter goal – which roughly translates to “why hire human workers when we can automate tasks” – perfectly when it announced plans to lay off tens of thousands of workers and automate a myriad of roles. 

These brutal workforce cuts will see the telecoms giant lay off up to 40% of its workforce by the end of the decade to become a “leaner business”, and focus heavily on integrating AI within key organizational processes. 

Anywhere up to 10,000 of these positions set for the chopping block could be replaced by AI, the Telegraph reported. That’s a serious chunk of the workforce automation will render obsolete. 

BT framed this shift as a direct response to sluggish growth; it recorded a 1% year-on-year decline in revenue while profits dipped 12%. But it’s naive to take this rationale at face value. 

In reality, the penny has dropped for businesses. Operating amid a period of tightening purse strings and a possible recession, AI offers a get-out-of-jail-free card for businesses already salivating at the prospect of cutting staff costs – only this time they can limit the operational pressure these cuts might create. 

BT isn’t alone here. IBM, last month, revealed it would pause hiring for non-customer-facing roles and eventually replace these with AI, according to CEO Arvind Krishna. He told Bloomberg the hiring freeze includes for back-office departments like HR, with the tech giant expecting thousands of jobs to be automated in the years to come. 

Around 7,800 non-customer-facing roles could be replaced due to AI, Krishna noted, which equates to around 30% of staff currently occupying these roles. Kudos to IBM: at least they’re being upfront in warning staff they’ll eventually be consigned to the scrap heap – but this will come as little consolation. 

We’ve been blind to the AI warning signs

Sam Altman, CEO at OpenAI, the organization behind ChatGPT, has made no secret of the potential risk to human workers, especially in recent months. Altman told ABC News in March he was a “little bit scared” of the detrimental impact of generative AI on the global labor market. 

He said “it’s going to eliminate a lot of current jobs”, but then added “we can make much better ones”. With Altman concerned, yet still pouring money into the field, it’s safe to say workers should be anxious, and angry, about the future. Industry leaders have also failed to clarify exactly how businesses plan to make “better” jobs following AI-induced workforce cuts. 

The expectation that an individual who, for example, has worked in HR for decades will suddenly be presented with a raft of new, exciting opportunities after losing their job is ridiculous, and ignores reality. Re-skilling is hard enough as it is, and changing careers is a luxury few can afford. 

AI was once feared as a tool that would eventually replace human jobs. But these fears gave way to optimism that it could instead augment roles. What we refer to as AI – largely machine learning – has developed into tools that can relieve the burden of repetitive tasks in favor of more fulfilling ones. 

Businesses, however, will embrace mass automation in the calculated manner we’ve come to expect over the years. Many workers will rightfully peer over their shoulder and wonder what cost saving plans the c-suite is plotting. With HR, customer-facing roles, and even jobs in software development potentially at risk due to generative AI, there will be no reprieve for roles in the crosshairs. This trend has been a trickle for months, but it’ll inevitably become a torrent that sweeps up thousands, if not millions, more roles across the labor market.  

As the sun sets on Appian’s annual conference, it’s clear artificial intelligence (AI) now plays a larger role for the company than ever before.

Whether it’s the integration of natural language prompts and digitization of documents in Appian 22.3, or new documentation capabilities for the platform’s own language SAIL, attendees have been treated to a buffet of AI options. Indeed, there’s a real sense that Appian is angling to make itself the go-to platform for AI usage among firms that aren’t yet sure if AI is for them, or otherwise consider it too risky in its current form.

Speaking with customers and officials alike, there’s a sense that Appian’s tender approach to integrating large language models (LLMs) within its platform is going down well. Depending on who you talk to, one gets the sense this is seen as either a necessary precursor to a larger expansion into generative AI tools, or a natural extension of Appian's existing suite of AI and automation offerings.

Adam Glaser, SVP of engineering at Appian rebuffs my suggestion the firm has done a remarkable about-turn to point itself so fully towards AI adoption in the six months since Appian Europe. He also denies the newfound support for developers creating their own AI models is a response to the market.

"We've had AI in the product in various forms of fashions, for quite some time," he states, pointing to Appian's machine learning-based smart recommendations and its intelligent document processing. "That's just a progression of us looking at AI, not even anticipating the hype and interesting things you can do with that GPT-style AI. It's 'what's practical? What's actually really useful?'"

Appian’s cautious optimism

Only time will tell whether this risk-averse strategy is likely to work, and whether Appian picks up pace to roll out generative AI solutions. There are, though, several indicators of an enthusiasm to see more of the technology at an executive level. 

Every image used in the first day’s keynote presentation was generated using the generative AI image model Midjourney, as ITPro was cheerfully informed by both Karina Buschsieweke and Malcolm Ross, director and SVP of product strategy, respectively. 

In addition, the script for the keynote's introductory video was generated in ChatGPT, as personally overseen by Ross. “We did edit it a little,” he admits. “It was a collaboration between AI and humans.”

Beyond the clear AI enthusiasm, these decisions also act as a suitable microcosm for Appian’s entire approach going forward. Buschsieweke and Ross, for instance, both note the output seen by conference attendees was the result of an iterative process involving precise natural language prompts.

Whether the end result was images of Toyota factories or leafcutter ants (both carried metaphorical weight in the proper context) none of the final images were without fault on the first Midjourney pass.

It’s this precise experience that Appian claims that it aims to eliminate with its low-code approach to LLM training and input. 

Despite all it’s shown off in the conference, from natural language input with its Data Fabric to advances in process mining, this balance of fine controls without too much need for experience could be a hard needle to thread.

It's promising, however, that Appian is approaching it as a low-code, user experience problem first and foremost rather than trying to iron out hallucinations or other foundational issues within the LLMs themselves.

"Our focus on generative AI in our product is really around having it embed inside the design time experience," Ross tells ITPro. "Because what you get back from it needs to be immediately refined, you'll find that it's not written quite right or interpreted [your prompt] wrong. So it's a very good complement to low-code design, where you get the initial result and you drag, move it around and tweak it to the final design."

More AI is waiting in the wings

There’s also a sense much is left unrealised in Appian’s current approach. Caution makes sense here, but it appears to have come at the expense of even more powerful functionality for systems such as process mining.

Buschsieweke says worries over generative AI hallucinations have dashed initial interest in integrating LLMs within the core solution.

“We had these discussions already… I wanted a chat for process mining, even before ChatGPT was released, a conversational interface with the user” she asserts. “But it was exactly these concerns: ‘how can we make sure that the insights are actually reliable?’ My perspective was that maybe we should just get started for now to see how it can work.”

The second keynote, headed up by Appian co-founder and chief marketing officer Michael Beckley, comprised in-depth look at current and future AI features. As is standard for promises made in keynotes, the audience was shown a disclaimer 

“This is what I believe today,” Beckley announced to the audience. “This is what we believe today, and with a rapidly-changing field like AI, the product roadmap is subject to rapid change.”

Appian has positioned itself remarkably well, in light of the AI competition. In staying relatively still while the AI market has rushed to innovate, it has counterintuitively come out on top in terms of its public image. It’s an approach that lives or dies with how its customers take it. But the Appian platform is well-placed to deliver on its promises for enterprise AI.

Appian has announced plans to increase natural language input across the platform, as well as new features for the automatic digitization of contracts.

With the implementation of pre-trained large language models (LLM) into its Appian Platform, the firm showed off new automated analytics solutions that will soon become available to customers.

Based on simple user inputs, and leveraging its integration with Appian’s Data Fabric, the system is capable of auto-generating prompts for data retrieval and generating complex data visualizations from plain-English sentences.

Michael Beckley, co-founder at Appian, demonstrated some of the new AI capabilities during a keynote at this week’s Appian World conference.

In one example, Beckley was able to produce a visual ESG breakdown with the phrase ‘show me the average waste emissions by utility bill’.

Appian also announced its new Contract Writing solution which is aimed at assisting public sector agencies by automation the process of drafting contracts.

Through a pre-recorded video, Beckley also demonstrated a warranty claim form being digitized using a few natural language prompts. 

Appian’s AI was capable of creating a digital copy with both optional and required fields, drop-down boxes and date-pickers, as well as company branding as described in the original prompt (in this case, green title text).

The time from upload to having a digitized contract was around 30 seconds in this example.

“Compared to the many hours this would probably take you, generally speaking, we think it’s a pretty great productivity booster,” said Beckley.

“These large language models provide a base level of natural language understanding, which is great,” Malcolm Ross, SVP of product strategy at Appian, told ITPro.

“But the value for us is to pair that with the context of the Appian software, and to have that natural language understanding translate into building an application or building something inside a product.”

A key example of this was shown in Appian Knowledge Base chatbot, which can return internal knowledge based on natural language inputs.

The prompt ‘What are employers subject to when fail to pay’, for example, returned the relevant legal information based on the territory of the company and cited the specific document from which it pulled the information.

In the near future, customers will also be able to generate requests for information (RFIs) - the documentation needed to obtain information from suppliers on goods and services - with natural language prompts.

A live demonstration showed a user asking for an RFI with a specific response time, and the categories respondents should fill in.

Using the Appian knowledge base, the system can produce accurate and company-specific RFIs based on previous documents.

Having made Appian Contract Writing with federal agencies in mind, the firm stressed that Appian Cloud is compliant with Department of Defense (DoD) impact levels IL4 and IL5.

These pertain to information on critical infrastructure, highly confidential financial information, and unclassified but sensitive military data.

The firm is also aiming for greater integration of generative AI throughout its SAIL code environment. 

SAIL is the declarative expression language beneath the hood of Appian’s visual low-code design UX, and Beckley quoted a reddit thread in which developers bemoaned the inadequacy of ChatGPT for working in the language.

With Appian’s new announcements, developers can quickly build workflows using AI and seamlessly open these in the Appian process modeler and edit them in SAIL or using low-code elements.

Developers seeking to use SAIL primarily can also use the inbuilt LLM functions to directly generate SAIL code, or translate SAIL code into plaintext explanations.

Enterprise cloud application firm Workday is being sued over alleged racial and other biases in its AI applicant screening tool.

The class action complaint alleges that the tool contains algorithmic discrimination against applicants who are African American, over the age of 40, and those with disabilities.

It also includes suggestions that Workday's AI is developed by humans who often have built-in biases of their own, conscious or unconscious, and is therefore likely to be discriminatory as a result.

Plaintiff Derek Mobley, an African American male over the age of 40, who also suffers from depression and anxiety, filed the document in a California district court.

He stated that since 2018, he has been rejected in 80-100 job applications to companies that he believes utilise Workday’s screening tool for hiring purposes.

“Workday, Inc. unlawfully offers an algorithm-based applicant screening system that determines whether an employer should accept or reject an application for employment based on the individual’s race, age, and or disability,” the complaint [PDF] read.

The complaint made no distinction between the use of Workday’s systems by individual firms as the systems in question are used by a range of companies. The complaint centres around the allegation that HR teams have used Workday’s systems to pre-select applicants in discriminatory ways and that, as a result, the plaintiff opposes the usage of the software and not the intricacies of its implementation at respective companies.

“We believe this lawsuit is without merit,” a Workday spokesperson told IT Pro.

"At Workday, we are committed to trustworthy AI and act responsibly and transparently in the design and delivery of our AI solutions to support equitable recommendations.

"We engage in a risk-based review process throughout our product lifecycle to help mitigate any unintended consequences, as well as extensive legal reviews to help ensure compliance with regulations.”

Mobley contends that Workday has violated laws including the Title VII of the Civil Rights Act of 1964, the Civil Rights Act of 1866, the Age Discrimination in Employment Act of 1967, and the ADA Amendments Act of 2008.

Without careful consideration and oversight of training, machine learning models and AI can contain algorithmic bias.

Another example of this being discovered in hiring is Amazon’s failed attempt to automate its recruitment process, which resulted in a system that discriminated against female applicants.

The model had been trained on a decade of Amazon hiring data, which revealed a tendency to hire men over women.

As a result, the model favoured male applicants and used evidence that applicants were women within their CVs such as references to all-women colleges as points to discount them from being hired. Amazon retired the system without ever having put it into use outside of simulated tests.

Nokia and Kyndryl have announced a three-year extension to their global edge partnership, focusing on industry 4.0 the development of LTE and 5G private wireless networks.

Since the companies joined forces, they have established more than 100 'engagements' with companies around the world. The nature of these engagements has ranged from the initial advisory and testing stages to the full implementation of solutions.

Around 90% of these have been with companies in the industrial manufacturing sector, including energy, mining, and petrochemical firms.

Kyndryl and Nokia aim to expand the adoption of leading-edge technologies in this sector and others, with Nokia Digital Automation Cloud (DAC) platform enabling quick and widespread adoption of wireless assets.

The companies have also committed to the launch of a lab in Raleigh, North Carolina alongside cyber security firm Palo Alto Networks. This will seek to develop auditable wireless networks with the advanced security capabilities necessary for critical industrial networks.

Kyndryl and Nokia cited their implementation of a private wireless network with edge computing at Dow Chemical’s petrochemical processing plant in Freeport, Texas.

Dow Chemical, one of the world’s largest chemical producers, worked with Kyndryl and Nokia to improve safety and efficiency across the site.

In 12 months, the companies have established a private LTE network that covers the entire complex, with a zero trust and containerised solution for the management of security profiles.

Site operators and engineers can now communicate in real time and make use of vehicle telematics, video and audio feeds, and tracking for increased safety.

The two companies first announced their edge computing partnership in February 2022, with an aim to digitalise enterprises and tap into the $510 billion (£417.9 billion) industry 4.0 market.

“Kyndryl and Nokia have a shared vision for digital transformation, and as leaders in our respective industries we are driven to grow this market together,” said Chris Johnson, head of Nokia's global enterprise business.

"We are excited to build upon our existing success and strengthen our alliance targeting more enterprise customers across multiple industries.

“The two companies are currently exploring and developing new, integrated solutions and services for edge, cloud, IP networking, optics, fixed access, 4G, and 5G core and network operations software technologies, which can address the growing demand for mission-critical, industrial-grade wireless networking.”

A study by Grand View Research projected that the private 5G network market will grow to $41 billion (£33.6 billion) by 2030, driven in part by massive investments made by the industrial manufacturing sector.

The benefits that private 5G networks can bring to the transportation and logistics industry are also expected to accelerate adoption of the technology.

5G private networks and edge networks have a clear role to play in advancing the ‘smart ports’. Already, sites such as the Felixstowe Port in Suffolk have adopted 5G networks to more efficiently process data, and enable the widespread use of internet of things (IoT) devices.

Oracle NetSuite has announced a range of updates to its tools designed to consolidate costs as customers battle recessionary cuts and sector-wide talent shortages.

Addressing delegates at its SuiteConnect conference in London on Tuesday, the company also affirmed its commitment to strengthening its localisation efforts for customers.

This includes adapting models for regional tax and regulatory requirements, as well as offering NetSuite's UI in 27 languages for a better user experience.

EMEA customers have specifically pointed to the complexity of VAT and customs compliance rules as piling on costs, particularly for organisations driven by product shipping or data transfer.

NetSuite has highlighted specific tools as antidotes for some of these regional issues. For example, the ERP giant has aimed to make supply chain management easier than ever through the use of products such as Oracle NetSuite Analytics Warehouse, the firm’s is a pre-built data warehouse based in the cloud.

In the new version of Analytics Warehouse, NetSuite has promised pre-built visualisations for industries such as manufacturing, software, and services.

This will include charts and graphs for greater insights, as well as key performance indicators (KPIs) that can be applied to a range of metrics such as project hours and case numbers.

Although US customers can also make use of these capabilities, the firm has drawn specific attention to them with regards to the needs of EMEA customers.

Complex VAT, customs, and data compliance rules have been registered as concerns across this region, and Russia’s invasion of Ukraine and subsequent fuel crisis have highlighted the need for flexible supplier prices.

62% of NetSuite customers identified rising costs as their primary concern in a recent survey, with energy prices a point of specific worry.

Although Analytics Warehouse has been available in the UK since September 2022, Evan Goldberg, founder and EVP at Oracle NetSuite, said that a number of improvements have been made to the tool based on customer feedback.

These include a range of new transaction types that the tool can draw on including data sets in sales, inventory, financials and support management. Data sets such as the new Cross Charge Journal, which allows financial teams to track charges across subsidiaries.

IT Pro was given the example of a company using this to seamlessly track invoices for a product shipped to an England-based customer from an Ireland-based supplier.

In the keynote speech, a representative from NetSuite customer Charlotte Tilbury praised the firm’s widening focus on prebuilt models. These can be applied to help businesses automate functions in a range of different tax and legislative environments.

“I’ve never come across another ERP which allows us to set up a subsidiary as quickly as NetSuite,” said Aman Deep, business systems director at Charlotte Tilbury.

“And not just setting up subsidiaries. We have had to change the organisational structure and hierarchies, there was much more to it.”

A global, local approach

NetSuite’s ‘Full Suite Ahead’ mantra buoyed it through its SuiteWorld conference in September, and stressed the importance of adopting an all-or-nothing approach in order to get the most value out of its tools.

At the time, Goldberg had stated that he was “not worried” about competitors located in regions into which NetSuite expands, as its unique full-suite approach is its selling point rather than any one service. The company has previously stated it aims to provide the world’s ‘most localised ERP system’.

“We have this tagline we use which is ‘act global, be local’,” James Chisham, VP product management at Oracle NetSuite, told IT Pro.

“So it's that notion of global capabilities on a kind of worldwide scale, but built for users in a specific market.”

NetSuite’s focus on prebuilt models for a number of different regions, which can react to changes in tax and regulatory requirements are part of this. But it is also reflected in the growing degree to which tools in NetSuite’s range integrate with third-party applications, even those of competitors.

Analytics Warehouse now comes with more than 40 third-party data sources including Google Analytics, Salesforce, and Shopify. NetSuite states that this simplifies the blends of data that an organisation may be handling, and strengthens the quality of analytics.

It’s a prime example of NetSuite’s current strategy, in which holistic customer experience appears to be prized over individual product returns.

“We’ve been really amazed by the takeup of NetSuite Analytics Warehouse, because NetSuite has built-in analytics”, Goldberg told IT Pro.

“First of all, we’re finding that our customers, not just in the software industry but in many industries, have a tonne of data in other systems. I just talked to someone here at the conference about how they’re excited to use it for legacy data from their previous NetSuite system, so we’re finding all kinds of use cases for that.”

Goldberg also stressed that EMEA leads the US in some NetSuite developments.

“There are definitely areas where we are EMEA-first, certainly on some of the automation of transactions. Europe and the UK are ahead of the US there.”

NetSuite has placed an increasing focus on automation in recent years. Core to its idea of centralising applications and data across businesses, it has emphasised its ‘full suite’ as uniquely capable of hosting the kinds of end-to-end automation that businesses can use to reduce strain on teams.

Asked about automation being used to tackle skill shortages, Chisham was quick to admit that individual needs still need to be addressed, and that automation is not a silver bullet for lack of talent.

“We want to use automation where it makes sense. Where we feel some of the skills shortage hits is availability of skill. You know what's happened over the last few years, it's well documented, tech companies have been hiring aggressively, you know?”

“So there's been a real difficulty in finding the right types of people. I think that that's the same for our customers as well, it's getting the right people in the right positions. And you know, automation in and of itself is not going to solve all of those challenges.”

A future led by automation

Going forward the firm will be investing more heavily in artificial intelligence (AI) and machine learning (ML), which it already uses for products such as NetSuite Supply Chain Control Tower and its Intelligent Recommendations feature.

Cormac Watters, EVP of EMEA applications at Oracle, told IT Pro that rollout of AI would be greatly backed up by existing Oracle cloud infrastructure.

“NetSuite and indeed Fusion both run on our OCI platform. This means we as Oracle, when we deploy new machine learning or AI algorithms, techniques, data assessments, can make it available to all of the products and their portfolio.”

“I think the world has moved, and that AI and machine learning are now no longer considered gimmicky. I think it's real and it's there to be used. So there's actually an expectation from customers, ‘what's the latest piece of machine learning you can give me?’”

Further detail on these developments is expected at its next SuiteWorld conference in October 2023.

IT departments, which have long faced difficulties trying to recruit skilled talent, are now facing an additional challenge as many businesses put a freeze on hiring in the face of economic instability and look to use existing resources as efficiently as possible. With this goal in mind, it’s important to enable employees to be productive, while not leaving them overworked.

Improperly organised work stacks, insufficient collaboration and a failure to adapt to changing work environments are all factors that can negatively impact productivity, and must be tackled from the planning stage to allow workplaces to thrive.

In this episode, Jane and Rory speak to Christian Lund, co-founder at productivity tech firm Templafy, to unpack concerns around productivity in the current landscape and how automation and AI can help to solve these problems.

Highlights

“I think where AI comes in extremely handy … are these more complex areas where you really need to think, and compile, and put together a lot of different information incredibly fast.”

“Let's make sure that people do their real jobs. And hopefully, they will do those jobs a lot better, and have all the support from AI and other stuff to get them to get them to where they need to be.”

“You could use [automation] for saving costs, or you can use it for growing your business. And right now, I think businesses are really looking to invest in this because it is something that helps them save cost.”

Read the full transcript here.

Footnotes

• 95% of organisations involved in the UK’s four-day working week trial say productivity has maintained or improved
• What is Robotic Process Automation?
• Nine best productivity apps to optimise your workflow
• AI is now powerful enough to automate the back office
• What are the pros and cons of AI?
• What is generative artificial intelligence (AI)?
• What is ChatGPT and what does it mean for businesses?
• Email is killing productivity, new research finds
• The best Microsoft Office alternatives: Free, paid, and online mobile office suites

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This automatically-generated transcript is taken from the IT Pro Podcast episode ‘Boosting productivity in the IT department'. We apologise for any errors.

Rory Bathgate

Hi, I'm Rory Bathgate.

Jane McCallion

And I'm Jane McCallion.

Rory

And you're listening to the IT Pro Podcast, where today we're talking about productivity. As the skill shortage continues to bite into IT departments, every business looks to use its resources as efficiently as possible and empower employees to be as productive as possible while not leaving them overworked.

Jane

Improperly organised work stacks, insufficient collaboration and a failure to adapt to changing work environments are all factors that can impact productivity. Today we’re speaking with Christian Lund, co-founder at productivity tech firm Templafy, to discuss the main concerns around productivity in the current landscape and the role that automation and AI can play in alleviating some of these problems. Christian, thanks for being on the show.

Christian Lund

Thanks a lot for having me.

Rory

So just to start with a broad question, how can we measure productivity?

Christian

Well, you can measure productivity, especially in time. How much time is being spent, how much time goes into productivity? And also, there is also a relativity to it to some extent, because it also measures against “how else could you be using that time that you're spending on doing a particular part of work”. So I would say those are probably the two, the two main ones. It then translates into a lot of other things like revenue, for example, which is maybe the most important for many businesses.

Rory

I think when a lot of businesses are looking at quantifying productivity, there's quite a few threads that can be pulled in those areas. Right now we're looking at a skill shortage and workers are perhaps having to ramp up their productivity to make up for absences in a company. With that in mind, how can an IT decision maker look to assess productivity in their team to maybe alleviate those concerns down the line?

Christian

Well I think the first thing that people do in businesses in general, and certainly in IT as well, is to look at the actual tasks that requires to be done inside of a business, and then try to figure out from that perspective the types of resources that is required to go into that. I think that's probably a starting point. And to your point, right now what we're seeing a lot is that you're really trying to see how much, how well you can spend your use your resources, also both from a people perspective, and also from a technology perspective, and really find the right balance between the two. Because oftentimes, what technology does is that it supports the productivity that, you know, it adds to the productivity, that the productivity, it adds to the productivity capabilities of people.

Jane

So I guess, do productivity and efficiency sort of go hand in hand if we're talking about use of time, I guess, as well as outcomes?

Christian

I think you're pointing to the right area there. Because productivity, as I said before, is very much oftentimes put directly in connection with time. It's a place where you can save time, or as efficiency oftentimes takes it a little bit further. What you do with that time, then translates into something else, for example, revenue. So it's more outcome focused. And I think that's really the difference. One of the differences between the two, that the efficiency piece really have a big look at not only how fast it was to do it, but also how well it works once you've done it. And what technology can do as well, again, is to oftentimes combine those two things really well.

Jane

So the IT industry and IT departments have, as Rory mentioned, faced all kinds of skill shortages recently. Can using technology, can increase in productivity, patch those holes or is it an 'as well as' rather than an 'instead of' filling those roles,

Christian

You know, to add to the productivity in essence, what it does when you add productivity, more productivity to your work, is that it allows you to essentially spend your brain better. So if you're a knowledge worker, for example, all the stuff that you have to go through that takes time, that you can then do more with higher productivity, actually adds efficiency to that pool. So in that sense, I think definitely yes. Because you allow you really allow to allocate the resources in a better place. And with knowledge workers especially, instead of having them to do you having them do tedious jobs or things that can be automated, or that way you can add productivity to it with technology, you can allow them to focus on on more relevant things that are actually focused more on efficiency. So I think the answer is yes.

Rory

So looking at productivity, breaking it down into as you've been saying, individual areas that can be done better, you're talking about breaking it up into drain on, drain on finances but also drain on time. Is productivity as much of a workspace problem as it is a worker problem?

Christian

Well, I think it can be, as well with a workspace, I think it comes on the other hand in, you know, in two forms, because you could argue that depending on on your workspace, and my understanding of that is where you actually work, where you physically go to work, how that how that influences you? Well, on one hand, that can be like very positive for productivity, I think, because it oftentimes come comes with a lot of energy and there is extra things you can get from that, that kind of actually ends up with you being more productive. There's also faster ways to get to information because you have your people right there, and things like that. So there's that side to it. But there's obviously also the other side to it, that having to go to work, you also get into chatty situations with people, you end up sometimes spending a little bit of time that you shouldn't have, of course you need to do the commute to even get there, and so on. So it kind of comes, it kind of goes both ways. But either way, I would say if that is done well or not, technology can still play a pretty big role in terms of supporting you in the way that you that you work and collaborate with your co workers also inside of a workspace.

Jane

Can we expand on that a little bit more in terms of, we've sort of danced around a little bit, what sort of technologies are we talking about when it comes to increasing productivity?

Christian

Well, I guess that again depends very much on the type of work that you do. But I can tell you sort of the example from the world that I come from, and which is very much focused on knowledge workers. So one particular thing that people if your knowledge workers do, if your knowledge worker do a lot, is to document your work through documents. That's kind of what they're for. So the way that knowledge workers can do that is really only that, because they don't have buildings to show, or furniture to show. They need to document their work through documents. And that is perhaps one of those areas that, you know, time is just being spent so much like in pretty much all knowledge worker areas that is producing documents is one of those areas where companies are really looking to add productivity to their work. So they don't have to spend so much time on undoing that piece, and they can do more of their real job, which is typically not actually doing documents. It's kind of a prerequisite to to document what they do.

Jane

And when you speak about knowledge workers, does this include the IT department?

Christian

Yeah, it does include the IT department as well. But actually the IT department, oftentimes in knowledge worker industries, is also serving as a good decision maker for providing the right tools and technologies, obviously, for the people that they co-work with. So they're kind of doubled, because they also of course need to do this type of work. But they also need to consider how they can support and help the organisations with the best possible technology for them to be more productive and ultimately also efficient. So it kind of plays both ways, in that piece, too. But some of those good technologies that are out there for productivity and efficiency, for certain also has a lot of productivity pieces built into them that helps the administration, that helps IT for deployment and updating, and things like that there are done well.

Rory

So when we're talking about these specific technologies that are used to increase productivity, are we primarily talking about automating workflows, are we talking about consolidating stacks into a maybe a more of a collaborative space? What specific changes are we talking about in regards to increasing productivity?

Christian

Yes, I think you're hitting on some of those, the two ones that are that are really important, because one are the ones that actually do and go in and actually support you with being more productive. Like, for example, tools that will automate the way that you build up business documents, or you build out quotes or you have other types of processes that you need to go through where automation plays a big role and really helps the end user focus on other things than going through those tedious tasks, and focus on on what they're actually hired for. And then at the same time, there's the consolidation piece where in order for that to work, oftentimes, many technologies need to work together. Because going through processes where you, for example, piece together a business document, you would oftentimes need to combine different types of data from different sources to piece that together on that canvas that ultimately is the output that you're looking to do. And in order to do that, of course, as an IT person you would need to make the right decisions in terms of combining those technologies in the best way to make sure that the end result is as productive and efficient as possible for the business.

Jane

And you know, Rory mentioned automation there. Is there a role to play for AI within this? I know it's everybody's favourite buzzword.

Christian

There is, obviously there is a very strong role for AI to play around these, you know, around productivity in general because it's what it does. I mean, automation, if you look back sort of in history, the first piece of automation were kind of people not having to use their hands so much, because these machines could take over and automate a lot of that work. And that is really what is travelling into the brains now where, with AI obviously, where the automation that frees up brainpower to do other stuff, as I've said a couple of times now. So there's a lot of opportunity for that to happen. And we see obviously now with OpenAI, ChatGPT and other services coming out. That is, it's moving super fast forward. And I think the new discussion then is, what can it be used for and where are the limitations that you really need to consider in terms of how to apply this best, not the least in in a business or an enterprise context where there are other things to consider as well. And on that note, it's oftentimes a combination. Because using the example as I've used a couple of times now, with the business document, what that ultimately is is a combination between different stakeholders that you need to serve for. There is the security part that needs to make sure that it follows the, you know, regulations and compliance standards of the company, there is a brand new piece that you take into account. And there is then all the rest that actually builds the business document. And the rest is then oftentimes a combination between very structured data that you have inside of your CRM system like Salesforce or similar, and then all the information that lives on the intranet, which is where really ChatGPT comes in. And ultimately, it's a combination of all those things to make it work. So AI alone, at least as it is today, will not take you all the way at least in a business context. It helps you with all the information that is available out there, unless you have like a very specifically trained model that only focuses on a certain area. But ChatGPT for example, unbelievable capacity in terms of supporting people with all the extra things in the, I would say the 'bespoke stuff' that goes into, for example, a business document can be super helpful. But all the very structured part, it can't really touch because it sits behind very strong walls inside of the business. So it's really about finding that right balance between exactly how can we apply this in the best possible way to support people being more productive all the way through. But the potential, obviously enormous.

Jane

I've got to say that if I put myself in the shoes of a technologist, while AI is quite exciting and it does definitely have a place it's already running in some places quite, quite helpfully and usefully, it seems quite expensive. So are AI systems, I guess when you think about a return on investment type idea, is it actually something at this point that is mature enough and good value for money enough that it's actually worth IT decision makers thinking about spending their budget on?

Christian

Well, it's difficult to be black and white on that in my opinion, because for some areas yes, it is very strong. And it's also not necessarily super expensive. It depends on how much you can leverage what exists already, like we've seen more recently with some of those technologies coming out that are more open source. But if it's worthwhile or not, or if it pays well, on the return on investment calculation, it really needs to go into the specifics on what you need to use it for. And I think one thing that oftentimes happens, I've seen many times in my career, is that you need to consider, you need to figure out what you're trying to achieve first, and then figure out if AI is the right thing for you to do it. Because there's also a tendency for that to become like a thing on its own. And it's not really necessarily super relevant, there might be other ways where you can automate a lot of things in maybe more structured ways that does not require AI, but will still take you to the end goal a lot faster and a lot, lot cheaper. So it's really about figuring out how to how to apply those things. I think where AI comes in extremely handy and will in the future, are these more complex areas where you really need to think, and compile, and put together a lot of different information incredibly fast and pieced together, and something that makes reason like we've seen with ChatGPT being a very good example of being unbelievably capable of. That is where I think it's really strong, but many of, I would say the more normal automation tasks that companies are looking at, there are many other ways than just AI to support those and to get to the same types of efficiency and productivity gains.

Rory

Something that strikes me when we're talking about large language models such as, I mean you've named ChatGPT as one example is that we're discussing them in the context of productivity, rather than say, end-to-end automation or worker replacement. So on this point of identifying the specific areas where maybe AI would be required versus where it wouldn't be required, are you envisioning more of a collaborative approach in the future where specific AI tools are used alongside human workers, rather than replacing them entirely? More of a productivity boost, rather than just a pure output boost?

Christian

Yes, I think definitely that it will be collaborative. And there are certainly, you know, certain industries or types of roles that are more exposed to these types of things than others, obviously. But in general I think that's the case, yes, that it requires still a very strong involvement of people from any of those things. And again, if you look at one role as an example could be like a seller, that goes out and sells a product. That person would, of course, still be incredibly important in the interaction with that person on the other side it is, that's kind of how those things work. But all the stuff that goes into enabling that person to be where that person needs to be, and how this person can improve and understand better which areas to improve in and so on, there are many ways that can support that person in getting better and ultimately allowing that person to do more of what that person is supposed to be doing, which is selling and not, for example, doing quotes and proposals and other stuff that kind of falls into into becoming like a successful successful salesperson, as well. So I think that the combination is really strong, but there are certainly areas where industries, we need to consider what to do also, with the people capacity that they will have in the future, the brain capacity that they would need to think about how to use in a better way.

Jane

Yeah, I guess it kind of strikes me when we talk about technologies like this, that computers didn't put typists out of work, they put typewriters out of work, and cars put horses out of work. The people tend to stick around at least for a while, while things change. Is that how it's likely to be with AI do you think?

Christian

Yes, it is. But it's also slightly different, because there is another type of... it is called artificial intelligence for a reason. So it kind of it adds an extra layer to that. On the other hand, we know as well that, at least for now, we're kind of always a little bit ahead. So it looks back on the language models, for example, that were mentioned earlier earlier here in this show that the they are looking at things that were available to a certain point in time. And it's combining that with good information that kind of gets you to here, but there is still kind of, you know, it's it's hard to get into the forward thinking kind of thing. And being ahead of the game, that's kind of the the advantage of the human right now. But let's see how that how that changes over time. It is going to be interesting to follow, but for now I think what it does really is that it opens up unbelievable opportunity for headspace, to use headspace better, because it frees up that. It takes away all the stuff that you wouldn't really be having to think about or do that others can do, so you can think about the stuff that it can't think about, and start doing more of that. And that's back to the point of let's make sure that people do their real jobs. And hopefully, they will do those jobs a lot better, and have all the support from AI and other stuff to get them to get them to where they need to be.

Rory

There's a report that was recently released, that was looking at concerns of IT decision makers, of CIOs, CTOs. And in that it was noted that a major effect on productivity is just being had by the fact that currently people are having to do the jobs of two people in their role. They're having to out up fires where normally they would be working effectively. So we can, you know, we can talk around some of the tech aspects, but also to go back to what we were saying in the introduction about the skill shortage it's clear that the skill shortages is having a profound effect on productivity. Do you think that some of the technology that we've talked about has the potential to help maybe less skilled workers become more productive, and help fill these roles as well as help people in existing roles become more productive.

Christian

Well maybe. I think what's more interesting is the other way around, that more skilled people can grasp over more areas, to put it in that way. So the skills shortage coming in as like, "I need to fill out two people's jobs". But, you know, the the other way to look at that is that where automation and technology can play in is to make those jobs easier to do in terms of the cumbersomeness that goes into it, and make it more like at least for some areas, like thinking jobs. Which means that you can widen out the bandwidth, essentially, of the most skilled people you have. So I think it kind of goes, you know, plays both ways. But being also a business person, I think it's it's attractive that you can use the skills of your best people more, make sure that they spread across bigger areas, because they typically have the best understanding as well of what you're trying to do. So it also goes in that direction, but for sure everybody will be will be lifted with better technology. Yes.

Jane

I suppose one of the ways I think that I've heard it described before is that technology or any kind of automation takes over the dangerous and dirty jobs, but also the kind of tedious bits of kind of manually filling out an Excel spreadsheet - other spreadsheet platforms are available - or, you know, that kind of thing that is time consuming, but doesn't really do very much and also makes you bored.

Christian

Yes exactly, I think that is where that is one of the biggest areas where you would see AI and automation excel. And we're seeing that already, right now with those exact things. Because it's information workers, typically highly paid information workers that are put into positions where they need to do tedious jobs, like the ones you just said. Filling out Excel spreadsheets, or building out business documents, piecing together things that require their time, but it's not really what adds value to what they're trying to do. So that's why there's so much focus on really, how can we eliminate the work that goes into that piece of creating documents? Again, documents are not going away you still need to document the work that has been done. But it's just that you don't have to do it, and I think that movement is really going on right now, on getting rid of all the stuff that automation could do for you so you can do your real job.

Rory

On the point of making specific processes more efficient, specific processes more productive in the hands of individuals. Where's the line drawn between a process that you can look at and say, "okay, this requires a more efficient individual input" - whether that's by automation, or you're giving an individual templates that they can they can work with - And those that require more of a centralised approach. So those that you need to step back and say, "okay, the problem here is the workflow", or "the problem here is the stack that this is situated in". Is there a specific line you can draw between those two? Or does that really vary depending on the company?

Christian

Well, I think there is, and it's kind of... if it's when you, before we spoke about what's the difference between productivity and efficiency. And the other side to this that might come in here is also risk. And once you kind of add a risk layer to it, that's where it becomes very, something that you typically look at from a centralised perspective, its governance and risks. Yes, we want people to be productive, but we cannot do it at the cost of risk. So we cannot put more risk upon ourselves by doing these things. And that is where it oftentimes goes into this centralised, very governing perspective of doing that. Whereas the more you go into the productivity and efficiency area, it tends to get closer and closer to the almost the end user, that needs to do do more with what they have today. So we definitely see that distinction. And for example, I mentioned before how if you have like 80 million documents produced every year in a company, one thing is that part of those documents need to serve for proposals and ended up being like deals with signatures on. A lot of them do a lot of other stuff, but all of them need to follow certain standards. You know, you cannot have things that were from an information security perspective, that does not like live up to the standards of your company, and you lose information into the wrong hands and things like that. You need to have that governance layer while you think about productivity at the same time. So this is the example of just the document piece, but I think that goes in a more generic layer as well. The ability to combine those things and the need and request from the business to be more productive, to be more efficient, and to balance that out with also making sure that you have control. And you avoid risk and do that in the same time. That is, those are typically very interesting discussions. And I think the best technologies out there, you know, cover exactly that. That goes both ways, do not leave anyone outside, but make sure that yes we can provide productivity efficiency, but we do it while you also have the opportunity to govern what you need to do well,

Jane

It looks like we are going into a recession and whatever is happening, whether it's that or through inflation, or a bit of both IT departments are having their budget squeezed. Can automation perhaps help IT departments, companies as a whole, use their resources and money more effectively even if it means an initial outlay?

Christian

Short answer is yes, I think the change that is happening with this, and again, we've been touching upon efficiency, productivity against each other, I think efficiency has been really strong. With the whole uptake that we saw over the past quite a few years now. Because it was so driven towards, you know, outcome and in many businesses growth and those types of areas. Whereas productivity is something that also plays in really well when you need to, you know, obviously have a better look at or a stronger look at your cost to make sure that you really are diligent in terms of how you spend your money. So I think it's trending towards that, back again now towards being more focused on the productivity side. How can we save time and be more efficient with the resources that we have, rather than doing something that helps us, you know, optimise for efficiency and growth towards for example selling more. So the good thing about this area is that it kind of plays both ways. You could use it for saving costs, or you can use it for growing your business. And right now, I think businesses are really looking to invest in this because it is something that helps them save cost.

Jane

Well, unfortunately, that's all we have time for this week. But thank you once again Christian for coming on the show.

Christian

Thanks. Thanks again for having me.

Rory

As always, you can find links to all of the topics we've spoken about today in the show notes and even more on our website at itpro.co.uk.

Jane

You can also follow us on social media, as well as subscribe to our daily newsletter. Don't forget to subscribe to the IT Pro Podcast wherever you find podcasts. And if you're enjoying the show, why not tell a friend or colleague about us?

Rory

We'll be back next week with more from the world of IT, but until then, goodbye.

Jane

Bye.

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Automation may be a key tool in any company’s arsenal, but the promise of implementing end-to-end automation – or hyperautomation – with no human interjection, is an unachievable distraction for tech teams.

It seems only a few years ago that businesses began incorporating artificial intelligence (AI) and machine learning into their processes. This is a far cry from the widespread usage these technologies now enjoy. While they’re undeniably valuable, and a properly thought out strategy can be extremely beneficial, some companies are stretching too fast and too far in the pursuit of an unfocused form of hyperautomation.

“Digital leaders have been surprised by the complexity of automation”, Bev White, CEO of Nash Squared, tells IT Pro. Despite this, a recent Nash Squared report reveals digital leaders are, on average, planning to automate nearly one in five jobs (18% of the workforce) within the next five years. White adds: “With today’s unsustainable salary demands, talent shortages and increased operational costs, it seems the business case for digital labour is getting stronger by the day.”

For menial jobs like document processing, which increasingly contribute to worker unhappiness, increased automation has a clear role to play. If executed properly, customers won’t know whether a behind-the-scenes process has been done at all, let alone if it was done by a human or artificial intelligence (AI). Indeed companies continue to invest in automating the back office.

What’s really being promised is a seamless customer experience (CX), and this is absolutely something to which every business should strive. Businesses that buy into their own claims, though, would do well to take a step back and assess whether their automation goals really fit their needs. On the whole, the industry-cultivated idea of ‘end-to-end’ automated ecosystems is doomed to fail, because complete automation of services is’t only impractical, but also fundamentally unnecessary.

Chasing the best customer experience

The industry perspective on automation has been skewed by its development phase, argues Bernhard Schaffrik, principal analyst at Forrester, but now systems are beginning to mature, the endless use cases simply aren’t there.

“I think the challenge is that automation promises were so easily harvested, during the times where you were experimenting with an automation technology for the first time,” he tells IT Pro. “The appetite grew, understandably, but many missed out on sitting down together and defining an automation strategy, or an operating model. I'm talking to many senior IT decision makers, and they are just driven by removing humans from the equation because humans are too expensive.”

Schaffrik maintains that without a clear strategy, short-term over reliance on automation won’t help businesses, and will hold firms back from properly delivering on CX. He calls for automation to be implemented only where it’s urgently needed, but for this implementation to happen alongside careful consideration of where the “human touch” is preferable.

“Customer and employee experience are the key to transformation rather than an 'all-in' pursuit of end-to-end automation, and looking at tasks in this way will help businesses focus their efforts on using automation where it will give them the most gain,” states Dermot O'Connell, senior vice president of services, EMEA at Dell.

Even when it comes to back-end tasks that don’t affect the customer experience, automation can be more effective when used in tandem with human workers rather than in place of them. Just as humans can benefit from automated tools to speed up their work, automated systems can become more ‘intelligent’ through observation of human co-workers. Extremely complex or critical tasks can also be deferred to human workers, to ensure quality and to save time on the development and deployment of the automated processes.

“Previous generation thinking about automation was that it was either zero or one: either the work was done manually, or these robots would completely take over that work,” says Ronen Lamdan, CEO of intelligent automation firm Laiye. “The reality of it is, when you apply AI, you never get to the 100%. The winning combination is actually empowering these human workers with digital capabilities, with AI capabilities, to take over the mundane parts of their work, but still retain people to service customers, to handle edge cases, to do the more cognitive intelligent thinking.”

The hidden, human cost of automation

In September, NetSuite made a number of automation announcements at SuiteWorld, its annual conference. Powered by AI and machine learning, the new features introduce ways to automate tasks such as invoicing, planning work schedules, and tracking employee metrics. The promise of end-to-end automation makes sense within the context of the ERP giant’s full suite, and speaks to a goal of providing customers with barrierless integration between services. Nobody wants to pay for a suite only to discover the quality of life features are all siloed into narrow use-cases.

But the reality is there will always be a need, or at least an ability, to escalate decisions to management level. Even in NetSuite’s keynote presentation, it could only advertise reduced manual checks for invoicing, acknowledging that the machine learning system has to escalate anything it’s confused with, to avoid costly mistakes.

In some cases, automated systems can cause more trouble than they’re worth. Business leaders are already running into implementation challenges, particularly where human labour is still required to shore up automated systems.

A prime example of this is social media algorithms, sold to the public as self-sustaining, automated content systems that occasionally requiring minimal human oversight. One of the main benefits, often touted by firms, is their ability to curb illegal and harmful content pushed onto the users’ feeds. The likes of Instagram and TikTok now boast systems to prevent such content from ever being seen by others, or delete content that slips through the cracks.

But this process is far from automatic. Every algorithm that recognises harmful content has been ‘trained’ by humans, whose manual moderation of banned demands they be subjected to the most disturbing posts. The churn rate of such roles is sky-high – far above the industry average – and driven by the intense and upsetting nature of the roles.

There’s no easy route to successful automation

White also notes that complexity is currently one of the top three obstacles to implementing automation. “What may have at first seemed like a simple process to automate, can quite quickly turn out to be a spaghetti of logic branches – which will also require some level of manual oversight even when fully implemented.”

This complexity is particularly true for firms that have not engaged in the right amount of testing or strategising in advance of implementation. If a system has only ever been trained in a vacuum, hard-coded with functions rather than learning them on the fly from active employees, its use cases could be outdated by the time it’s properly installed. It could even be detrimental. Similarly, if a system has been designed with a ‘one size fits all’ approach to end-to-end automation, companies could find themselves rushing to rip it out down the line. Waterstones’ recent botched AI stock system affair is testament to just this.

This framing is important to understand the issue overhyping hyperautomation has created. It’s not a ‘one size fits all’ framework for increasing efficiency, nor a silver bullet for a sector facing a skills shortage. There’s no doubt hyperautomation in action can achieve powerful results, but only when taking factors like employee satisfaction into account.

On the same note, human labour saved by implementing automated systems can lead to quality improvements for workers and customers alike. Proper integration of automation alongside workers can be a win-win, improving satisfaction and productivity levels. But the lure of end-to-end automation should never overtake questions around its practicality, nor be used to hide human efforts behind the scenes.

Businesses must foster Gen-Z’s sense of meaning through important goals such as sustainability targets, in order to maintain competitiveness and spur growth, according to industry experts.

In order to attract young talent, businesses should choose to offer roles in which individuals feel like they’re making a difference to the world, and maintain a culture of communication, business leaders have suggested. Organisations that follow this, and foster a culture that supports overlaps with sustainability schemes, could future-proof their business strategies and remain competitive in a market increasingly reliant on new talent.

Younger workers require a clear understanding of the moral value in their job, and sustainability schemes that include contributions from individual employees could fill this need. As Gartner recently identified sustainability as the key tech trend for 2023, and businesses increasingly bet on sustainability to tackle disruption, the field could offer returns in both investment and employee satisfaction.

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Alongside purpose, young workers increasingly demand honesty from employers, so maintaining a young workforce amidst growing drives for net zero carbon will require a transparent approach.

At a roundtable discussion, representatives from Dell, Red Hat, and Kyndryl spoke to a changing strategy in hybrid cloud, driven in part by the onboarding of younger workers, and gave examples of tasks that can meet these demands.

“It’s got to be something we can bring to life, and imagine,” said Tosca Colangeli, UK and Ireland president at Kyndryl.

“When we launched Kyndryl, we joined up with One Tree Planted, and for every employee that we had, we planted a tree. We wanted to do that to recognise the importance of the environment, and we all voted for One Tree Planted; choice is part of the cultural shift - it’s important on a personal level to be able to contribute.”

Firms were also urged to use clear language in order to communicate the effectiveness of schemes such as those implemented to reduce energy demand. For younger workers, this can feed into the wider needs for transparency and a sense of progress in work, but it can also prove the value of environmental, social, and governance (ESG) schemes to C-suite executives.

“They're super intelligent people, but they're not experts in zettabytes and kilowatt hours,” Dayne Turbitt, UK general manager and SVP at Dell.

“So, if you put it in context for them, in terms such as “by doing this, you save as much electricity as a million houses”, that really brings it home.”

Members of the panel said the shift in generational priorities has happened alongside a gradual slowing of growth in the cloud market, as businesses have begun to take stock of the systems they have in place before expanding further.

“There’s a period of consolidation now, which says “how do I manage these costs I have?”, said Colangeli.

“There's economic pressure, there's a demand for real-time information... the real prize is about the data we're unlocking in the cloud, and that's what we're really seeing coming to life right now, around artificial intelligence (AI) and insights. We're going to get from having all of this data in the cloud.

“You're going to have to get your house in order. You're gonna have to get some control over the cost, so you can reinvest in the data and the insights that really will game-change your organisation.”

Increased automation, whether in the back office or through robotic process automation (RPA) systems that share tasks with human workers, is one cost-effective way for businesses to maintain efficiency amidst economic downturn.

If implemented correctly, automation can also be used to improve employee experience, allowing workers to get on with more meaningful work in lieu of tiresome manual processes.

“The case for the return on investment and the case of the environment have never been closer,” Simon Wright, director, strategic solutions team at Red Hat UK.

“It’s the small gains, and I think automation and self-service are two key things which will help drive us in the right direction.”

Microsoft and Kyndryl announced an expansion to their strategic partnership in October, with the aim of helping customers improve mainframe data access. Dell and Red Hat continue to work closely on containerisation, and the Dell APEX consumption model to improve customer scalability in a landscape increasingly demanding real-time reaction to macroeconomic shifts.

Forrester predicts that due to the shifts in worldwide economic events, automation is quickly becoming a business imperative.

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This automatically-generated transcript is taken from the IT Pro Podcast episode ‘The rise of automated contracts'. We apologise for any errors.

Rory Bathgate

Hi, I’m Rory Bathgate. And you’re listening to the IT Pro Podcast, where this week we’re discussing digital contracting. As automation has been ramped up, companies have sought to improve manual tasks such as document handling using machine learning and AI. But when it comes to automation in the legal space, strategy is key. Contracts can be very complex and require human input, especially in stages such as negotiation — achieving the perfect blend of machine and employee oversight involves striking a careful balance. Rich Somerfield, CTO at Summize, to discuss the opportunities presented by automated workflows, and how companies can implement systems such as contract automation to improve efficiency and insight. Rich, thanks so much for being on the show.

Rich Somerfield

Thanks for having me.

Rory

So just to start off with, what are some of the current problems in the tech sector that Summize is seeking to address?

Rich

So Summize is a product that aims to make legal easy, so trying to understand what's in contracts, trying to help legal teams work with the rest of the business to understand what's in those contracts, and just overall processing those contracts. So we see our product is really like changing the game, in terms of how businesses work with the contracts and understand them. But yeah, overall, it's really just trying to make that whole process a lot smoother and a lot easier.

Rory

So in trying to speed up that process and trying to make that process smoother. What kind of qualities have you identified, that businesses are looking for, in IT contractors at the moment? And then vice versa, what kind of qualities are contractors looking for when they're forming contracts with businesses?

Rich

So I think it's quite interesting. So I've worked with contracts, never have actually been a contractor myself in the IT field, but I've worked quite closely with a number of different contractors, and for a range of different reasons as well. So some have been very specific projects with a very specific requirements and milestones, and others have been much more open-ended, kind of almost like as an ability to kind of increase your development team quite rapidly. But without kind of the fixed nature of a long term employee, so really kind of accelerated. I've worked on so many different projects. And those ones have seen both successes and challenges. But then really, in terms of the contractors themselves, it's critical to try and obviously find the right people, get them up to speed as quick as possible, and really deliver value. And like I say, I've seen successes and failures in that. And I think typically, it really revolves around a clear understanding, when you go into the process, about what the milestones are and what you want to achieve, whether that be a short term or a fixed event, make sure everyone understands on both sides what's expected, or whether it's a like I say, a longer term addition to a team to kind of accelerate other expertise or capacity. But then in those scenarios, given they are sometimes longer, longer ended, or, you know, kind of over a longer timeframe with with a less clear end date, I think again, it's really important that both sides understand what's happening and what's what's going on. What the end point is really.

Rory

So on a contractor side, being transparent, very clearly communicating what what a business can expect when they're entering a contract with you.

Rich

That's right, yeah, like I say, I've seen some of that have been very much more open ended, which is, you know, you've got a team, it needs more capacity for for many reasons, or it needs some expertise. And in some cases, they have been multi-year, in the end, they might have started out as kind of a couple of months that gets extended, keeps on getting extended, and then you kind of look around and it's they might as well, you know, have been a permanent employee for the time they've been with you. But, it's different. And obviously, it gives both sides at that thing, get their own benefits and cons as well. You know, from a contractor's perspective, they get the opportunity to work in an environment, a little bit of stability, but without the typical constraints of being a permanent. And then obviously from the business' side, you know, if things go really well, then you can look to different options moving forwards or if things don't go well the project closes down or whatever it would be, then obviously, you can, it's a little bit easier to kind of just agree an endpoint and kind of move on separately.

Rory

So when businesses implement solutions, such as Summize, they're really looking at, they could see benefits in the short term, but they're potentially looking at really great long term ROI.

Rich

For sure, I mean, in the IT sector hiring is quite challenging. There's been a massive increase into the supply side of things. Since I started 20 odd years ago, the supply has increased, but the demand has increased and exceeded that supply as well. So everyone's looking for the right people, and looking for the right skill set. And I think that really, everyone's quite different, which is quite interesting, the diversity that we're seeing start to expand. Traditionally, it might have been someone who went into IT in high school, and stayed in it and beyond. I think what we've seen over the last 10 years or so, is people actually transitioning from other careers and sectors. And I think what we've found is that diversity is actually incredibly useful, incredibly beneficial people perhaps being in the services sector, for example, and bringing that to the IT team. I think, yeah, that that kind of diversity has been incredible, really, overall.

Rory

Yeah, there's been a lot of discussions around roles such as CIOs, for example, really benefiting from people with maybe an HR background or humanities background. Do you see that contracts are kind of following in that suit? And there are there are greater discussions around maybe more flexible roles and pairing up companies maybe that traditionally, you wouldn't have paired up before?

Rich

Yeah, I think that's a really interesting idea. I really like that that thought process really like you say, you're looking at those combinations of different experiences, lead to kind of unexpected results, and unexpected and beneficial results. So if you've got people from different backgrounds, different ethnicities, different kind of previous careers, those combinations actually really generate a much better end result is what we've experienced. And I've seen from the different roles I've done, as well, I always kind of look to like innovation, there's some people look at innovation has being like magic, but really, it's just connecting the dots between different things that have never been connected before. So if you've got someone that's perhaps worked in, like you say, HR, or the service industry or anything like that, that then comes into an IT role, then they've got experiences, they can connect in to new experiences, or new understanding of IT. And it's those connections that if you've been in the pure IT role on your career, you're unlikely to see. But the connecting the dots is actually quite simple, if you've experienced it. We've got a strong ethos at surmise round DEI, so a dedicated DEI person, and really trying to make sure that we're doing the right things. Because it is easy to kind of stick to what you know, and recruit from people that you know, but you're really trying to make sure that you're looking outside of that. And bringing those different, different experiences in is incredibly beneficial, whether that be you know like I say, all the different backgrounds, or contractors, what it would be like you think of typical contract has probably done quite a few different contracts, seen a few different things experience have experienced quite a lot. They've they've got a wealth of experiences they can bring into a team as well. So like keeping those combinations there is incredibly valuable.

Rory

So taking into account a range of data points for any hiring process, any contract process that really evaluates people are more than just the traditional metrics.

Rich

Absolutely right. Yeah.

Rory

Fantastic. So, on the sort of more technical side of the solution itself, Summize is looking at using AI powered automation, and improving workflows to automate contracts, automate hiring. How would you go about combining AI powered automation and human workers to achieve a balance. Presumably, there must be situations in the creation of some contracts where things have to be, for example, escalated to a to a manager for oversight.

Rich

Absolutely right. So, we typically try to think a little bit more about augmented intelligence than pure artificial intelligence. I think artificial intelligence, is obviously a very broad, a broad area with many different areas of applicability, but really thinking more about augmented, that ties in quite nicely with the legal, with it being very much an advisory service. So you've got people who have trained seeing different things, understands the current business strategy and the appetite for risk, all that kind of stuff. And then really kind of tying that together with the direction that you're assessing contracts that coming in, or that you're drafting new contracts, we really see that as kind of a, very much a human powered activity, really, at the moment at least. But then bringing that in with where are the areas where computers can help make that process more efficient, more effective, perhaps more predictable in the areas that make sense? So coming into legal I, prior to joining Summize, I was had not been in the legal sector at all. And from a programmers perspective, you kind of look at the look at contracts, and you think "well obviously they're going to be consistent language, you know, everything's going to be like a, almost like a coding language that turns into a contract". And the reality is extremely, a long distance away from that. Contracts are very much bespoke. Everyone's kind of got slightly different favourite clauses and different words and approaches to tackling them. So I think what's interesting is how can you blend that variety with something that potentially is more predictable? There's been some initiatives in the industry for things like one NDA and one DPA, which is trying to kind of narrow down the ranges in contracts that perhaps don't need that ultimate flexibility in the drafting side of things. But, but in other cases, you know, you've got your most important supplier, and negotiating the contracts with them, you're highly unlikely just to kind of click a couple of buttons and let the machine generate the contract for you, you're going to want to be much more involved, understand, on both sides of things, and also build that personal relationship as well with the third party that as you go through that negotiation process, you both understand what the best result for you is. I've looked into negotiation practices in the past, there's some quite interesting podcasts out there. And they often talk about aim for the win-win, because almost certainly, whether you negotiate contract with that, that party again, or like a friend of a friend, you know, there's always kind of relationships. And if you get a reputation for kind of, even for win-lose negotiations, it's always going to come back and cause you challenges in the future. So yeah, the win-win's where you want to get to, typically you need relationships to be able to do that. And like I say then the computer software itself, just trying to support you and make that process a bit easier. And anything that is repeated, really take on the load of those ones. But keep the advisory nature for sure.

Rory

Right, so it's it's drawing on a kind of repertoire, that it builds up and understanding of, like you were saying, in-house clauses that are used more often while leaving leeway for, you know, leaving the door open to somebody to come in and create the more bespoke aspects of a contract.

Rich

Exactly right. I mean, one of the one of the capabilities we've built into Summize is to, like understand payment terms, for example, it's good example, payment terms. Now, obviously, if you're a supplier, you might want those payment terms to be going in a particular direction, you know, kind of payment terms want to be as short as possible. If you're a purchaser, you might want the payment terms to be slightly larger, obviously. So you've kind of got some kind of thing you're looking to, to optimise or to average out overall. If a contract comes in, and it's massively different than your average payment terms, that's something you probably want to know about. So, Summize software can do that, we can automatically tell you what the average payment terms are, how this relates to that one. And then obviously from from the human perspective, you're going to understand this particular contract with this particular third party, how important is it for us to get that one really tight on the payment terms? Or are we a bit happier to be kind of slightly more flexible? And that's really where that advisory part comes in. But as long as you have the data points to kind of guide you, then we see that as a real win.

Rory

So are you looking for the software to kind of learn over time? So you're building up examples for it? Are you looking to go for a more traditional route, of sort of setting out rules for the AI?

Rich

I think it's both. As with all these things, everything's a bit of a hybrid, isn't it? So you start with the rules to get a good baseline to get the data. But then obviously, over time, the learned behaviour element is incredibly helpful. We kind of typically think around things over three phases, really, when we talk about the augmentation. So, you start with the manual. So here's all the tools as a human, you're totally in control of everything. And then from that point onwards, then the next stage beyond that is like a suggested based approach. So "we've seen you do an X, we think Y would be the next best thing to do", or we think this is interesting to you, so really trying to help cut down the time it takes you to see the data point to understand what's going on. As you started to look at those suggestions, if the, if your use of those suggestions gets to a certain threshold, effectively what you're telling the system is that the suggestions are pretty good value. And then that's when you look to the automate. So everything we really do follows those three phases, really. So we'll start with the start with the repetitive manual thing, shift through suggested and then turn to automated. And we see that's a really nice, nice approach for tackling AI overall and integrating that into people's experiences, that you gain the trust, and then once you've — you know, really when when you look into any role via the if you've got an assistant or someone that's helping you do something or team of people, you'll typically follow the same process anyway, there'll be an education phase. Then you'll kind of monitor and then the trust builds up and you say, well, great, we're happy with all that goes and and then until something goes wrong, then we'll just keep going.

Rory

Right? Putting the AI on probation.

Rich

That's not it's not a bad way to think about it. Yeah.

Rory

So on that point of rules learned over time: some businesses, when they implement automation workflows, worry about leaving losing oversight of the process, over time, or pretty quickly. How do you manage this?

Rich

It's a really good point. And I think it's, I don't think there's a free lunch, when you're talking about this sort of stuff. So whether you're looking to automate something, or whether you're looking to do it yourself, there's always going to be some involvement in the process. So even in a fully automated system, you want to understand how well it's doing is it being effective. You know, you might have a fully automated manufacturing plant, but if everything that comes out, the other side has got defects in it, it's totally pointless, you've just wasted even more time. So I think keeping that regular quality control, staff check on how things are going, is it actually working is critical. So you just kind of change your involvement in the process. And that might, you know, may be the case that you can offload that monitoring capabilities. But it doesn't go you know, you don't go from having work to do to having zero work to do. It's always important to stay in the loop, even though obviously, the time involved in that, and perhaps the skills needed to do that oversight changes might free you up for more time. But yeah, if it's doing something on your behalf, I think I would always recommend that you keep an eye in to make sure it's doing it correctly.

Rory

Right. And then on the other side of that, I know that Summize, offers increased data insight into in contracts with a data system. What kind of data are clients typically looking to draw out of contracts in particular, and and how are they using those to improve their decision making going forward?

Rich

We say that businesses run on contracts. And I think when you start to think about it, you might might not think about it often. But when you start to think about it, it's absolutely true, everything a business does, is really signed into a contract. Whether it be for your employees, suppliers, or obligations, or whatever it be, it's in a contract, almost always in a contract somewhere, if not always in the contract. And then what we often see, is that people don't really have a clear view on what contracts they've been signed up for. Whether the contract sat in someone's inbox, which is quite often the case, that it gets signed, stays in the inbox, nobody ever knows about it apart from that individual, or whether partially centralised often in a slightly ad hoc way. So I think one of the key bits is like, can you get all the contracts into one place? If the business runs on contracts? Which obviously does, you kind of need to know what's in them, the first step of knowing what's in them is actually getting them gathered them all together, and have a process which keeps them all together. So it's one of the things that our product offers is the ability to kind of centralise your contracts. Then the next part there is to actually understand what's in them, and how that differs or aligns to your business risk appetite. So there's an element of that one. And then the other bit is simple things where they like, end dates on a contract, or maybe you've got to lease on your offices; when do you need to renew the lease? When when's the timeframe that you perhaps need to break the lease if you want to move? The cost implications of some of these things missing that date, is incredible. So one of the elements that we've got in our product is we automatically understand dates and their relation within the contract, whether it be a termination or renegotiation that whatever date, and then surfaced that into a central calendar, so even if it's even simple things like that one, giving visibility around kind of like the calendar for your contracts is incredible, but like I say it starts really around collecting them all together, understanding them, and then different parts of the business are interested in different pieces of information. Whether you're like, the C level might be interested more in the kind of holistic risk you have, and where strategic is whereas down to individual account execs are probably more interested in the specifics around renewals and delivery targets.

Rory

So on the product more specifically again, Summize offers integration with Word, with Teams, with Slack. Is that something that was based on customer demands? Or was that led by a specific concept of the system?

Rich

When the company started, it was really trying to help legal teams be more as effective and efficient with contracts, and legal needs, and I think what we what was pretty clear to us straight away is that a law department so in the existing business law department is often considered the cost centre. They don't generally generate money, but they really like obviously. but even though they're providing value to the business, they're not really like a revenue generator. So what what was clear is that any kind of budget constraints that they might have, for that team themselves, imposing a totally brand new system on the rest of the business, and getting the rest of businesses switched over can actually be quite challenging. And you look at businesses as well, they typically have services that they've integrated with, whether it be like CRMs, or whether it be your IoT side of things, or your document management, you've almost always implemented some kind of system. And you're unlikely to want to rip all those out and replace it with an all in one solution from your legal team, for example. So you're really kind of always trying to look to see how can you integrate that into the existing environment. And that's really something that's been critical to the way we've thought about the product, so integrated into office 365, or Microsoft 365, as it's now called, or whether it be into the the G Suite side of things, Slack, Teams, you know, these are the things that people are using today and continue to want to use, and obviously Microsoft Word as well, as is hugely used in the legal sector. So integrate what people are already doing, I think there's a couple of benefits there, the ease of adoption, obviously goes massively, massively improves this limited need for training. So that becomes a lot easier. And then obviously, working with the rest of the business as well, there's less of that pushback, because it's kind of where they already are. So one of the elements that we've got is the ability to interact with your legal team, we call it legal front door, whether it be for creating new contracts, or reviewing contracts. That capability is available Teams, Slack, or through the web application. So it's really easy to adopt. And then also, because they've adopted that piece of technology and something like Teams or Slack, for example, that chat experience is where we can start to preempt questions. So typically, and this always raises a bit of a laugh with any lawyers I talk to, but they'll typically get an email on a Friday at 5.30 with a Word document attached from somebody in the business that just says "FYI". What does that mean? When do you need? What do you need me to do? Do you need me to review it is an important client, you know, all that kind of stuff? The first questions you’ve got to ask are that information. Well, our software means we can preemptively ask that question before you even see it as a human. And I think when we come back to what we talked about earlier about augmented intelligence, that simple step of pre collecting that information is a huge value add. So, when the legal when the person in the legal team receives the request, they know who it's for how important it is, and with it being 5.30, can they go for the beer? Or do they need to kind of stay around and just and just do the work? Because that is what it is. So I think like I said, integration into existing tools. And practice is absolutely critical in for being a success. And it's really important to us as well, that our customers are successful, obviously, a long term partnership, but really kind of starts as quickly as possible. How can we get you to the point where you now see this project as a success? We'll talk about kind of expanding beyond that in the future. But yes, always around that first point where you're actually seeing the value. And I think the other bit to touch on as well is obviously we've all been through COVID and experience, experiences around that. And Teams and Slack, the virtual office. Before that it was used in some places, but probably a little bit kind of sporadically. More often people were used to kind of the in person meetings, I think what we saw very quickly was those virtual offices being adopted. And you only have to look at the Microsoft Teams, the usage went from double digit numbers in the millions, to many, many hundreds in a very, very short space of time. And I think even though we're you know, people are starting to move back into the office, bit more of a hybrid style approach thing. It's really, really centred around those virtual offices, still, people are still using Teams, because almost certainly somebody on your team is going to be working from from home on particular day. And I think really, that's where business happens now, in those environments, Teams and Slack. So it's critically important that the we're there in that mix, and we can be part of that story as well.

Rory

Right. So yeah, you'd say that if you're not coming into implementing automation with a specific strategy in mind for how employees can access that and whether it's recognisable or not, then you're almost at risk of immediate tool sprawl. I know that that's something that employees run into increasingly, with a range of different digital tools that they're being asked to use, it makes more sense to have them in in a single place.

Rich

Absolutely. I think I mean it's a great question really, because it talks a little bit to what are you trying to get out? You're buying some software, or product or whatever it is, what is the what's the win scenario for that piece of software? I think it's always an important thing is trying to identify, looking at, you know, six months or whatever, looking back, what is it that we get to this point of being successful? So, some products are more tool-based, like you say, and they are excellent at what they do. But they're probably confined and constrained in the kinds of impact they're going to have into the wider business. So the legal team, I'm sure, could make use of many of these tools, but they're never really going to go beyond the legal team in terms of effectiveness, really. So we think a lot more around kind of like business optimization, how can we help the business work better with contracts. Well, we're talking about the business, clearly, that's all departments, and every area. And in those cases, like you say the one off tools are probably not going to achieve what you want. And it's much more around the entire business process, making that successful in as easy a way as possible. And I think a lot of that really, many experiences I've had, and people I spoke to had as well. It's really that implementation phase where you have those business transformations, obviously, but it's the implementation phase where the business transformation really stalls. And so that's one of the real areas of focus for us, that we want to identify, like I say, the first milestone where you started to get successful, and then how it helped you through those. But that first point, if you can get that first point of being successful, the rest really follow a lot more naturally. Yeah, absolutely.

Rory

Something on once again, the more technical level, but that I noticed that Summize is advertised as offering the ability to scan documents for legal risks. How is that achieved? Is that using the same kind of repertoire of clauses that the AI has become used to? Is it identifying problem areas in that way?

Rich

I think exactly right, exactly what you've said. So we've got the ability to analyse contracts for clauses, whether they be PDFs or or Word documents, whether it's a scan, effectively a photo of a contract, and doesn't really matter to us. So we kind of ingest those, when we ingest them, we start to analyse them for the different clauses. The often what you'll see in a contract, as well as even though there might be a primary paragraph related to a clause, there's probably other sections all the way through the documents that have additional additional information or constraints around that clause. And I think typically, when you're looking at contracts, you might find the first bits or finding the subsequent bits is a lot harder from a human perspective. So one of the things we've got is to try to tease out those bits. So we'll tell you the highlights, the one we think is the most important, but then also, it's really easy to navigate through the other bits as well, that you may or may not have found. So I think that's kind of the ability, to kind of analyse it. And obviously, when we're starting to look at other entities, like dates, places, times, etc. What are they in relation to? Is it in relation to, like, termination or payments or whatever. So we can understand that information as well. Coupled with our ability to run the analytics across your other contracts, whether they're similar contracts or different contracts, you can start to kind of build that cross-contract picture now. How does this contract compare to others of a similar type? Is it better or worse? Or would it be? And what party is it with? Is that party something we genuinely have different terms with? I think all that kind of stuff from an analysis perspective, which which learns and adapts from usage. And then the other bit that actually ties in quite nicely to this as well is the concept of a playbook. So in case you didn't know, a playbook is typically you have a Word document, or maybe an Excel file of "given this particular scenario, this is what we recommend you do. If they disagree to X, Y, Z and it's come through three negotiations, then please escalate to somebody else on the team". So that kind of internal guidance, on how to deal with certain things. Again, typically, it's in a Word document that people print out, they're probably not always got the most up to date version, they probably always don't refer to it. So one of the critical things rules is for example, in Microsoft Word, which is where most most legal work typically tends to happen, we surface that playbook actually in Word itself. And we can be context aware as well, what you're looking at, so we can tell you about what the favourable positions are for or who to escalate to when you're in the contract, when you're reviewing it, and the time saved from that is incredible. Because that play book is also centralised, it means that any modifications to your positions over time are automatically reflected on everyone's system that's using using Summize. So there's real benefits to be had there as well.

Rory

Fantastic. So that that rating system as well, just to circle back to that, that that would be in house per customer. So what constitutes maybe a risky contract or a good contract for one customer, for another, it's a different set of a different metric that it's measuring it by?

Rich

Exactly. Yeah, exactly. Right. And I think it's not just different per customer, it's almost different per party per customer as well. So with inside one customer, they may have different parties, like I said that you know, that their most important supplier versus maybe some of the not most important ones, then you're going to be looking those and analysing those in a slightly different way as well. So that's all alternately possible.

Rory

Right, fantastic. And then just broadly, on the kind of outlook for automation in the industry: do you think that going forward, the old idea of kind of carving out the back office and just plugging in automation is maybe not reflective of what's actually going to happen? And that what will happen will be more of this integration between automation providing context, but work is still very much being in control?

Rich

I mean, for sure, let's say we talked about augmented intelligence, and I think it's much better framing, artificial intelligence feels a little bit scary, a little bit unknown. I think when you talk about it as augmented, it becomes a lot clearer about what you're trying to achieve. So look for the repetitive stuff, get the computers to do that. And then the advisory elements really keep that with the humans. But what benefitted or accelerated through data, to really try to combine those bits together, and when you look at some of the advancements we've seen recently in like text to image, some of these, the image generation stuff, it's phenomenal what AI can do. But it's, I don't know, if you've used any of these image generator things it's very, very much an iterative process. You put some keywords in, get some interesting images out, which probably aren't what you're after, three or four, ten, fifteen tries later and it's, actually something from that section is quite interesting. And that's a really good example for where the way we see things is you still got the humans involved in the loop. They're kind of managing and coordinating work that's done by a computer, you perhaps don't always understand how the computers got to a particular point. But if it's good data, then it's good data, whether it came from a computer or whether it came from a human.

Rory

Thanks so much for being on the show. As always, You can find links to all of the topics we've spoken about today in the show notes and even more on our website at itpro.co.uk. You can also follow us on social media, as well as subscribe to our daily newsletter. Don't forget to subscribe to the IT Pro Podcast wherever you find podcasts. And if you're enjoying the show, leave us a rating and a review. We'll be back next week with more insight from the world of IT but until then, goodbye.

Automation has been widely adopted across the sector, and firms have repeatedly applied it to laborious tasks such as document handling. Using machine learning and AI, a great number of documents can be processed, and decisions made without the need for painstaking human input.

But automation in the legal space requires careful thought, as contracts can be very complex and often require a human touch — here, a hybrid approach is needed.

This week, we spoke to Rich Somerfield, CTO at Summize, to explore the opportunity of automated workflows, and the demands of the legal sector when it comes to implementing tech of this kind.

Highlights

“I think what we've seen over the last 10 years or so, is people actually transitioning from other careers and sectors. And I think what we've found is that diversity is actually incredibly useful, incredibly beneficial people perhaps being in the services sector, for example, and bringing that to the IT team. I think, yeah, that that kind of diversity has been incredible, really, overall.”

“So typically, and this always raises a bit of a laugh with any lawyers I talk to, but they'll typically get an email on a Friday at 5.30 with a Word document attached from somebody in the business that just says "FYI". What does that mean? When do you need? What do you need me to do?”

“It's really that implementation phase where you have those business transformations, obviously, but it's the implementation phase where the business transformation really stalls. And so that's one of the real areas of focus for us, that we want to identify, like I say, the first milestone where you started to get successful, and then how it helped you through those.”

Read the full transcript here.

Footnotes

• Gartner: RPA software market will continue to grow as business demand increases
• What is Robotic Process Automation?
• What is machine learning and why is it important?
• How AI can help – and hinder – the supply chain crisis
• AI is now powerful enough to automate the back office
• How can CIOs help to close the tech skills gap?

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This automatically-generated transcript is taken from the IT Pro Podcast episode ‘How can we make procurement smart?'. We apologise for any errors.

Rory

Hi, I’m Rory Bathgate. And you’re listening to the IT Pro Podcast, where this week we’re discussing procurement.

Whether a firm is looking to ramp up its manufacturing, expand its IT solutions or improve quality checks across its supply chain, the initial stage of accessing good partners and contractors to make these changes happen is key. Procurement is an ongoing, complex process, and can be a drain on any company’s resources, even with increasing levels of automation.

This week we’re speaking to Sudhir Bhojwani and Lalitha Rajagopalan, co-founders of supplier engagement platform ORO Labs, to talk about how the implementation of automation has to be balanced with a clear strategy in order to cater to specialised services.

Lalitha Rajagopalan

Thanks, Rory. Glad to be here.

Sudhir Bhojwani

Thanks, Rory. Nice to meet you. Nice to be talking to you this morning.

Rory

Lovely to be talking to you. So just to start off with, broadly, what kind of issues in the market in the landscape? Did you identify that that led you to creating or, and smart workflows?

Sudhir

So the core issue that we identified is the amount of manual effort and pain that a business user fields in a company when they have to procure something, procuring something very simple like, for example, Amazon business has made great strides in the procurement world. And people, more and more companies are connecting with Amazon business and other suppliers. Amazon business is just one example. Of course, other such companies make simple buying easy. When it comes to procurement people are not just buying stuff, which are commoditized on Amazon business, but they're also buying something more complex like services, for example, equipment, for example, software, technology purchases. So these purchases are larger purchases, they are pretty complex purchases, and purchasing through the system. It's a lot of manual effort, actually today, in every organisation. We come from a city Alibag, where we spent a lot of time a lot of big companies, we found even the best adopted procurement companies who have a procurement system in place, a lot of their purchases is still highly manual. And experience is, let's say, not Amazon-like and it can take weeks and months to work with suppliers. And if you take on supplier perspective, the pain is even more acute, if I'm a small supplier trying to work with a large company. And it takes me two months to get to the process. Because I just happen to be a small supplier and the customer is treating me like a big supplier. So that conflict that exists drove us to thinking hey, can we automate this workflow in a more interesting way where the friction between buyer and supplier can be reduced considerably. And that's what drove us to building this. And because current solutions were not built to solve the core user experience and removing the friction problem, to the degree we think we can and it's also driven by the complexity of the semantics, people assume people are buying standardised goods and services. The current procurement systems are designed for standardised goods and services. But people forgot that people buy a lot of non-standardised goods and non-standardised services and technology purchases have gone up, compliance requirement has gone up, everything has just actually gone up. And how do you still keep things ticking along and make the workflow automated? That's kind of why maybe Lalitha can chime in as well.

Lalitha

I think one thing I'll add here is that if you look at the current procurement technologies, they were all designed for a very simplistic spend approval, like yes/no. And most of it is basically, you know, should you be spending this money or not? And most of the time answer is no, unless it's been, you know, pre-procured by procurement kind of a thing. So even procurement has a big pain here, because right now when it comes to anything that is bespoke, or something that is specific to a business need, like I'm in marketing, I want to work with an agency for a specific project or something like that. Procurement really doesn't have any tool beyond throwing people at the problem they can take a ticket and then they have to figure out how to help the user navigate it. So feel the procurement technology is very stuck in a simplistic world. And procurement is not getting the help that they need, to help the business user make do it faster, do it better and keep the company protected. And I think that friction is in all user points and context is missing in how decision making happens today, if you just make it about spend approvals, and we felt that it was time for a richer and more cracked experience which will make it faster.

Rory

So not just, kind of, smoothing those those decisions, but also deepening those decisions and putting them into like you're saying into a wider industry context, and allowing businesses maybe to view a wider range of suppliers with with all of the necessary context? I think at this point, it could be good for those who don't know if you both could briefly outline what exactly Smart Workflows does in comparison to the standard model.

Sudhir

If you think about a procurement workflow today, most people will relate directly to this, we'll use the word approvals. People think of it as approvals. But the truth is, a lot of things happen in a procurement which is which goes above and beyond approvals. So as an example, if I want to buy the marketing service that Lalita mentioned, first thing I would like to know is, is the vendor already a vendor that we have done business with in the past? Second thing we'd like to know is, is an MSA in place? Are the contract rates in place place? What ave they done for us in the past? Do we need to get IP agreements in place? Is this an engagement that requires GDPR compliance? Is this an engagement that will require some more security consideration? So that's lots of considerations that are way beyond approvals, budget approvals. And, I also like to use the word, it really is a workflow, things go through step different steps in the process. Different people actually do certain things beyond approvals, like for example, negotiating a contract, I would not think of this as an approval, you negotiate a contract, and potentially afterwards, the contract needs to be approved, actually. So a lot of stuff actually happens. So when you think in that direction, so workflow is actually quite more complex, and it's not just approvals. That's how I would think of the problem more than anything else. And the reason we do things we decided here, we call it smart procurement workflows, it's plural workflows, because we don't believe procurement is one workflow. Because if you think about it, the way people procure marketing is not the same way, the way people buy software. It's definitely not the same way people buy raw materials, very different processes, you can imagine the workflow is different, the requirements are different, everything is different people involved are also different. And the reason we thought 'smart' is also equally important, is for the workflow to be effective, it needs to be smart as an example. It should not be the same whether I'm working with a brand new vendor, or when I'm working with a vendor, which I've already done business with, but my certificate is in already. Let's say I'm doing some construction-related work. And the health and safety certificate is already in place. Should we again, do health and safety? The answer could be yes or no depends. If the safety was done 30 days back, and I'm just starting a new, maybe you don't need to do it. On the other hand, if the safety certification was done two years back, maybe you need to do it again. On the other hand, if it was never done, you definitely need to do it again. So, the smartness really also means it needs to understand these concepts natively, and there are many such concepts, health and safety is just one. Sustainability is another concept, security is another, privacy is another, there are lots and lots of interesting concepts that companies have to deal with. And if you don't do smartly, you will end up doing same thing again, and again, for no good reason.

Lalitha

If you look at organisations today, you know, compared to say, 10-15 years ago, 10-15 years ago, it was very command and control kind of a model, which is very hierarchical. And you could have, you know, the process kind of laid out top-down, right. And I think the big difference in how people work today, modern companies are much more democratic employees have a lot more agency to do what they need to do to get the job done. And when people talk about oh, "speed of business" and everything, there's something fundamentally at core that's happening, where, you know, companies give a lot of room to people to operate the way intelligent people would want to operate based on the context, they're not really dictating the procedural aspects as much. But that also means that anything that's a centralised function, whether it's procurement, whether it's IT, whether it is legal, etc, they are stuck in a world where they have to have a customer service mindset with the employees and organisation to help them you know, to do what they need. And we see saw in IT, right? It went from, 'you can't even upgrade your browser' to you know, 'bring your own device', kind of a thing. And so it's really important to understand that then the central functions there is, it's very hard for them to always keep up with the context, and they are shrinking and shrinking their NPS score, and the operational SLAs are highly scrutinised. And so, our goal is that smart procurement workflows have to have context embedded in it, and it should adapt organically to the context. You don't have to rely on a good person in every department reading every request correctly, and doing the right thing. Smart nurses can auto context triage the workflow as it moves through the system, can the system itself basically make it easier for legal to review or IT to get the task done, or whatever it is? And it also needs to have understanding that oh, legal likes work in a different system, or IT uses something else, to be able to integrate a process across different tools. So 'smart' implies all of these things.

Rory

That's interesting what you're talking about with the kind of cross silo experience there. Something I know that a lot of firms implementing automation right now are contending with? Is this idea of things having to still be flagged to a to a higher level, how do you balance a kind of end-to-end, cross-silo solution with that need for maybe certain huge procurements or maybe ones that are flagged by the system as a one off? How do you balance that with that seamless end-to-end experience?

Lalitha

So it's really interesting, you bring that up, right? Like, one of our customers is, you know, a fast growing biotech firm. They have a policy, which says that, hey, anytime you spend more than $100,000, you need to have competitive bids. Okay? Now, oftentimes what happens is, when a scientist is trying to work with something, you may have a very unique thing that you want to get. And there's a bit pretty much a single supplier, who basically is the right supplier there, okay. Now, what you do not want to do is to automatically keep red flagging this, and it becomes a red herring, it's a false alarm kind of thing. So how do you basically make sure that you're helping the business user, and you're helping the procurement, and you're helping the executor who has to approve the one off? Think about it that way, right. So what a smart workflow will do, is it will actually not wait till the user fails, saying that, "Oh, you don't have an alternative," it will tell him right up front, it'll give him the in-guided policy guidance to say, "Hey, you're trying to buy something that's going to cost more than 100k. The company policy says that, you know, it should have a competitive bid, do you have a competitive bid? Or an alternate supply you'd like to consider? Or is it a unique situation? Like it's a unique supplier or something like that?" So the user is guided to provide exception, right there, they don't fail it and then go back. And then the second thing it does is that, from a procurement process perspective, it allows them to say, "Yes, I know this to be true." So they can kind of comment or annotate that. And it also allows, nobody wants it to go to like, you know, the CEO without the you know, CEO minus one kind of being known notify. So you can compose a workflow to say, hey, heads up to someone else, but then summarise it for their review to say, hey, the reason why this is so is because of this. So it comes with the notes there. So you're not trying to then think back and say "hey, why are we doing this?" or something. So how do people feel comfortable making decisions only if they understand the context? So, can you gather context along the way? So smart workflow doesn't mean that oh, intake is complete? And after that is just, you know, yes/no, yes/no. It basically collects context along the way. So that's one of the ways in which we make sure that, because at the end of the day, it's human beings who are deciding and human beings are doing it asynchronously. How do you make sure we carry context along?

Rory

That's very interesting. It seems like instead of keeping those processes under the hood, as it were, with automation, maybe that just that extra bit of context, that extra insight into why an AI is making the decisions it's making can kind of in turn, make all the difference when it comes time for people to make decisions.

Lalitha

What you said is exactly right, the visibility. Because today, users feel frustrated with procurement, because they are like kids stuck in the backseat of the car asking the parents "are we there yet? Are we there yet?" It's like a complete black box, and one big part of it is making the visibility of what's going on and why it's going on.

Sudhir

All right. I think it's such a, I mean, if you this is people think of this procurement as a ticketing problem. So hey, I just need to create a ticket and somebody will work on it. The truth is procurement is actually quite a complex workflow. That's why we really wanted to focus on the workflow. And we had, we took a workflow from from one of our customers who is live with us globally, now. They're doing, they're executing workflows in 60 plus countries with us. And they had the current workflow implemented on a ticketing system. And what they realise is, even though everybody was creating a ticket for someone to execute, it was not consistently even executed. Different people who got different tickets, they're executing it differently. Because it was not thought of it as a workflow problem, it was thought of as a ticketing prop. problem. We believe what procurement is much more of a workflow problem than a simple ticketing problem. Of course, the ticketing involved in the middle of the process sometimes, right, of course, but it's much more of a, "Hey, what is the step one? What is the step two? And how do all these things come together?" It is a complex data problem. How does the data flow from point A to point B? How does it and how do the decisions get made? How did the risk event how is the risk evaluated along the way, and that lots and lots of interesting stuff that you have to do to make the workflow be executed in a consistent and accurate way every single time? Regardless of who's involved?

Rory

That's really interesting. On that wider point of visibility that came up, I know that something that your system advertises is the idea of qualified suppliers, showing suppliers that overtime, accrue a kind of rating or qualification. I was wondering if you could talk a bit about how precisely that system works, and also how you balance a kind of internal qualification system with maintaining competition in the market, and maintaining a range of suppliers for any given customer.

Sudhir

So I'll start broadly and then I'll let Lalitha also chime in. So it's a good question. Firstly, let me start by saying, in procurement, the most complex object is supplier object. Like in CRM world, you would say customer is the most complex object. In procurement world supplier is the most complicated. If you look at the supplier in ERP, it has more fields than we can imagine. And every customer we talked to, including small customers, by the way, and I'm not talking just about really multinationals, even small customers, they have problems such as duplicate supplier records. My data is not clean. It is like my mailbox, I clean it, it gets dirty before I know it. So that problem is absolutely true. And then the question then becomes is, why is this even important? If you think about it, I'm trying to do business with a supplier. And I don't even have a good view of a supplier object. How can the workflow be smart? So our core premise is, we need to have a good understanding of supplier objects. So when you think about auto, what one of the important things in smart also is, we are not just a horizontal workflow engine that can solve any problem and every problem. We are geared to solving procurement, because we have a deep understanding of the core supplier object. So we understand how does the supplier object map into ERP, whether it's Oracle, whether it's SAP, whether it's NetSuite. We know why duplicate vendor records exist. And people think, "Oh, they exist because of a mistake". No, sometimes duplicate vendor records is the right answer. Let's say like, one company acquires another company, they both were doing business with the same exact supplier. It's not reality to just merge the two vendor records off requisition immediately, it's not reality, because there could be some transactions out there invoices to be paid, etc, etc. And there could be other terms too, right? So various reasons why I cannot merge the two records, but I want to still merge my ERPs. Right? So duplicate vendor records will exist. But one thing we saw actively is we give a view of the supplier, which is beyond duplicate supplier records, but now think what supplier itself, it also happens to be a company, which may have its own legal structure. They like, we are a very small company, always a small company, we are a startup. But we have two legal entities, one in here, one in India. And if you look at some of the other companies, they will have hundreds and thousands of legal entities. When you try to do all of this stuff. User is possibly extremely confused, "I have no idea what this jargon means. I don't understand what ERP means to begin with. I don't know what legal entities mean to begin with, secondly." But these two worlds have to come together, unfortunately. And the workflow has to do it effectively. So to answer your question, a lot of that revolves, that's the first piece of the puzzle, this is just the basics. The second thing after that is if you ask — the running joke in procurement, if you want to know what your company is doing with the supplier, ask the salesperson. And the supplier's like, he will tell you what your company is doing with them. And that running joke continues in the world. So our system is kept, and the running joke happens for a reason. There is no system, there is nobody who owns a supplier object today actually effectively gives a view of a supplier, that is really useful to the business use. Think about it. If I'm a business user, somebody in marketing, I want to find out what are the, what agencies we use to create some sort of production videos last year, or a year before last. Nobody can answer that question today. So our answer, we want to build a system that can answer those kinds of questions in a much more effective way. Lalitha maybe you can add.

Lalitha

I think the only thing that I will add here, is that the end vision for us, right end vision for us is we want to essentially be equivalent of CRM on the supplier side. Okay. And the reason why workflows and this kind of come together is because we realise it's not a data problem, it's actually an engagement problem. So it's really important to have a self-curating view so that when you think about a supplier, the system should logically be able to provide context of "hey, what are all the activity engagement that's going on with the supplier?" Again, going back to what I said about how companies operate today, today, even having view of what supplies my company does business with is very well hidden. So the core of our experience is being able to have that view. And also to enable to your question peer to peer, you know, discussion. And peer to peer ability to understand supply contracts, like think about is the water cooler effect, right? Like, I'm in marketing, I'm a new employee, and I want to start a project, I probably want to talk to other people in my team to say, "Hey, have you guys work with these guys will be like to work, how would it go?" And then you can very nuanced feedback, you get feedback, like, "yeah, this team is great, make sure they assign this project manager, that's the A team. And when you do the contract, make sure they do this, they'll say no, but we've done it in the past, just tell them, you know, this contract, we've done it." This is normal, tribal knowledge that is completely lost. So it's not just, you know, company name, company address, company logo kind of thing, you need this richness of context to enable better decision making. So at the end of the day, right, if great CRM for suppliers is going to help customers, companies essentially work better with their suppliers and make better decisions with the supplier, it should result in two things, I want to be the customer of choice with the supplier because I can work with them better, which means my company employees in my company can work with them better. Which means that every time a supplier shows up, it shouldn't be like, you know, you're starting from scratch, again, name of the company, everything. I should know you I should give you a red carpet welcome, I should know exactly how to work with you. And that tribal knowledge is kind of enabled. So that's kind of how we envision it and it was a long, a little bit of a road to go to kind of build it out that we believe that technology today. That's possible.

Rory

That's fantastic. So do you think that this, you described it as tribal knowledge, do you think that AI offers a kind of new opportunity to retain this tribal knowledge in organisation far longer than normally, you would be able to retain it manually? Because you know, people would leave them and with them, these relationships would go. So do you think that AI is a kind of a it can it can store that memory and retain that through through the years?

Sudhir

To be honest with you, I would say the two parts of the puzzle answer. First is not even AI. It's just the basic structure of the system. And the system is geared to store the data in a some, in I would say smart way. AI is different in what you learn from it, right? So first is can the system, I think you also asked the question, what granularity can you sort the data? Is the system designed to, does it understand the complexity that, hey, the supplier object exists in ERP with duplicate records, or the supplier object also exists in my contract management system. But that looks very different. And there's no connection between the two systems. Then the supplier is an existing company. So that whole jargon, it understands first and foremost, and that's not an AI, that's a more of a structural problem. Do you have the intelligence to do this? Now second, is what you can derive out of it. And I believe that's where the AI can be really, really helpful. A very simple example. We don't think of it as an AI. But nobody ever goes to Google on page number two, every result comes on page number one, is it AI? Or is it not AI? It's definitely doing a lot of learning, I tell you that much, the algorithm does a lot of learning. It's a highly, very curated high, it does a lot of learning, based on which it knows what what results to put on the rock top rank. So I think those are the ways we are thinking about AI problems. If people are saying, "Hey, can you make sure that if I type in, you know, almost what I'm typing and why I'm typing and based on that the recommendations that come out, are very accurate?" So this way, I can make decisions faster, smarter, better. And that's how at least the AI will come into play. And then of course, we can take it to the next level. How can natural language be used in a more interesting way? Because there are some really interesting power in procurement. Like for example, when you look at procurement of the cost of a commodity, what are you trying to buy with the supplier? Everybody's trying to map to this concept called 'commodity tree'. Some of some commodity trees are extremely complex, there's something called UNSPSC, which has like 27,000 nodes in it. Now picking a node from 27,000, good luck. I mean, and they're horribly — I mean, not horribly, it's not designed for human being let's call it, it's designed for systems. So the human being can't necessarily understand that. Can we use natural language for user, to describe what they're trying to do, and we figure out the rest? Simple problem, of course, compared to the supplier problem, actually. How do you make sure the suppliers are aligned correctly, etc. So yeah, that's how we're thinking about AI. So there's a lot of AI work that is needed to make this happen. But also the base, base application layer has to be strong to handle this, otherwise, nobody is gonna help.

Rory

So with all of that in mind, bringing in the improved structure, bringing in AI, where it helps. Would you say that this is more of a long-term investment for businesses, that the savings or the returns that we'll see are, are going to be more in the long term? Or are you also finding that customers are finding that, in the short term, they're seeing things dramatically improve by adopting automation within their workflow?

Lalitha

So I definitely think they have an immediate need, and an immediate ROI to this. So one of the ways in which it's immediate is that we are an audit ready system, which means that companies can feel confident about having an accurate picture of are we compliant in our engagement with the supplier X, supplier Y, okay? And what was done, what was not done? What's missing? So that's the question that you don't have to do analytics and reporting to do is like, right there. The second way in which I think the benefit is pretty immediate, is that often times when Sudhir said that it's all bespoke custom complex things that people are trying to, you know, work with the supplier for, you know, you are throwing people at the problem in a regular ticketing kind of world, only the procurement can keep up in a fast growing companies. Like I'm adding, you know, a dedicated procurement person for, you know, this department, that department. And by composing smart workflows, which kind of bring the context along, you can do more with less people. So I can, my immediate ROI is just operational cost management, right? I can scale more and better with a workflow tool, which is more sophisticated like this. The third value is actually, if you think about the supply chain disruptions and everything, it's really important to know, not just for procurement to know, but for the organisation to know, who are all the suppliers that we already kind of have an engagement with, what are they capable of doing so that I can basically start with searching or existing suppliers, and front and centre that is what is there in our experience. So I definitely think the ROI is immediate. However, in the long term, the long term, it's even more. I think it's an exponential value for you to say that I can have a consistent global process. That I can start my rollout and say UK, but then I can do North America, Asia, whatever. But from a process governance perspective, it can be consistent process, but it is done in a local context way, right? Like in UK, your quality check can be done by the quality team in Manila, maybe you outsource it to somebody. But so this is a checklist that needs to kind of work through etc. Right? So you can do that. And the second thing is also like, you know, I think having, it's a big competitive advantage for customers who say, I know how to work well with suppliers. And to build that internal competency, it's a constant curation and data problem. And that is what rolling this out in a global way would allow them to do.

Sudhir

But I think I like two use cases that highlights the problem. So one use case is, we work with a customer, we work with their marketing team, in particular in this use case. And marketing team says "Hey, my current procurement process will take me two months to work with a new vendor on this kind of a topic on this kind of engagement." What is the value if it comes down to two days instead of two months, to the business? It's not just the savings, definitely the savings. And I'll talk about that in a second. But the in marketing, that means they can do the lead gen faster, which is amazing. So the outcome procurement has been dreaming about how can I do that? How can I have a direct impact on top line, I believe speed is an important factor to deliver value on top line, especially when you talk about the business driven spend not. So that's one. Second thing I would say is, just talking to a CRO of a company. They say we our CFO does a monthly meeting, where we are all trying to say look at given the market conditions, we're trying to see how do we drive the savings? What contracts are possible that we can put a potentially put a pause on so we can save some money though savings is still an important part. And it's gonna get trickier next year, I think, given what we're seeing in the market, right? And they say this meeting is extremely complex the amount of preparation that goes into this meeting, and we still don't have visibility into what we can put a pause on in terms of discretionary spending. So our system, when we implement the workflow correctly, it also generates the right amount of data to make literally real time decisions. Now you can make real time spend management decisions, which actually are very tough to do in current systems.

Rory

That's very interesting, I think that point of of insight through real time data, and also the automation of compliance, are these both pain points that you're seeing common throughout throughout the industry throughout your customers?

Sudhir

Yeah, yeah, absolutely. I think if you look at the spend management problem, if getting more serious, more serious, and people really, really need to have a system. Look, I think spend, you can't manage the spend until there is a full adoption by the business user. So you need a system that first and foremost has the business users, so that adoption is high. Once the adoption is high, and then you need the smart system that gives the data in a shape that you can do real time decision making on that, so that you can control the spine, so generate the right data. So it should not be that it should not just be act as a repository, it should not act as the repository just. So we that so we see that as a pretty big driver. On the other hand, if you look at some regulated industries, like say, financial, financial institutions, like banks, for example, for them, this is not an optional thing. I mean, the kind of fines that you will see without onboarding and offboarding a supplier correctly, not following a consistent process to onboard — not just onboard, offboard too, by the way. Consistently we have seen fines of 60, 70 80 million dollars being applied by OCC. And this is a global problem. So I think on both ends, you'll see really lots and lots of examples.

Lalitha

I mean, to underline the smart procurement workflows, right, Rory, I think that simplistic spend approval is an ok system, if all you want to do is to track bookkeeping, record keeping, cut the PO, pay the invoice somebody approved it. But if you want a modern, I think modern enterprise software has to go beyond that it has to be a system that enables better decision making. And in the CRM side of the world, you kind of see that right? The modern ref tag, the CRM tag, all of them allow for a lot of, you know, a curation to be able to make better revenue management decisions. And I think that there, you don't hear revenue systems CRM system talking about order to cash and stuff like that, right? Procurement technology today still spend approval, you know, source to pay, procure to pay, it's kind of still stuck in that world. And I feel that in order to have a user experience where users actually want to use the system very early, it was only possible if it actually allows them to work better, work faster and make better decisions. And if it is just going to be like, you know, I need to, you know, file taxes kind of thing they will avoid as long as possible.

Rory

So it's it's not just about, it's not just about the fear of replacing workers, which I know is always tied to automation, but it's also about giving workers like we were saying earlier, that context, that ease of mind that they can go in, and the system will assist them in doing their job properly.

Lalitha

Yeah, like if I'm a facilities manager, I'm in marketing, if my job is important to me, and my job depends on me working with a supplier. So I'm, I'm inclined to do whatever I need to do to get the job done. And if a system is default, designed to say "no", for anything that is not standard, I kind of want to avoid it. That makes sense. So I can always ask for forgiveness later I think.

Rory

I think expanding on that, too, do you see this as a model that companies will be aiming for, or should should be aiming for in the next few years? Implementing not just more optimised workflows, but also AI and machine learning in this way to, as a kind of a backbone and the back office, but also to provide this this extra context?

Sudhir

Yeah, absolutely. I mean, I think the supply chain disruption has made supply chain as well as procurement, a whole lot more important and opened people's eyes that, hey, this actually impacts us. This is not just a back-office function, where a sub-optimal system will suffice. Or just a back-end process on an Excel is also okay. It's okay for us to not even know which supplier does what for us. And that is hidden in an Excel sheet. And we can't figure out from a spend management perspective which projects or which contracts we can put on pause and save money. All these decisions are important, and if not done in real time, I think people are starting to see this. So if you look at the general investment in SaaS, obviously CRM always leads the way. Everybody wants to make money first, I think before they worry about saving money, generally speaking, so the CRM always sees a lot of investment. And HR investment is natural, you have to do an HR investment, you cannot not have hire people and not know how to pay them, or not know how to track their benefits. So HR investment is clear. So the procurement has been the almost a little bit, in the back in the queue. But now the supply chain disruptions, and the dependencies on global economy are now more and more things are coming local as well. So this whole shift in the global economy is, people are realising, oh, this is an important part of the puzzle. This is not just Excel kind of a system that I can live with, I really need to have a smarter system. So I believe this, this area is gonna see a tremendous investment in next five years. That's kind of our bet anyways.

Lalitha

Yeah, so basically, you were using the word backbone, right. And I think that, you know, I see ourselves as a new age platform, which is actually not under or behind, but more on the top right. And I think that a good analogy to think about is actually smart home automation, right? Like, everybody has old homes with old wiring, etc. But if you think about modern home automation stuff, it is doing two things. One is my smart light bulb senses, its context of that, "oh, it is getting dark so I need to switch on". Or my you know, "resident is away, so I need to pretend that there are human beings here", right? You know, and it basically I can talk to it, it's very talk to me baby kind of thing, I can say, "Hey, turn on the music in the living room, it's gonna rain, therefore, I should turn off the sprinklers" kind of thing. So and I think that in enterprise software, especially the SaaS explosion, with every department having a very specific tool for doing some job, there's a new layer of technology, which is more like a fabric, which is the word for these users, which is going to unify the entire context. But it's not just you know, routing, it's not like an RPA kind of thing, like take it from system A to system B kind of thing, just a routing logic kind of problem. It's a context gathering, and context service problem. So that you can essentially provide a layer of seamless start to finish automation, which is kind of what, you know weird enough, in a consumer world, you're trying to do the same thing, like, you know, can the can an operating system run my house kind of a day? Sudhir, can you talk about just one thing, I don't think we touched upon it in a specific way, which is one of the things we're trying to do is to work with external data repositories. Like for example, you know, if a company is a UK-based company, then we know how to work with Companies House to kind of validate that entity and things like that, right? So can you just bring in this data context?

Sudhir

Yeah, I think while customers find it very interesting that we actually integrate with their ERP, and our, one of our goals is to give a good visibility of an existing suppliers. That's a really tough problem, actually. Because as I said, duplicate vendor records exist. So how do we take the existing data and turn it into something that is fully searchable? And I always felt this way, is if I searched for IBM as a company in a procurement system, then I searched for the same IBM on Google, the knowledge panel of Google on the right hand side gives a pretty interesting piece of information. And that information seems to be more interesting than the information I have in the company. When I'm spending $4 million at IBM. How can that be? Public information, public sources have gone a few notches, let's say a lot of really, really interesting data sources. And one thing we are doing is, we are enriching data from various data sources. Obviously, our use case is procurement, we're not trying to build ZoomInfo for our goal is not to be ZoomInfo. But our goal is to really get the right data, so the right decisions can be made faster, and that lots of interesting data sources we're using right now, to get that enrichment done so we can deliver higher value in a smart workflow. So our goal is smart. Smart is important is not just candy, candy word, in the slogan. I believe, without smart workflow, people will continue to do the same thing. Same mistakes will happen, and then we'll wonder why it takes two months, what should take two days, and we believe without proper data, and without the proper, proper context, it will never happen.

Rory

Well, thank you both so much for being on the show.

Sudhir

No, thank you, Rory. It was pleasure, pleasure talking to you, and hope to connect with you again sometime in the future.

Lalitha

Thank you Rory.

Rory

As always, You can find links to all of the topics we've spoken about today in the show notes and even more on our website at itpro.co.uk.

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Procurement has long been treated as a ticketing problem, with check boxes to fill and suppliers to onboard according to regulation. But with increasingly sophisticated automation systems, and a growing need for exact partner agreements amidst global supply chain issues, companies could do well to rethink their linear approach to procurement.

This week we talked to Sudhir Bhojwani and Lalitha Rajagopalan, co-founders of supplier engagement platform ORO Labs, about its ‘smart’ procurement strategy, and the place that automation has within the procurement workflow.

Highlights

“If the safety certification was done two years back, maybe you need to do it again. On the other hand, if it was never done, you definitely need to do it again. So, the smartness really also means it needs to understand these concepts natively, and there are many such concepts, health and safety is just one. Sustainability is another concept, security is another, privacy is another, there are lots and lots of interesting concepts that companies have to deal with. And if you don't do smartly, you will end up doing same thing again, and again, for no good reason.”

“Think about it that way, right. So what a smart workflow will do, is it will actually not wait till the user fails, saying that, "Oh, you don't have an alternative," it will tell him right up front, it'll give him the in-guided policy guidance to say, "Hey, you're trying to buy something that's going to cost more than 100k. The company policy says that, you know, it should have a competitive bid, do you have a competitive bid? Or an alternate supply you'd like to consider? Or is it a unique situation? Like it's a unique supplier or something like that?" So the user is guided to provide exception, right there, they don't fail it and then go back.”

“Users feel frustrated with procurement, because they are like kids stuck in the backseat of the car asking the parents "are we there yet? Are we there yet?" It's like a complete black box, and one big part of it is making the visibility of what's going on and why it's going on.

Read the full transcript here.

Footnotes

• ORO Labs
• What are digital workflow solutions?
• What is customer relationship management (CRM)?
• Gartner: RPA software market will continue to grow as business demand increases
• What is Robotic Process Automation?
• What is machine learning and why is it important?
• What is the supply chain?
• How AI can help – and hinder – the supply chain crisis
• AI is now powerful enough to automate the back office
• How smart homes are the next frontier for independent IT providers

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Intelligent automation firm Laiye has forecasted the end of subscription models in the IT industry within the next five years, citing the inadequate extent to which such models can serve growing automation needs.

Laiye's chief strategy and ecosystem officer Braham Shnider said 'rip and replace’ requirements currently imposed in the software as a service (SaaS) market, in which companies have to remove current systems in order to update to new ones, are an ineffective model for automation.

This is because of the way that Laiye argued end-to-end automation will have to work, as a combination of automated 'digital workers' - programmed bots performing specific manual tasks - with humans working alongside them.

In such a system, digital workers could be loaned for specific tasks like a rental car, rather than paid for as part of a wider systems package in a costly, yearly subscription.

Instead of subscription models, the firm is proposing a more ‘open’ automation ecosystem, replacing digital transformation and vendor lock-in with ‘digital transition’, to address the skill shortage gaps experienced by each company.

In the coming years, the company believes digital workers could be paid for by firms through a consumption model, with a set amount given to vendors per process carried out, akin to virtual freelancers.

“For example, we can provide an invoice-processing digital worker, and we can charge by the number of invoices that digital worker processed,” said Yichuan Hu, co-founder and CTO at Laiye, to IT Pro.

“It's no longer 'you need to pay ten thousand for this digital worker, for a year'. You just take, say, 10 cents for every invoice this digital worker processes. So that will actually be more attractive and more elastic for customers.

“There are three stages, and at the third stage — that is ten years from now — our product will become ‘work as a service’.”

Launching the Work Execution System

Laiye’s claims were made at an event held in London marking the launch of its new Work Execution System (WES), an automation system which provides partners with digital workers powered by machine learning (ML) and artificial intelligence (AI).

WES digital workers learn rules, taught by human employees in no-code interactions, which they can then contextually apply to tasks of varying complexity, from menial form processing to more sophisticated handling of forms.

Laiye advertises that WES can be integrated with systems such as UiPath, Slack, Teams, and SalesForce, and Shnider claimed that it “doesn’t care” if its customers choose to go with Laiye robotic process automation (RPA) or a competitor’s.

At the same event, the company highlighted the importance of harnessing the metadata generated by automated systems, in order for organisations to adequately address the ‘work execution gap’.

Trillions of pieces of data, from integers to complex information such as documents and videos, are caught up in automated systems, capable of producing vast amounts of metadata for big data analytics.

With an aim of getting a better view of this data, the firm announced that upon release, users will be given the choice of a free version or paid enterprise version.

In the former, users will be able to leverage the features of this system at no cost, in exchange for sharing their metadata for public use, giving companies insight into non-identifiable industry and use-case benchmarks and feeding this data to better train ML algorithms.

For example, a company could compare their invoicing automation stats to the industry benchmarks, use this information to determine whether more changes need to be made to their system, and in the process teach their system gaps that should be eliminated in future.

Paid enterprise users will generate only private metadata, for internal benchmarking purposes — IT Pro was given the example of the figures from different departments being compared against one another.

Laiye claims that companies that have adopted its automated systems thus far have seen a 60% improvement in productivity, and is willing to offer a full refund if it cannot integrate its WES by a company's deadline.

Another benefit of accurate metadata is explored in an upcoming white paper by Laiye, which proposes a carbon calculator for its customers.

Through the WES, this will determine the sustainability of companies in comparison to the overall market, and offer partners discounts in the form of credit against future purchases in exchange for meeting sustainability goals, which Gartner highlighted as the key strategic technology trend for 2023.

The beta version of Laiye’s WES will be launched on 30 November, with general release slated for 20 January 2023, and any company that buys a current Laiye product before 16 December will be given free access to WEP in 2023.

Security vendors' pursuits of an autonomous security operations centre (SOC) are fruitless, according to claims by a leading industry analyst.

According to Allie Mellen, senior analyst at Forrester, security vendors are all searching to build an all-in-one product that could entirely automate the many functions of a security team but the idea would be almost impossible to implement due to technical and logistical limitations.

Mellen argued that although automation has been instrumental in areas such as automating back office functions, and is increasingly powerful for security applications, the complexity with which threat actors operate means a machine could never fully protect against their various techniques.

Threat actors are also highly unpredictable in their methods and anticipating the next move in any engagement would require a well-trained human mind, she said.

“In contrast, security tools must follow a set of rules - they are built with an intention in mind, whether it’s to detect threats on the endpoint or to find anomalies in otherwise consistent data,” said Mellen in a blog post.

Security oversight still demands escalation to human workers and always will, Mellen added, especially with complex environments in which automated systems could “go off the rails".

“These constraints force a limitation on technology that cannot be overcome without the aid of humans. If an organisation uses endpoint detection and response, an attacker will find a way to bypass it or not target an endpoint. If an organisation collects all logs from every single asset into a security information and event management system, an attacker will find a vulnerable employee to leverage for covert access.”

Theoretical upsides to fully automated SOCs and security orchestration, automation, and response (SOAR) solutions include the reduced impact of cyber skills shortages on organisations and fewer data protection weak points among employees, but human decision-making is still required for the best protection.

The retained need for human input is the key differentiator between SOAR and fully-autonomous solutions and although companies such as Google Cloud and MITRE have taken steps to provide customers with pre-built threat-hunting queries in their environments, no one is selling an out-of-the-box, fully automated cure-all to security fears.

Tech giants including Microsoft continue to offer business security solutions that blend automation and expert insight. Providers that offer security as a service might yet fulfil the same role as automated security for smaller businesses, as this still has the end result of freeing employees from the burden of threat management.

Firms such as QuSecure even offer ‘quantum security as a service.’ In this sense, it could be argued that there is less of a need for a fully-automated SOC, with hybrid solutions working well.

A number of meaningful advances have been made in recent years using artificial intelligence (AI) and machine learning (ML) in security applications.

In 2022, AI cyber security software has continued to innovate and has seen the uptake of tools capable of identifying suspicious web traffic, such as NDR products.

Microsoft and Darktrace partnered on AI cloud security in 2021, while it was recently revealed that MI5 and the Alan Turing Institute have collaborated on AI since 2017 with the specific focus of using the technology for defence and security.

Additionally, a great deal of research and development is being done into the potential for deep learning solutions to threat actors, which carry the potential to predict ransomware strategies, or even combat AI malware developed by leading-edge threat actors.

Adopting an automated performance management (APM) strategy is the only way organisations can break through application challenges & fully realise the opportunity presented by continuous integration and continuous delivery (CI/CD)-powered environments.

As CI/CD increasingly becomes a key goal for enterprises, this whitepaper shares that when automation is introduced at every layer of performance management within an organisation, it can reduce costs and improve business outcomes by enabling the effective reallocation of staff time.

Download now to learn how to best implement automated APM as well as how to maximise CI/CD agility.

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APM and observability tools have become powerful analytics platforms that ingest multiple telemetry feeds, providing critical insight into application performance. The significant differences amongst the vendors mean infrastructure and operations leaders need to consider strategic monitoring choices.

This Gartner report looks at the capabilities of APM and observability tools, including security functionality, application monitoring on mobile, support for VDIs, and integrations with service management tools, amongst others.

Read now to gain insights into the current vendor landscape and how IBM Instana has been recognised as a leader in this field.

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Automation is increasingly becoming part of organisational strategy to modernise and improve workflows. Robotic Process Automation (RPA) can enable businesses to overcome business challenges by tackling repetitive tasks and accessing unstructured data, meaning compliance requirements are also met more effectively.

This report from Forrester Consulting looks at the ROI of adopting RPA, and how this investment has increased efficiencies, allowing staff to be deployed elsewhere, as well as improved compliance reporting and a reduction in fraud.

Download now to learn why RPA initiatives are just as vital as business-focused ones in your organisations' digital transformation strategy.

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A senior industry analyst has said modern businesses need to embrace automation to capitalise on the next big business growth opportunity in the coming years.

Businesses are facing the next epoch of growth opportunities and are currently at the bottom of the epoch’s S-curve, said Leslie Joseph, principal analyst at Forrester. The way to capitalise on the accelerated growth opportunities is to embrace automation before industry peers, he added.

Speaking at UiPath’s Forward 5 conference, Joseph likened modern businesses to penguins - they are all currently so similar in terms of digital maturity and the only way to stand out over the next few years is to embrace automation.

Companies are currently spending large amounts on digital technology, but improvements are stagnating, largely because every company is spending the same money on the same once-disruptive tools.

This means growth opportunities aren’t as plentiful as they once were, now that more companies are progressing through digital transformation journeys, representing the top of the previous epoch’s S-curve.

Deploying automation platforms and related technologies, like robotic process automation (RPA), will allow businesses to achieve what Forrester calls the ‘Future Fit’ characteristics required to leapfrog competitors and join the next S-curve of growth opportunities before competitors. The three Future Fit characteristics are adaptiveness, creativity, and resiliency.

Businesses must be capable of reconfiguring core business concepts flexibly for success, according to Joseph, as well as be able to engage with the emotion of every customer, and do so through their employees, and build an ‘enterprise muscle’ to be able to identify and manage risks on an ongoing basis.

According to Forrester’s research, Future Fit companies grow 2.7 times faster than their industry peers, but only a minority of modern businesses meet these criteria.

“Automation is the new fabric for digital business,” said Joseph - meaning that automation is the tool that businesses should be harnessing to meet all three of the Future Fit characteristics and set up for a path to accelerated growth.

“We're not even talking about the goalpost shifting a little bit here, we are talking about an entirely new stratification of value between the haves and the have nots,” he added. “It's a whole new world. It's not enough anymore to just be digitally mature, they have to be these three things.”

A business’ automation journey will only succeed when a number of key requirements are met, according to Joseph.

The company’s chief executives must be involved when developing automation goals and outcomes. Additionally, the value of each automation needs to be captured from a holistic perspective, like an automation platform allows a business to do, ensuring the function of each automation is aligned with the goals set in conjunction with the CEO.

“Automation is a transformational initiative across your organisation, it must be supported by your CEO,” he said. “Your CFO must set and align automation-centric outcomes that must be distributed across your business functions, so that everybody in the company is invested and is tasked with creating an atmosphere of resilience to automation.”

Transforming employees’ attitudes towards automation will also be important, and specifically reassuring staff that their jobs will remain safe, since they are most at risk from the uptake of automation.

“You need to engender trust, you need to create pathways for skills for your employees so that they can continuously see value for themselves on the automation programme,” said Joseph.

Companies also need to consider hiring their first chief automation officer to maximise stewardship over what would be a programme that transforms the company.

The second full day of Oracle NetSuite’s annual SuiteWorld conference focused heavily on the solutions the company sees as unique to its brand, and continued the emphasis on automation established at the conference thus far.

If the first keynote riffed off the conference’s slogan to embody the company mission — ‘Full Suite Ahead’, referring to customer adoption of the full suite capabilities — the second relied heavily on an in-company term, ‘Suiteness’. In short, this was defined as NetSuite’s USP, the quality of life features that customers can only enjoy as a result of its cross-solution integration.

The term was touched upon throughout the various announcements, including that customers will soon be able to enjoy integration between their NetSuite accounts and other business cornerstones such as Microsoft Office and Google Sheets. the regulatory focus of its global expansion.

In one demonstration of what the company sees as its unique offering, Gary Wiessinger, SVP product management, NetSuite, showed NetSuite’s solution for the task of reviewing 70 separate invoices. Using machine learning (ML) rules and the review history that the system has learned from previous user actions, NetSuite filters the list to only include those that require manual review. In-line, through context options, the user is able to assign a review to a relevant employee.

The system also leverages artificial intelligence (AI) to suggest an email template for a customer that it has identified as being slow to pay its invoice, shifting the tone of the payment request in the proposed email to speed the process up. The same automated system was later shown detecting delayed order shipments, and producing a mass-email to all affected customers.

“So, Suiteness intelligence and automation enables you to be more proactive and better serve your customers,” noted Wiessinger.

IT Pro spoke to James Chisham, VP international product at Oracle NetSuite, for a deeper definition ‘Suiteness’.

“We do lots of things, we're a broad ERP suite,” said Chisham.

“But what we want our customers to understand is the value of it being in one place. So how do those parts work in conjunction with each other to help you run your business? I think that's the thing.”

Beyond expanding end-to-end services for its existing customers, NetSuite has outlined a commitment to growing services for new customers, and improving the initial setup experience through pre-built automation presets and by promoting no code development.

“We're leveraging intelligence automation and Suiteness to make the suite more proactive, finding problems before you do,” stated Wiessinger.

“We're also extending our concept of end-to-end ease even further, to include ease of activation. Setting up the product shouldn't be a big monolithic effort you need to do entirely before you start using the product. We’re creating the concept of progressive setup.”

“So you’ll only need to do minimal setup before starting to use the product, and then you can gradually iterate the setup as you use it. And inline sets of assistance will allow you to configure the product right in context, as you work.”

In part to increase its customer base, and also in an attempt to better serve its current customer, NetSuite is looking to expand its supported regions. Human resources (HR) solution SuitePeople is now available in the UK and Ireland, and is coming soon to Japan, and regionalisation of tax services and contextual insights will soon be available in Brazil.

The latter demonstrates the lengths that the company is going to on its mission to automate the back office: though users may never see the individual calculations, Wiessinger claimed that over 20,000 of them can be involved in processes such as tabulating the correct regional tax codes.

“I think one of the biggest challenges for customers that will affect us as well, is compliance regulatory changes. That’s been happening at a rate that I've not seen for many years, and they’re the sort of things that, obviously, keep customers awake at night,” asserted Chisham.

“If we take Brazil as an example, it's one of the most complex jurisdictions on the planet and it changes very quickly. So the capability that we've announced today is going to take a lot of pain away for our customers.”

UK businesses, eyeing up potential IR35 changes and the government’s proposed Digital Reform Bill, could lose out on key NetSuite services such as proper tax automation if the company failed to quickly adapt to legislative changes.

Elham Ghassemzadeh, VP product management SuiteCloud Platform, spoke more on the technical aspects of NetSuite’s expansion. In particular, she asserted that the data centre and cloud infrastructure available to the company as a subsidiary of Oracle is instrumental to its end-to-end suite services.

“We have access to the wealth of Oracle technologies here at Oracle Cloud Infrastructure and OCI is at the heart of it all. Not only does OCI give us the essential functionality we need to run our service, it also enables us to take intelligence to the next level.

“We can now mine very difficult to see and powerful insights, and optimise the NetSuite application in new ways. And we are bringing all of that intelligence to you. We are entering new geographies faster than ever before with OCI. In fact, for the very first time, we are running in Japan.

“Later this year, we plan to go to the Netherlands and Wales, realigning our European and UK presence as Brexit redefines and changes data residency requirements. Next year, we plan to be in Canada. In fact, in the last 12 months, we've added 11 new data centres, in five new cities all around the world and the majority of our customers run on OCI now.”

Ghassemzadeh also praised SuiteScript, NetSuite’s Javascript platform, and its role in powering APIs that customers increasingly rely on to improve their efficiency.

“Data is everything. Our integration APIs manage a massive amount of data movements across our ecosystem and our latest APIs are used by thousands of customers. In fact, we are seeing a 133% usage increase of the rest APIs across our customer base year over year.”

OutSystems has announced a new partnership with enterprise automation firm UiPath that the pair say will help customers improve productivity and bridge talent gaps through improved automation.

The collaboration will combine UiPath’s Business Automation Platform with OutSystems’ high-performance low-code to enable customers to automate core business processes and applications.

Solutions and services will also be integrated with a new connector that allows UiPath software robots to be managed from within OutSystems applications, designed to help prevent vendor lock-in and maximise ROI.

Rui Pereira, VP of Global Channel at OutSystems, said that digital transformation pressures are creating a mandate for organisations to make “smarter, more efficient workplaces and effortless experienced for customers”.

“Our high-performance low-code development approach, combined with the power of UiPath automation, provides our joint customers with a proven roadmap to higher-order efficiency gains,” he said.

“The result of this integration enables IT leaders to bridge the talent gaps of their teams in order to accelerate innovation and generate massive value for their organisations.”

OutSystems’ high performance low-code platform provides tech developers the tools to build and deploy their own business-critical applications at pace.

With its new partnership with UiPath, the firm says customers can now also apply automated processes end-to-end across departments and systems of record, as well as leverage easy-to-use design interfaces and native integration that reduce development times and help rapidly deliver composite apps.

Users can also incorporate AI and Machine Learning to automate document understanding, image analysis, language analysis, and comprehension, while enterprise-grade RPA will automate manual application testing.

“More than half of large enterprises today have four or more simultaneous automation initiatives - and this number is only expected to rise over the coming years,” explained Dhruv Asher, UiPath Senior Vice President of Alliances and Business Development.

“Our partnership with OutSystems will be integral to serving this growing market demand and enabling our joint customers to deploy complex automation at scale.”

Robotic process automation (RPA) firm UiPath has announced a quartet of new features that will soon be coming to its Business Automation Platform.

UiPath Studio Web is the first of the new platform updates that builds upon the existing UiPath Studio and StudioX products.

It’s a browser-based automation development tool that aims to simplify the creation of public-facing apps and processes for various use cases.

UiPath said the tool brings new capabilities such as a connection builder to link APIs ​​to both in-house applications and bespoke industry solutions, while offering the opportunity to develop automations on a cross-platform basis.

Studio Web was used by Microsoft to organise a raffle in which conference delegates participated. It was able to develop a web app to log each entrant and randomly pick winners, sending them bespoke emails confirming their prize automatically.

The company has also bundled three individual improvements under a moniker of ‘continuous discovery’, as part of its first day of its Forward 5 conference.

UiPath said customers are now able to investigate the as-is state of processes and take actions based on the result, while also being able to continuously monitor other processes to identify areas that can be tweaked for better profitability, for example.

‘Continuous discovery’ brings improvements to the UiPath Automation Hub through new return on investment (ROI) capabilities, offering comparisons between estimated benefits and actual outcomes.

New analytics features are coming to Process Mining - a tool used to understand how humans and software robots interoperate on different task - for better insights, as well as general performance improvements.

UiPath’s Task Mining product, which scans staff workflows and suggests the most efficient automations, will also receive a new assisted mode. This will allow those involved in developing the automations to add in their own insights in addition to what the tool’s AI learns.

The third big feature coming to the platform is Communication Mining, a feature born out of the standalone product developed by Re:infer, a natural language processing company that UiPath acquired in August.

Communication Mining will allow businesses to analyse emails, chat logs, and other communication channels to open up new automation opportunities from within the UiPath Business Automation Platform.

The technology can be used in collateral management scenarios, for example, where teams send a large volume of margin call emails to trading counterparties. These emails are usually met with one of three responses: agree, partially agree, and dispute.

Assuming the centralised margin call email inbox has communication mining enabled, automations can be configured to take the responses, filter them by the response type, and send them to the necessary internal teams without any human intervention.

Speaking at Wednesday’s Forward 5 conference keynote, Rushabh Shah, programme director of intelligent automation at Deutsche Bank, told delegates that the financial institution has been using the technology across the business, leading to savings of “weeks and months of work”.

“When you can understand every message flowing through your business, you can understand all your customers' needs, all of your business' problems, and the bottlenecks you have in your processes,” said Ed Challis founder and CEO at RE:infer. “And what's more important is you can uncover all of the great automation opportunities.”

New enterprise-focused features in UiPath Automation Cloud and Automation Suite complete the new platform features, with the former receiving new security capabilities such as IP range restriction.

Automation Suite sees process mining embeded within the platform for the first time after previously only being available through an on-prem installation model.

Serverless robots are also soon to become part of Automation Suite and act similarly to those already available in Automation Cloud, offering “an elastic way to way to scale up automations automatedly,” UiPath told IT Pro.

“They are different in that they will only scale up as high as the customer has infrastructure for them.”

All the newly announced upgrades to UiPath’s Business Automation Platform will become generally available to all customers on 31 October 2022.

Oracle NetSuite hopes to go further than ever before in providing its customers with a fully end-to-end solution, as it signals that automation and cross-service integration are integral to the company’s vision.

This was stated loud and clear by Evan Goldberg, founder and executive vice president, Oracle NetSuite in the first of two keynote speeches made at the company’s SuiteWorld conference in Las Vegas. Making a range of service announcements centred around fixing problems faced by businesses, from vendor payments and shift efficiency to retail and supply chain solutions, the overriding message was nevertheless one of unity across the company’s full spectrum of services.

From acquiring customers to delivering products seamlessly, NetSuite is reaffirming its role as an end-to-end ecosystem for businesses rather than a tool to be used for specific tasks. Goldberg used the example of a fictional fitness company, WYRA, to illustrate just how wide a role NetSuite sees itself as having in assisting each of its customers. In the story, NetSuite comes to the company’s help just as it clinches its biggest ever contract.

“They needed to continue to acquire and grow their customer base. They needed to create and deliver fantastic products and services, and to do this they needed to hire and empower a next generation of employees. Then finally, they had to do all of this while optimising their cash and their profits.

“They went to NetSuite Increase their efficiency, automate complex processes, break down the silos, and it's not just the functionality in all these different areas and all these different value streams, but how it all works together.”

Goldberg listed a range of services that NetSuite provides, and how each would improve WYRA’s platform, but in running through them in order of adoption made clear that from warehouse to customer, all work best in tandem.

This analogy, combined with the slogan of the conference — ‘Full Suite Ahead’ — could best summarise NetSuite’s vision for its role in business growth. While any number of the solutions announced at the conference could benefit businesses on their own, from AP Automation to enhanced Workforce Management, NetSuite contends that the more of its suite a business buys into, the greater the gains it will experience as a result.

“We believe that as customers adopt more and more of the suite, they get exponential value. Everything ties together,” noted Goldberg.

It could be said that small businesses stand to gain more from NetSuite's end-to-end overhaul, as it reduces their need to invest in additional services or operate in-house. Responding to a question from IT Pro at the press conference, Goldberg clarified that the majority of customers seek out NetSuite’s services just as they are about to embark upon rapid digital transformation, or looking to scale into a larger market.

“We’re especially attractive to companies that outgrow their initial accounting system, when they decide they need a more professional finance operation.

“So definitely our customer base is biased towards people that are growing and they see it as an opportunity to set themselves up for long-term success. And you can talk about a company in the software industry, many of them are thinking about potentially IPOing and we have an incredible track record there in the majority of companies' tech ideas.”

Indeed, NetSuite is perhaps best known as a provider of accounting solutions, and it continues to provide innovative systems for managing company finances to its many customers. However, with its ever-growing suite, and newly-announced automated banking features, NetSuite could be seen as going up against competitors within the managed banking and transfer sector such as QuickBooks. Despite the potential threat posed by expansion into such markets, Goldberg stated that he is “not worried about them.”

“Because of the vast capabilities that we have, the entire suite, how we can scale, and things like CDQ. That's not something that you're generally going to see with smaller products.

“And at the sophistication that we're going to do and also, much of the work that we've done for vertical solutions and industry solutions, product companies or service companies and nonprofits, we’ve made enormous investments and it’s accelerating massively as part of Oracle.

“So I'm not worried about being a flank, but I am concerned that our customers feel like when they go to NetSuite, they're continuing to get all the benefits that they had before.”

Indeed, NetSuite’s customer base has grown by 5,000 in the past year, and the firm’s ethos of providing for the widest range of customer needs possible, regardless of whether it is competitive or fully innovative in the markets into which it edges as a result.

Looking at the company’s philosophy in light of tech skills gaps and economic issues both regional and global such as the cost of living crisis, NetSuite also appears to be telling businesses that scaling a company does not have to involve increasing head counts. Through the full embrace of its services, NetSuite argues that customers can look forward to greater insights and an increasingly automated experience, and hopes that customers will enjoy growth as a result.

“Everything we showed today was about eliminating processes, automating things, so that you don't have to necessarily grow your staff,” Goldberg later stated at a roundtable discussion.

If NetSuite’s suite-wide automation can facilitate growth in lieu of extra hires, it could push the company into a particularly powerful position in the current market. Its parent organisation Oracle reportedly made cuts to its workforce over the summer, eyeing up a potential $1 billion in savings in exchange for thousands of roles, and other tech giants such as Microsoft are easing up on hiring for the immediate future. With some businesses choosing to invest and grow their way through economic headwinds, NetSuite might become even more widely used to save companies money on systems and better identify what needs cutting, or conversely see its customer base dwindle as firms batten down the hatches rather than aim to grow.

Oracle Netsuite has announced NetSuite AP Automation, a banking solution designed to make it easier for businesses to process bills and pay vendors.

The new solution, launched at the company's annual SuiteWorld conference, provides firms with a full cloud enterprise resource planning (ERP) system that automatically captures and processes vendor bills.

Using AI (artificial intelligence) and ML (machine learning) object detection, the system is able to capture bills in a faster and more accurate manner than manual entry, and from sources including emails. Captured bills are converted into digital text.

NetSuite AP Automation also automatically creates bill records, with accurate filled fields for vendor details pulled in the capture process, and matches bills to ensure payment details are accurate. Bill matching is fully integrated with SuiteApprovals for a seamless oversight, review and approval process, with bills routed to relevant employees.

Through the use of optical character recognition, the NetSuite AP Automation is also able to accurately capture cheque payments, an important feature for the 81% of US businesses that still use this as a B2B payment method.

Many companies are already finding that automation is a powerful tool for increasing both efficiency and employee productivity, with back office automation freeing up workers to tackle more complex duties. In a landscape increasingly led by digital transformation, Oracle NetSuite is attempting to target those companies that lack the resources to build whole systems from scratch, and need easily deployable, pre-packaged solutions.

On transactions, Oracle NetSuite is continuing with its HSBC partnership, working with the bank to facilitate automated ACH, cheque or virtual credit card payments through NetSuite AP Automation. Customers can use their own current account to fund payments or the HSBC virtual credit card, which provides security for payments by generating single-use card numbers. The SuiteBanking Center will act as a dashboard for HSBC online checking and credit card accounts, and allows users control over transactions and payment statuses.

Greater integration between HSBC and the automated system also provides benefits when it comes to payment reconciliation, with NetSuite AP Automation’s “intelligent rules engine” used to flag irregularities for review, and automatically creating bank fee entries. Users are encouraged to set their own parameters during setup, for example allowing a degree of discrepancy between payment totals.

HSBC hopes that the efficiency of the new system would in and of itself drive businesses to adopt its virtual credit card system. Other benefits include the increased security of its single-use numbers, and the decreased time it takes for the bank to verify payments through the method in comparison to mediums such as physical cheque.

In contrast to simple filtering scripts, which can automatically action corrections to common mistakes such as typos, Automation AP's ML elements learn what to flag and what to change over time. For example, if a typo is flagged as appearing in the 'company name' field of a bill, a user with appropriate authority will be prompted to select which company the bill actually references. Future instances of this typo will result in the system automatically sorting through the problem on its own.

Similarly, the system will learn from a company’s finances in order to prompt alerts for any anomalous payments, as well as to anticipate regular payments without the need for developers to manually assign each one.

As part of future updates, Oracle NetSuite is working on a framework to allow companies better control over the rules that AP Automation learns. For example, under the current system it is possible that the system might take on a one-off payment as a ‘rule’ for future payments, and while this can be manually rejected by the firm, Oracle NetSuite has indicated that future releases will give more transparency over AP Automation’s decision-making process.

“Accounts payable plays an important role in helping organisations manage cash flow, control costs and maintain strong relationships with vendors, but all too often the process is slow, tedious, and error-prone,” said Evan Goldberg, founder and EVP, Oracle NetSuite.

“By simplifying and automating the entire bill payment process – from data capture to payment and reconciliation – NetSuite AP Automation eliminates these challenges. This helps businesses streamline and improve a key operation, empowering AP teams to operate more efficiently and ultimately reduce costs.”

NetSuite AP Automation is available now in the US, and the first 1,000 companies to purchase it will receive a 50% subscription discount, free implementation and bill scanning at no charge.

The NHS' automation efforts, used to clear the COVID-19-related patient backlog, are being hampered in part by sub-optimal 'depth of understanding’, one NHS Trust head of emerging technology has said.

Each Trust is saving the hours of between one and ten full-time equivalent (FTE) staff, on average, each year with robotic process automation (RPA), according to Tremaine Richard-Noel, head of emerging technology at Northampton General Hospital NHS Trust. However, more staff training is needed to build robust RPA solutions in each organisation.

The NHS’ RPA tools are deployed across every single one of its sub-organisations in some capacity and are currently seen as “one of the biggest solutions” it has to tackle the six-million-patient backlog.

"If you consider the fact that the NHS has got 1.7 million staff, at the minute - this might sound odd - there's quite a lot of impact but, on the grand scheme of things, there's a lot more to do," said Richard-Noel to IT Pro at UiPath’s Forward 5 conference.

There are numerous challenges facing the UK’s healthcare service and deploying RPA across each NHS organisation, of which each is entirely different, is “not very easy”, he added.

The primary difficulty in deploying the tools is educating the IT experts in each Trust, since there is no centralised list of systems and RPA has to be deployed in each organisation individually.

“It's not like you deploy it once, you have to deploy in every place and there isn't a centralised list of systems in the NHS, so there are challenges in educating quickly,” he said.

There is no shortage of experts within the NHS who are willing to train to use and deploy RPA in each organisation - “they’re really keen,” said Richard-Noel. Around 50 individuals are trained each month through workshops and other upskilling programmes.

The upskilling programmes currently in place aim to improve the existing FTE figures and increase each Trust’s expertise to a point where they can build their own software robots and maintain the automations - although completing nationwide baseline training is a “huge undertaking”.

Cyber security considerations are also slowing the rate of robot development within the NHS, albeit not with the same significance as the lack of training across each Trust.

Some of the software robots being developed by the NHS are built for basic, non-sensitive data entry, and these can be deployed relatively quickly.

Other robot builds require the safe management of patient data and some projects rely on overseas developers, raising the need for NHS organisations to gain a greater understanding of these new risks.

The only risk when managing the safe transfer of patient data, for example, with software robots is if a bot was built badly from the outset, said Richard-Noel. However, the high degree of governance within an organisation like the NHS prevents unsecured bots from ever being deployed, he added.

How is RPA being used across the NHS already?

The healthcare industry is one of the areas in which use cases for RPA are often touted. For example, previous research has shown that clinicians in the US are spending around 43% of their jobs doing data entry and not face-to-face with patients.

Richard-Noel said there is an endless list of ways RPA is being used in the NHS but one of the most notable is with automated appointment scheduling.

He called the specific initiative ‘automation-initiated follow-up’ which is used by some NHS Trusts to deploy RPA software in a way that reads blood tests, for example, and automatically book a follow-up appointment if the result reveals a cause for concern.

Before the use of RPA, NHS IT systems would book a follow-up appointment by default, even if the results were unproblematic. It’s one way in which the NHS is using RPA to gradually mitigate the patient backlog.

Some NHS Trusts are also using RPA to process the significant number of referrals for people being transferred from primary to secondary care - around 20 million a year, Richard-Noel said.

The processing of these referrals can be done autonomously using RPA, he said, moving away from the days of needing them to be printed off.

The NHS’ use of RPA has accelerated in the past five years thanks to it being part of a national directive from the healthcare service to each of its subsidiaries, but “there is evidence of it being used for about ten years” in total, said Richard-Noel.

The NHS has also been funding dedicated centres of excellence (CoE) for specific technologies.

“A centre of excellence develops common solutions, promotes best practice, and acquires new skills that are then spread throughout the enterprise to increase the likelihood of adopting new ways of working to realise value and allow teams to become self-sufficient,” read the NHS’ cloud CoE website.

Modern enterprises need hyper-automation to drive exceptional customer and employee experiences, let alone outperform the competition.

In today’s fast-moving and customer-driven world, hyper-automation empowers organisations to automate complex business processes and thrive in this digital-first economy. It’s no longer enough to simply automate tasks. Now you must automate entire business processes.

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Enterprise automation software provider UiPath has announced a revamp of its global sales leadership team, with former SAP executive Mark Gibbs taking the role of senior vice president and managing director of EMEA.

The reshuffle also sees UiPath veteran Ryan Mac Ban promoted to senior vice president of sales for the Americas.

The appointments form part of UiPath’s plan to increase its market penetration across the EMEA region, as well as build on its position in the Americas, UiPath said in an announcement.

Gibbs joins the business from SAP, where he held several international roles and most recently served as president of SAP Greater China, covering Mainland China, Hong Kong, Macau and Taiwan.

Previously chief operating officer of SAP Asia Pacific Japan, Gibbs helped revitalise SAP’s presence in the market, registering double-digit revenue growth and building key relationships to further the company’s footprint.

“Mark’s decision to join UiPath is further evidence of our ability to attract world-class talent as we drive toward our objective of increasing market penetration in the region,” commented Chris Weber, UiPath chief business officer.

“UiPath has the industry’s most compelling vision for customers and I’m excited about the expertise Mark brings to enhance our operations in EMEA.”

In the Americas, new sales chief Ryan Mac Ban steps up to the role having previously served as UiPath’s senior vice president for worldwide growth sales, where he oversaw significant growth year-over-year.

Before his tenure at UiPath, Mac Ban held several sales leadership roles at VMware, most recently as Senior Vice President of Worldwide Sales for Networking, Security, and Automation. Prior to that, he served in sales leadership roles at networking giant Cisco.

“Ryan has an impressive history of scaling large enterprise software companies, and his sales approach aligns perfectly with our values,” Weber added in UiPath’s announcement.

“As we make our vision of the fully automated enterprise a reality, scaling customers successfully is our number one goal. Ryan’s experience and passion for customers will be a great combination toward extending our leadership position throughout the Americas.”

98% of organisations have skill gaps within their IT departments, and most senior leaders agree that hiring talented IT workers has never been harder, according to new research.

The IT Leaders Pulse Report 2022, which surveyed IT leaders from around the world, has revealed the extent of the talent gap problem in hiring, driven by the so-called ‘great resignation’ of 2020-1. 73% of respondents claimed that hiring within the sector is facing record difficulties, with the worst impacted areas including IT and solutions architecture and cloud and infrastructure management.

To fill vacant roles, and craft more effective teams, companies are increasingly looking to widen hiring search parameters. 80% of the surveyed leaders stated that they are seeking developer candidates from non-traditional backgrounds, as well as investing in reskilling.

MuleSoft, a subsidiary of Salesforce, produced the report from interviews with 1,000 IT leaders between June and July 2022, across nine countries.

As company strategies change, and digital transformation becomes a more widely accepted duty, firms are also focusing more on people over technologies and products. 86% of senior IT leaders in the survey indicated that the experience that a company provides to customers and employees alike is of equal importance to the products and services that it offers.

Beyond the problems presented by the skill gap, the report also highlights the widespread problem of friction between IT and business departments. The vast majority (98%) of IT leaders indicated that the relationship and working process between their department and business teams within the same organisation could be improved.

The creation of fusion teams, composed of employees from different departments working together to improve the efficiency of company processes, appears to be on the rise. 69% of firms indicate that they have either formed or are currently forming, fusion teams while 22% identify the task as a goal to achieve in the next 12 months. The downsizing and combining of teams is in part driven by internal strategy, but also external factors such as the incoming cost of living crisis, which analysts say will necessitate optimisation in IT teams.

Nearly two thirds of leaders say that fusion teams have helped with meeting objectives, increased innovation and boosted the satisfaction of employees and customers.

However, 62% of UK respondents stated that they are exploring automation to address the skills gap. This highlights the growing degree to which, faced with a talent drain, firms are turning to technologies such as artificial intelligence (AI) and algorithms to improve the customer experience. Despite the potential benefits of this approach, a majority (81%) of respondents stated that too much focus on leading-edge technologies caused complexity issues.

“Shifting economic headwinds are making technology even more fundamental to success across every part of the business, including sales, service, marketing, commerce, and IT,” said Matt McLarty, global field CTO, MuleSoft.

“As IT leaders struggle to fill roles to support this additional demand, the traditional playbook is in question. Today's IT leaders must look instead to broader, company-wide process improvements, through automation, that foster innovation, enhance user experiences, and drive efficient growth."

Connectivity and automation specialist Boomi has announced the appointment of former Deloitte CIO Larry Quinlan as an independent, non-executive member of its Board of Directors, amid a shakeup of its partner programme.

As the former Global Chief Information Officer for Deloitte, Quinlan was responsible for the $45 billion professional service giant’s technology strategy and operations, overseeing more than 10,000 IT professionals across 175 countries.

Quinlan also sits on the board of cloud digital workflow firm ServiceNow, real estate service provider Jones Lang LaSalle, as well as UBS America Holding, where he chairs the Technology and Cyber Forum of the board.

Boomi said Quinlan’s expertise will help the business navigate through its “next phase as a company”.

“Boomi’s continued leadership, coupled with its award-winning platform and culture, make this company a force to be reckoned with,” Quinlan commented. “I’m honoured to serve the Boomi team during this exciting time.”

The appointment follows a revamp of Boomi’s partner programme, which has been expanded to include new opportunities for its partners to create plug-and-play ‘Accelerators’ for customers, as well as simplified training resources.

Partners can now create their own accelerators for customers to set up in their Boomi accounts to address specific use cases, providing additional revenue opportunities and speeding up customers’ time to value.

Boomi says these will provide implementation expertise across industry vertical use cases such as manufacturing, life sciences, financial services, retail, transportation, and higher education.

The addition follows a string of investments in the company’s partner programme over the last year, which included an expansion of its Partner Resource Center, as well as the launch of pre-built solution library Boomi Discover.

“These enhancements to our programme will help us expand our relationships with current partners, and in turn, provide stronger service to our customers, many of whom want specialised industry expertise,” said Ed Macosky, Chief Innovation Officer at Boomi.

“These updates lay the groundwork to usher in more partners globally, giving our customers more ways to quickly and easily solve their complex business problems.”

A globally renowned software-as-a-service (SasS) company, Boomi has a growing user community of over 100,000 members and boasts one of the biggest ranges of global systems integrators (GSIs) in the iPaaS space.

The company’s worldwide network of partners includes Accenture, Deloitte, SAP, and Snowflake, as well as cloud service giants AWS, Google, and Microsoft.

Slack has announced an update to its Workflow Builder that adds new tools for automating tasks within channels and improvements to workflow visibility.

Chief among the additions to workflows is the ability to use conditional logic within the Workflow Builder. If-then statements, a stalwart of simple coding, will allow workflow creators to send users down paths depending on the answers they provide, streamlining workflows that can produce different results based on input conditions, such as holiday request forms. Slack expects this to be available in early 2023.

Other new features include tools for automatic channel creation and alerts to the operator of a workflow when it has received a request, as well as the expansion of steps that feed into Slack-integrated apps.

Users will now also be able to easily copy-and-paste workflow links into channels and direct messages. Once sent, the link will expand into a full workflow preview, which can be run directly and pinned in the channel for ease of access.

Workflow Builder is a tool within Slack, that allows users to create and customise a series of automated steps within their business’ Slack channels. For example, a workflow could be set up to send an automatic welcome message the first time a user is added to a channel, and provide useful onboarding links.

Since Slack introduced Workflow Builder in 2019, over 540 million workflows have been launched, and this has grown by more than 230% in just the last year. In a blog post announcing the update, the company stated that 10.5 million users run workflows in Slack each week.

Slack has taken a number of steps in the past few years to improve its productivity functions, and allow business users to do as much of their work as possible within the app, to reach their aim of being a ‘digital HQ’ for companies. This has included the introduction of Slack Connect for external business communication, or the upcoming release of multi-person screen sharing within huddles.

“This is part of our goal to make automation accessible for all users, period,” stated Steve Wood, the senior vice president of product, platform at Slack.

“These updates are happening at a critical time when businesses are watching their bottom line. When every minute counts, it’s important to bring the automation creation process closer to the people who are actually going to use it. That’s the measure of a successful digital HQ and where the magic happens.”

The five largest economies in the Asia Pacific region are more at risk of physical robot-based automation than both Europe and North America.

That's according to a Future of Jobs Forecast from Forrester which suggests that by 2040, 63 million jobs in India, China, South Korea, Australia and Japan could be lost to automation, with industries such as construction and agriculture set to be hit hardest.

Forrester's Future Of Jobs Forecast, which looks at the state of automation from 2020 to 2040, suggests that the green economy will potentially help to offset some job losses as more governments commit to carbon neutrality. This will include more renewable energy, green buildings and smart cities developed by 2040.

However, even with more green roles, the IT industry, particularly in the Asian Pacific area will see 13.7 million jobs lost to automation.

"To prepare for the changes brought on by automation, the five largest economies in APAC will have to radically rethink their workforce strategies," said Michael O'Grady, principal forecast analyst at Forrester. "While each economy faces its own challenges, common focus areas such as hiring more female workers can help offset working population declines. In addition, investing in STEM education, technology workforce training, and protecting the rights of freelance workers will become of utmost importance."

Automated jobs will impact each country differently, according to the report. For instance, Australia will see a similar situation to the US, with 11% of jobs lost to automation by 2040. China, in contrast, will see 7% of jobs lost to automation, though some 3.8 million additional new jobs will be created within the next two decades.

India, which has a relatively young workforce, according to the report, will add 160 million new workers over the next 20 years. However, 69% of these are under threat of automation, making job creation a main priority for the country.

Japan has the opposite problem as it has an ageing workforce, according to the report. Coupled with its low birth rate, the country's workforce is set to decline by almost one-third. Similarly, South Korea's ageing working population and its dependency on the construction and agriculture industries will be highly susceptible to automation. The report suggests that 23% of South Korean jobs will be automated over the next 20 years.

Transportation and delivery giant FedEx and logistics technology firm Berkshire Grey have announced a deeper partnership in an effort to overhaul the former’s supply chain.

The two companies announced in a blog post they've agreed to work together on improving safety and efficiency throughout FedEx’s package handling system, using so-called robotic automation and artificial intelligence (AI).

Berkshire Grey’s Robotic Product Sortation and Identification (RPSi) systems have already been rolled out across eight FedEx facilities within the United States. This sorts small packages for distribution automatically, a small part of the more holistic approach indicated by today’s announcement.

A master system purchase agreement, which would help speed up purchases from Berkshire Grey, is being drafted and both parties hope to execute it before the year is out. The agreement implies that, once formalised, FedEx is serious about overhauling its backend to embrace automation wholescale.

Moreover, Berkshire Grey has allowed FedEx to purchase incrementally-vested public stock, to a maximum of 25 million shares available. This number is subject to FedEx purchasing ordering at least $200 million in Berkshire Grey services and products by December 31 2025.

FedEx has engaged in a series of partnerships to facilitate its digital transformation and promote efficiency within its internal systems. In January, it announced that in a continuation of its dealings with Microsoft, it would be utilising the tech giant’s Dynamics 365 software to improve order logistics using the power of cloud networking.

On its website, Berkshire Grey claims that its package sortation systems can “reduce shipping costs by up to 20% and improve sorter utilization by up to 50%”.

It identifies key areas of streamlining such as sorting parcels by zone to reduce freight costs, auto-identifying barcodes without need for manual handling and picking individual items to be sorted to cut down on labor.

Amazon has long been an outlier in its reliance on automation within its warehouse back-end, and recently announced a new generation of fully-autonomous robots to work in even more areas across its fulfilment centres.

“Berkshire Grey and FedEx are strategically aligned. These new agreements reflect our mutual commitment to innovations in robotic automation that can remove barriers within the supply chain, ease the physical burden on employees and streamline operations,” stated Tom Wagner, CEO of Berkshire Grey.

“We look forward to working together on this new program and to advancing other automation programs with FedEx moving forward.”

Robotic process automation (RPA) software is expected to see successive yearly growth as business demand continues to increase.

The revenue generated by the RPA software market will reach $2.9 billion (£2.3 billion) by the end of 2022, according to leading analyst house Gartner.

This represents a 19.5% increase from 2021 - a figure that exceeds that of the overall software market which sits at around 16%.

In 2021, the market grew 31% over the figures from the year before and growth is expected to continue throughout 2023 at a slightly decelerated rate of 17.5% year-over-year.

RPA software has nothing to do with physical robots and instead refers to the ‘robots’ inside software that help businesses automate back-office functions that have traditionally been highly manual and often laborious.

Tasks that have typically required human workers to do repetitive tasks involving copy-and-paste ways of working, such as database population and data manipulation, are now being automated with RPA software.

The benefit to an organisation is that human workers can be reassigned to larger, more complex tasks that require human attention, but the technology has also raised fears regarding the outright replacement of human employees in certain roles.

“RPA companies are rapidly evolving to provide a wider set of larger automation platforms,” said Varsha Mehta, senior market research specialist at Gartner.

“Organisations will look to increase their spending on RPA software solutions because they still have a lot of repetitive, manual work that through automation could free up employees’ time to focus on more strategic work.”

The market is largely driven by businesses in North America, Western Europe, and Japan, Gartner said, with the three regions accounting for 77% of the global RPA market revenue this year.

North America claims the largest share out of the three, accounting for 48.5% of the global revenue overall, with Western Europe contributing 19% of the global revenue and Japan contributing 10%.

Gartner predicted last year that the vast majority of organisations (72%) will begin working with RPA software within two years and categorised the market as the fastest-growing in the software industry.

It believes that businesses are looking to embark on a journey towards hyperautomation - automating myriad corners of an organisation with a variety of different technologies such as RPA, artificial intelligence, computer vision, low-code platforms, and more.

By 2024, Gartner predicted that organisations will adopt three out of the 20 process-agnostic types of software that enable hyperautomation.

Its global revenue predictions for the software that enables hyperautomation far exceed that of RPA. Gartner said last year that it expects the market to reach $600 billion (£489.5 billion) by the end of 2022.

Electric car major Tesla faces yet another roadblock as Germany’s road traffic agency recalls models Y and 3 after detecting a flaw in the car maker’s automatic emergency call system.

By far, the software glitch affects approximately 59,129 vehicles globally.

The German federal authority for the road, Kraftfahrt-Bundesamt (KBA), has warned that the software flaw causes Tesla’s eCall emergency system to malfunction, preventing automatic contact with first responders during an emergency.

The mass recall was first reported by regional broadcaster Rundfunk Berlin-Brandenburg (RBB) on Saturday. It’s unclear how many of the affected 59,129 vehicles were registered in Germany.

In its second-quarter report, Tesla mentioned it delivered 17.9% fewer electric vehicles than the previous quarter, as China's ‌Covid-19 shutdown affected supply and production.

Additionally, Tesla's new factories in Texas and Berlin are "losing billions of dollars" due to Chinese port issues and a shortage of batteries.

Tesla's progress is supposedly further hampered by the recent eCall software glitch.

HPE has announced that open source leader Red Hat has joined its HPE GreenLake ecosystem, a move it says will help joint customers better run and manage their IT systems.

The pair will work together to combine new service offerings with Red Hat’s open source technologies such as Red Hat OpenShift, Red Hat Enterprise Linux, and Red Hat Ansible Automation Platform, which will be deployed on the GreenLake platform.

Announcing the move at its Discover 2022 event, HPE said the solutions will be engineered and designed to provide complete, open source IT stacks for compute, containers and automation – ultimately addressing the industry need for more agile solutions.

“This extended partnership makes it easy for HPE GreenLake customers to consume and work with Red Hat’s highly regarded open source solutions,” explained Keith White, EVP & GM of HPE GreenLake Cloud Services Commercial Business at HPE.

“This enables our joint customers to focus on accelerating their business transformations, at a lower cost, while solving their most pressing challenges around performance, risk, and speed, without worries about integration, licenses, or product updates.”

HPE GreenLake with Red Hat promises a host of benefits, including more reliable performance across a range of workloads, reduced risk and complexity, as well as lower cost of ownership.

The open source IT stack solutions are designed to allow companies to move and adapt faster to market changes for a faster time to market, while HPE’s comprehensive support covers physical, virtual, and multi-cloud environments.

Stefanie Chiras, senior vice president of Partner Ecosystem Success at Red Hat, said the two companies are “committed to enabling greater customer choice and flexibility” as many businesses look to accelerate their digital transformation.

“Red Hat’s open hybrid cloud portfolio offers a more consistent and scalable foundation for customers to optimise their cloud operations, from the datacenter to the edge,” she said.

“We are pleased to collaborate with HPE to integrate Red Hat technologies with HPE GreenLake platform, further supporting customer choice wherever needed.”

Amazon has announced the deployment of two new robots across its fulfilment centres, which the company says will work alongside human workers to lift, shift and sort packages with improved safety and efficiency.

Adding to the fleet of 520,000 robots already in use at Amazon, the new systems, dubbed Proteus and Cardinal, will be the first designed to shift packages autonomously around workers, with no need for a restricted operating area.

Currently, Kiva and Pegasus robots are used to move large storage pods within a caged inventory area, using 2D barcodes to navigate. Workers call over robots to pick items off the pods, package them, and send them on conveyor belts to be loaded onto worker-operated trolleys Amazon calls GoCarts.

The new robots will assist with the sorting and movement of packages that workers do currently. Proteus will navigate loaded GoCarts alongside humans, while Cardinal will bear the weight of offloading packages from conveyor belts in sorting centres.

Amazon claims that it is not moving to replace workers, simply reducing their involvement in risky tasks.

A demonstration video shows Proteus moving around an unmarked warehouse space, and automatically braking upon detecting a human in its path.

Cardinal, which boasts a large crane arm, will be implemented to not only lift heavy packages from conveyor belts but simultaneously use AI to sort packages as they are loaded. Amazon claims that Cardinal is being tested with lifting capacities of up to 50lbs (22.7kg) and will be introduced in warehouse settings in 2023.

“Our vision is to automate GoCart handling throughout the network, which will help reduce the need for people to manually move heavy objects through our facility and instead let them focus on more rewarding work,” stated Amazon in a press release.

While Amazon has not specified what more rewarding work may entail, employee safety within fulfilment centres has been the subject of scrutiny in recent years. A 2021 study by the labour union coalition the Strategic Organizing Center (SOC) found that Amazon warehouses experienced 5.9 serious injuries per 100 workers in 2020, a rate “nearly 80 percent higher than the serious injury rate for all other employers in the warehousing industry in 2020.”

Addressing some safety concerns, Amazon has also revealed a new “AI-powered” identification system, AR ID, which uses high-speed cameras to identify packages. This means employees no longer must scan products manually and can hold packages safely with both hands.

A new “containerized storage system”, which utilises robot arms to bring containers to employees, has also been demonstrated, with the goal being to reduce the risk of injury through climbing and bending down.