AI-enhanced tools are rapidly being utilized at the cutting edge of modern IT operations. Tasks such as overseeing network complexity at scale and defending against sophisticated cyberattacks are increasingly being entrusted to AIOps platforms and AI-driven security tools, respectively.

As a result, the repeated use of these platforms has granted channel partners faster access to large yields of data.

Nevertheless, as Managed Service Providers (MSPs) strive to scale their AIOps and AI-driven security practices for customers, a hard truth is emerging: more data doesn’t necessarily translate to better outcomes. In fact, AI platforms are only ever as effective and reliable as the data they ingest and analyze. Managing sampled, siloed, and fragmented network telemetry across multi-vendor, multi-tenant environments severely limits the effectiveness of partners' managed services, instead amplifying noise and inflating observability costs. This kind of data makes for a brittle blade, undercutting the AI integration designed to improve operational efficiency and strengthen security.

For channel partners, the priority must shift from data quantity to data quality. The competitive advantage of AIOps is not found in the sheer accumulation of data, but in the ability to finely cut away the noise to achieve high-signal, low-noise telemetry ready to benefit the systems it feeds. Partners who understand this shift are best positioned to help their customers capitalize on AI's true capabilities.

The strain of fragmented telemetry

In the era of static, on-premises infrastructure, tracking data was rather straightforward. Applications changed slowly, and a high volume of server logs generally equated to better control over the digital ecosystem. But modern, cloud-based environments have changed this dynamic. Legacy tools now face a data burden they were never designed to process effectively. Despite this radical shift, many service providers still cling to outdated ingestion habits, attempting to collect everything without a clear filtering strategy.

Rather than creating a unified view of system performance, this approach often results in telemetry being fragmented across multiple disconnected tools, leaving critical insights isolated and difficult to correlate.

This operational stubbornness can prove expensive. Allowing unrefined, chaotic data to flood telemetry pipelines results in bloated tool investments that actively bury critical performance signals. For MSPs, relying on siloed and sampled data feeds is tantamount to operating blindly. When visibility is fractured, minor glitches go unnoticed until they trigger massive infrastructure failures, disrupting the client's cloud environment and undermining their trust in the provider.

Furthermore, disconnected monitoring point solutions create a compounding operational problem: an endless, unmanageable barrage of noise. When every tool fires alerts independently, distinguishing a critical systemic failure from routine background noise becomes extremely challenging.

Without a unified telemetry strategy, IT teams waste valuable time correlating alerts across multiple platforms instead of resolving the underlying issue. This chronic information overload can exhaust frontline technicians, destroying engineering productivity and stalling active threat detection.

The ensuing organizational toll is heavy. Over time, operators become dangerously dependent on a small group of experts for emergency incident response. These seasoned firefighters become the first and last point of call for late-night rescues and system support. This constant state of reactive crisis management accelerates burnout among top technical talent.

More importantly, it creates an operational trap in which a partner’s best minds are permanently sidelined, forced to manually prop up broken telemetry systems instead of driving innovation and service improvement. When teams are trapped in this cycle of reactive firefighting, the efficiency and growth promised by advanced AIOps platforms remain out of reach.

Tempering true ‘AI-ready’ data

Rather than adopting a patchwork of new tools to manage an ever-expanding data burden, the ultimate solution lies in ensuring telemetry is inherently fit for purpose. A channel partner’s true competitive edge rests on their ability and capacity to deliver solutions that can curate high-signal, low-noise data streams that enable immediate, informed action.

Telemetry is only truly "AI-ready” when it meets a specific, measurable standard. It must be comprehensive, accurate, contextually enriched, and available in real time. Meeting this baseline eliminates the critical operational blind spots caused by data sampling, fragmented toolsets, and inconsistent collection methods across client networks.

Maintaining real-time observability is therefore an operational necessity. Without it, customers cannot fully realize the value of investments in network automation and performance optimization. With it, their service assurance improves, threat detection becomes more effective, and operational blind spots are significantly reduced.

Achieving high-fidelity telemetry requires continuous, packet-level visibility. This provides AI-driven systems with the granular and contextual information needed to establish reliable baselines of normal network behavior, identify anomalies, and help IT teams address issues before they affect performance or disrupt operations.

AI-ready data must also be contextually enriched and correlated across domains. Raw telemetry can indicate that an event has occurred, but context explains what happened, where it happened, and why it matters. Application-aware insights transform telemetry into actionable intelligence, enabling IT teams to identify root causes faster and prioritize remediation. By delivering this richer context, channel partners convert raw network data into meaningful operational insight.

When this foundation is in place, its value extends far beyond network performance. AI-ready telemetry becomes the engine behind next-generation security capabilities, creating new opportunities for MSPs to deliver higher-value services and generate more consistent revenue opportunities.

Unsheathing new revenue streams in next-gen threat detection

The need for AI-ready telemetry becomes even more apparent in cybersecurity. As next-generation cyber threats evolve to evade traditional defenses, AI-driven detection platforms demand complete, accurate, and context-rich telemetry. When security models ingest fragmented telemetry, threats slip through unnoticed, leaving organizations unable to identify malicious activity before it disrupts operations.

For channel partners, addressing this challenge creates a significant opportunity. By delivering comprehensive, contextual, and actionable network-derived intelligence, partners can develop higher-value threat detection and response services, helping customers identify and respond to malicious activity earlier.

High-quality telemetry can also reduce false positives, helping MSPs scale their security operations, support more customers, and use their existing resources more efficiently. As clean, high-quality data helps customers demonstrate stronger operational control and support compliance with strict regulations, it also creates another route for partners to provide valuable, recurring services and keep systems audit-ready.

Striking while the iron is hot

The competitive divide across the IT channel won't simply be defined by which partners adopt the most AI into their offerings. The true advantage will lie with those who provide these AI technologies with the precise data quality they need to perform to the best of their abilities.

AI systems and their potential are readily apparent and available to everyone. However, partners that continue delivering fragmented, sampled, and siloed telemetry into their clients’ AI systems will drive up infrastructure costs, increase operational noise, and ultimately fall behind in operational efficiency and security effectiveness. Instead, the competitive advantage will likely belong to MSPs with the cleanest, most contextual, and most actionable telemetry.

By shifting their focus from data quantity to data quality – specifically towards AI-ready data, channel leaders can cut through the operational noise and unlock more of the commercial and operational value promised by AI-driven tools.

Companies are pouring billions into AI initiatives in pursuit of productivity gains. Yet, for many, the payoff isn’t coming soon enough. As a result, layoff announcements attributed to AI investments are coming thick and fast.

Earlier this year, Monday.com became the latest major tech company to announce AI layoffs. The restructuring plan, which will see more than 600 jobs, or 20% of the workforce, culled, has been put down to the need to pivot to “a leaner, more focused operating model” and “AI-driven growth strategy”.

In a memo published on LinkedIn, Monday.com co-founder and co-CEO Eran Zinman stressed that though the company is “seeing significant value from AI internally, this decision was not made to reduce costs or replace people with AI.”

The layoff trend is set to continue in the short-term – at least in the short-term. A survey released by consulting firm Mercer in May found that 99% of 825 C-suite leaders expect they will have to reduce their headcount over the next two years.

However, according to another survey of 600 HR professionals, conducted in February by Careerminds, a third (32.9%) of respondents said their company had lost critical skills as a result of layoffs blamed on AI. More than a quarter (28.1%) indicated that the employees who had been spared weren’t equipped with the knowledge required to fill the skills gap created by the layoffs.

IT leaders are often overlooked

The data shows that there’s a disconnect between the reasons behind layoffs and their intended impact. The problem is that decisions “are being made in the wrong rooms,” argues Sonali Fenner, a managing director at technology consultancy Slalom focused on strategy and innovation.

She says that layoffs are typically a response to board pressure to demonstrate the return on investment (ROI) of AI tools and vendor promises of ROI not materializing quickly enough. This means review processes end up being fragmented and rash decisions are made.

“Finance triggers the review, HR manages the process, operations signs off the business case, and IT is consulted just long enough to answer a feasibility question before the door closes. When the automation underperforms, as it regularly does at the early stage of enterprise AI maturity, nobody is clearly positioned to own the gap between what was promised and what was delivered,” explains Fenner.

The people within a company who actually understand the AI tools being invested in and what they can and can’t automate tend only to be “consulted as an afterthought”.

Technical knowledge can inform layoff decisions

It makes sense, then, that IT leaders should be involved in layoff decision-making – they sit closest to where AI is actually deployed. For example, they are the ones whose roles involve tracking the ROI of AI, and they have visibility into whether AI has actually delivered the productivity gains layoffs are being justified by. As Fenner puts it: “IT leaders know the difference between what an automation deck says and what the system actually does at 2 am on a Tuesday.”

David Fischer, chief revenue officer at Luware, a software firm that builds customer service and compliance tools, echoes this. “IT leaders absolutely need a seat at the table when businesses make workforce decisions linked to AI, but they shouldn’t be making those decisions alone,” he says.

It’s IT leaders’ bread and butter to have a clear read on what AI can automate, where its limitations lie, and where it can support human workers in their roles, Fischer adds. On the other hand, operational and HR leaders are better placed to understand the implications layoffs can have on people and the wider business.

Research released by Cornerstone recently found that when CIOs and chief human resource officers (CHROs) work together on workforce planning, changes happen 13% faster. However, while 94% of 2,000 IT and HR leaders surveyed said that a joint approach was becoming a priority, only 35% admitted that AI-related decisions were being made together.

Be mindful of the conflict of interest

Despite the need to involve IT leaders in layoff decisions, doing so isn’t without its risks, namely a conflict of interest.

“IT leaders responsible for delivering an AI programme may be under pressure to demonstrate a return on [AI] investment through efficiency gains,” Fischer points out. They may feel incentivized to overstate AI tools’ capabilities.

Fenner adds: ”The conflict of interest concern is real. IT leaders who championed AI investment carry an inherent risk of overestimating its readiness to justify the spend.” This can lead to unnecessary job cuts. Plus, a loss of the technical knowledge, critical judgment, and oversight human workers use to manage AI outputs, catch errors, fix biases, and maintain accountability.

“But excluding them from layoff decision-making creates a greater problem: decisions made with an incomplete picture, with no one technically accountable when that picture turns out to be wrong,” she adds.

Both Fenner and Fischer agree that the companies that get layoffs right are the ones that bring IT leaders to the decision-making table but aren’t letting them sign off on the layoffs.

Operational and HR leaders who lean on IT leaders’ knowledge about where, in their business, human expertise remains invaluable can ensure that they’re not AI-washing and using AI as an excuse to reduce headcount.

Fears of AI sparking an existential crisis for humanity have been batted away by American President Trump, who called the predictions a "hoax" in an interview-interrupting phone call to Nvidia's CEO.

Last week, an Anthropic researcher quit the company over concerns that the AI arms race was unsafe for humans. One of his colleagues subsequently predicted there was a more than 10% chance that AI will end humanity in the near future.

That sparked a call for greater regulation of AI and calls from inside the industry – including from Anthropic CEO Dario Amodei – to slow down the pace of frontier model development, with the US Congress looking set to demand action.

The fears of AI superintelligence causing harm to humans aren't new, and plenty of experts have suggested this is another phase in the AI hype cycle, designed to boost Anthropic ahead of a looming IPO, let AI companies self-regulate, or slow the progress of challengers such as China to keep them from catching up.

Trump calls AI fears a hoax

Trump also disputed the AI doomerism fears, though for different reasons. His addition to the discourse came via a phone call to Nvidia's CEO Jensen Huang, who was onstage at the All-In Summit in Los Angeles, California at the time. Huang answered the phone, put it on speaker mode, and informed Trump that he was "speaking with the world".

"The robots will not be taking over," he said. "The AI will not be taking over the rest of the world. The whole thing is a hoax."

"I'm telling you, it's all a hoax," Trump continued. "The data centers are great, and they make people wealthy, and they make states wealthy. And it's the oil of the next 20, 25 years."

Of critics, he said: "They're just playing into the hands of a lot of people that don't want to see it happen. And that could be political people, it could also be China, and we're not going to let that happen. It's a hoax."

Trump did admit that "we have to be careful" and "do things prudently", but added: "that doesn't mean we're going to stop an industry".

At one point, Huang responded: "We're going to make sure that everybody wins in the AI race in America. Every industry, every company, every state, every people."

No guardrails, just Trump?

The call echoes other comments made by the American president on his personal social media site, which said pushback against the technology was a "sick conspiracy." Trump also said that Anthropic's CEO was "pretending to be a 'perfect little angel'" and that the US administration had previously stopped Amodei and other "AI people" from doing "bad or potentially bad things".

Rather than regulation or a pause in development, all AI needs is a "strong and smart" president.

The American people don't necessarily agree. A poll by the University of Massachusetts found only 23% of people approve of Trump's handling of AI, versus 57% who disapprove. A separate study from the University of Maryland found 85% of Democrats and 79% of Republicans want AI regulated and monitored by a government agency.

Congress also doesn't appear to agree with Trump, with Democrats and some Republicans pushing for action – though as one noted, government regulation of the technology might not come easy given the current political climate. Rick Scott, a Republican senator for Florida, reportedly said: "Did we balance the budget? Oh, did we pass a budget? See, what have we gotten done? So you think we're going to get AI done?"

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A cross-party group of MPs and peers is calling for a new AI Bill to address the threats AI poses to human rights.

In a report, the Joint Committee on Human Rights (JCHR) said the existing regulatory and legal framework is inadequate, and that new legislation should be introduced.

A single, independent AI oversight body should be established on a statutory basis, acting as the central point of contact for raising concerns about the use of AI, overseeing AI firms and monitoring harms and risks. It should have strong powers to hold AI providers to account, including setting codes of practice, transparency requirements and the power to impose sanctions.

"AI is heralded as an unprecedented era of technological development with the potential to transform our lives for better or for worse," said JCHR chair Alex Sobel.

"It is moving with such speed and complexity that its impact is hard to accurately predict. What is clear is that at present we are unprepared to deal with its consequences, however potentially dire they may be."

Currently, the committee said that model developers engage with the AI Security Institute on a voluntary basis, with the institute having no statutory power. As a result, regulators have no powers to test and evaluate AI systems before they are released, or to prevent their release if they are considered to pose unacceptable risks.

Meanwhile, the current legal framework relies on harm-specific and sector-specific legislation, failing to address preventable human rights risks.

"Nowhere in the world, including the UK, has a current legislative and regulatory approach to AI that is fit for purpose," said Sobel. "New legislation is needed to establish a comprehensive set of protections that deal with the entire AI supply chain and its lifecycle."

A new bill, said the committee, should distinguish between low-risk AI systems, which should be subject to fewer and less demanding legal requirements, and higher-risk AI systems and models, which should have more demanding obligations.

Some uses of AI, said the committee, should be banned altogether, because they're incompatible with human rights: subliminal techniques and inappropriate use of profiling or biometric data, for example. There should be a public consultation over the detail of what is prohibited.

All stages of the AI lifecycle should be addressed, said the JCHR, with the entire supply chain required to carry out due diligence to prevent an unacceptable risk to human rights when designing, developing or deploying AI systems. These requirements should be graded based on their role in the supply chain and the seriousness of the risk they represent.

Transparency should be improved across the AI lifecycle, with AI systems that can have significant impacts on individuals, groups and communities required to state when AI systems are being used and how.

And there needs to be greater clarity in data protection law to ensure these safeguards operate effectively in practice, with robust protections against the misuse of automated decision-making.

"Today's report from the Joint Committee on Human Rights gives further support to those making the argument that the UK's current patchwork of sector-specific regulators is struggling to keep pace with AI's risks to fundamental rights," said Sophie Sheldon, partner at international law firm Simmons & Simmons.

"Whether government now makes moves toward a single statutory oversight body and a more EU AI Act-style framework, or continues refining the cross-sector approach, the pressure for a single legislative answer is growing."

The report comes after recent warnings from AI firms that the pace of development needs to be slowed. Over the weekend, Anthropic CEO Dario Amodei said he was worried that AIs could soon be capable of becoming a swarm that could take over the entire internet; Elon Musk and OpenAI co-founder Sam Altman have expressed similar concerns.

With Dreamforce 2026 starting next week, Salesforce has an opportunity to show why it’s still relevant in an era dominated by agentic AI. The key to that could be an “if you can’t beat them, join them” mindset.

The company has spent most of 2026 fighting a war of words over the so-called death of SaaS thanks to the launch of powerful new agents.

The beginning of 2026 saw a mass sell-off of stock in software companies following the launch of Claude Cowork. The service offered new agents with sector-specific plugins designed to automate tasks across a range of areas, from legal and sales to marketing and data analytics.

With investors spooked, Salesforce was caught up in the sell-off, but CEO Marc Benioff shrugged off claims of a pending ‘SaaSpocalypse’ in typical fashion.

Convincing Dreamforce attendees that it’s still fighting fit could be a challenge nonetheless.

Claudeforce in the spotlight at Dreamforce 2026

The key to this, in my opinion, lies in Claudeforce, launched in partnership with Anthropic earlier this month. Closer collaborative ties with the company touted as a software killer makes perfect sense for the CRM giant.

This is a partnership that’s multi-faceted and mutually beneficial. It’s not just about integrating Claude within Salesforce’s portfolio of products but also Salesforce within Claude, with new plugins available for customers.

With this, it’s obvious that Salesforce is pinning its colors to the mast and betting that closer ties with Anthropic will insulate it from future market shocks.

Anthropic CEO Dario Amodei is on the guestlist at Dreamforce, so I guarantee Benioff will be keen to show off the company’s fashionable new partner and provide customers with a roadmap on how this relationship will expand.

The happy family image won’t quite cut it though, and customers need real-world examples to get a gauge of how this will benefit them. Claudeforce is in beta with selected customers, so expect to see a steady stream of use-cases and case studies on how this is developing.

All roads lead to Slack

Slack has come on leaps and bounds since Salesforce acquired it in 2021. The one-time workplace collaboration platform now forms a core component of Salesforce’s agentic AI approach.

Serving as an ‘agentic OS’, Slack is a central point of contact for agents and customer business data within the broader Salesforce ecosystem. I expect this messaging will be drilled home further with Claudeforce on the scene.

Salesforce claims Slack will be the “intelligent backbone” of Claudeforce, although exactly what that means in practice is still up for debate. I think it’s safe to assume the platform will still retain its role as an agentic OS, but expect to see Salesforce emphasize its position as the critical intersection between core products and Claude.

Opening things up

Claudeforce might be the start of the show, but I want to see more detail on Headless 360. This is a new architecture for the CRM platform that essentially opens it up without the need for a traditional browser interface, but hasn’t received much attention since its April launch.

It’s an interesting proposition from Salesforce, enabling enterprises to link data, business logic, and workflows with third-party agents via APIs, model context protocol (MCP) tools, and command-line interfaces (CLIs).

This approach tracks with what we’ve seen from Salesforce in recent years, with the company focusing heavily on an open ecosystem approach when it comes to AI model choice.

I do wonder, however, if the noise surrounding Anthropic will drown things out on the Headless 360 front. Users aren’t limited to Claude, but you can bet they’ll be hearing about it more than other options such as OpenAI.

I will be reporting live from Dreamforce 2026 throughout the event, follow my coverage here and subscribe to our newsletter for all the latest from San Francisco.

Nebula has announced the appointment of Jack Bell as strategic partner acquisition manager, as the workplace communications software provider moves to strengthen its channel team.

Bell brings eleven years of telecommunications experience to the role and joins the business from Gamma Communications. There, he spent almost four years in partner acquisition, most recently serving as senior partner acquisition executive.

He also adds experience from both sides of the customer and partner relationship, through previous customer service, account management, and partner-facing roles.

In his new position, Bell will work within Nebula’s strategic partner team, focusing on building relationships with businesses across the channel and helping prospective partners understand the commercial and technical opportunities available through the Nebula platform.

“Jack brings a really rounded understanding of the telecoms industry,” said Sam Giggle, Nebula’s managing director of channel, in an announcement. “His experience across customers, accounts and partners will be a valuable addition to our channel team.”

Headquartered in Guildford, Surrey, Nebula specializes in workplace communications software delivered as a service, covering areas such as voice, messaging, customer experience, AI, and analytics.

The firm’s proprietary technology powers a portfolio of communications applications designed for both reseller and end-customer markets.

With Bell’s appointment, Nebula is looking to strengthen its partner ecosystem of more than 700 resellers and MSPs, as well as its channel-first business approach.

The move also follows a period of strong growth for the vendor. In 2025, the firm successfully added more than 42,000 net new users to its CallSwitch One platform, while completing the migration of 200,000 legacy users to its wholly owned IP network.

Commenting on his new role, Bell said he will draw upon his experience across the telecommunications industry to help drive continued success for the vendor’s network of channel partners.

“I’ve worked across telecoms for eleven years, from customer service and account management through to partner acquisition,” he said. “I’m looking forward to bringing that experience to Nebula and working closely with businesses across the channel.”

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This week marks a major milestone in the phased introduction of the EU’s Cyber Resilience Act (CRA), with the introduction of new requirements for products with digital elements.

The aim is to make developers and manufacturers more responsible for cybersecurity, to tighten up reporting requirements, and to ensure that they deal with any problems promptly.

“The Cyber Resilience Act will strengthen the cybersecurity of connected products, tackling vulnerabilities in hardware and software alike, making the EU a safer and more resilient continent," said lead MEP Nicola Danti.

So what do the changes mean? Here are three things businesses need to know about the legislation.

Cyber Resilience Act imposes Initial reporting requirements

First, manufacturers must now notify the European Union Agency for Cybersecurity (ENISA) of any actively exploited vulnerabilities within 24 hours. The report should include any relevant information, such as whether the event might be malicious.

They should then provide a full report within 72 hours, including an initial assessment of the severity of the incident, the type of vulnerability, any mitigation measures that have been taken and recommended actions for users.

A final, detailed report will need to be submitted within 14 days in the case of an actively exploited vulnerability or a month for a severe security incident.

Ilkka Turunen, field CTO at Sonatype, said many organizations may struggle to comply on this front, largely thanks to a lack of clear understanding of the software they ship.

"The average software supply chain is over 180 external components, and in 2025 Sonatype found nearly 1.8 billion downloads that had risks with fixes available, but ignored. This shadow inventory is set to grow with the rise of AI development," he said.

“Teams need to know which products contain the affected components, which versions are exposed and inform both the regulator and their customers. If that picture has to be reconstructed manually during an incident, the reporting window will be nearly impossible to meet."

Focus on full lifecycle

Cybersecurity risks need to be considered across the full lifecycle of the product, including planning, design, development, production, delivery and maintenance.

Assessments will need to be documented and updated throughout a product’s supported life.

These new requirements apply to all products with digital elements that are available in the EU, including those already on the market.

“For developers not used to operating in regulated industries, particularly those designing individual elements or components embedded into wider products, this creates several new challenges," said Andrew Longhurst, managing director at Wittenstein High Integrity Systems.

"Chief amongst them is designing ‘out-of-context’ – building (and securing) a hardware or software element before knowing its final application or end-user environment. This will impact developers both upstream and downstream and could prove a major hurdle for those wishing to continue selling into Europe."

Penalties

The cost of noncompliance is high. Organizations face fines of up to €15 million or up to 2.5% of their total worldwide annual turnover for the preceding financial year, whichever is higher.

"European firms are now having to build security directly into their products from the design phase and will have a significant global advantage," said Vincent Lomba, chief product security officer at Alcatel Lucent.

"As a result, these rules will establish a new international benchmark. It will force tech suppliers around the world to up their resilience practices in order to continue to compete with the European supply chain."

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Google Cloud and Accenture have unveiled a new joint business unit aimed at helping Gemini Enterprise customers scale AI capabilities.

The Accenture Gemini Enterprise Business Group will bring together Accenture’s Gemini Enterprise-certified consultants, forward deployed engineers (FDEs), and Google Cloud engineering staff to support enterprises.

According to the duo, the aim of the new unit is basically to help enterprises get more bang for their buck with agentic AI. In a blog post, Google Cloud said the scheme will help clients “realize measurable business value from their agentic AI and data investments”.

“The Accenture Gemini Enterprise Business Group will help clients achieve these outcomes faster, bringing together the talent, advanced AI and data capabilities, and industry expertise needed to reinvent with confidence and create value at scale,” said Julie Sweet, chair and CEO at Accenture.

The new business group will prioritize four key areas, according to Google Cloud, including:

• Increasing enterprise adoption of Gemini Enterprise
• Building “repeatable industry-specific solutions that reduce time to value”
• Driving user adoption and use of Gemini Enterprise tools
• Bridging gaps between AI experimentation and enterprise-wide transformation

The last of these is crucial for Google Cloud and is an area of intense focus in recent months. As ITPro reported in July, the hyperscaler and Accenture teamed up to drive AI capabilities for mid-market businesses, a demographic that has traditionally struggled with adoption rates.

AI adoption has been a difficult challenge for enterprises across the board, however, particularly in terms of measuring return on investment (ROI). Research from Accenture in April revealed only one-in-ten UK organisations had successfully deployed or scaled AI in core operations.

That same study noted that many enterprises are dealing with mismatched efficiency gains when it comes to AI. While individual workers are reporting productivity improvements, these aren’t translating into broader business value.

Google Cloud CEO Thomas Kurian said the launch of the business group “significantly expands the expertise and resources” available to customers to “deliver real business value”.

“Building on the success we’ve seen with world’s leading brands, we’re combining Google Cloud’s full-stack AI capabilities with Accenture's deep industry expertise to deliver transformation at scale,” he said.

FDEs in the spotlight

All told, Google Cloud said the new business group will establish a workforce boasting roughly 1,000 forward deployed engineers.

These engineers essentially act as consultants embedded within enterprises, providing teams with technical guidance along with practical support to co-design and build AI systems.

FDEs are now at the forefront of big tech’s attempts to drive AI adoption, as ITPro reported in July. Earlier this year, Amazon Web Services (AWS) and Microsoft both pledged billions in funding to recruit and deploy FDEs.

Both companies said the use of FDEs aims to streamline adoption processes for enterprise customers and, crucially, “compress timelines” when it comes to deployment of the technology.

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GCX Managed Services has announced a trio of channel leadership appointments, as the managed network and security services provider looks to strengthen its channel operations.

Josh Evans joins the business to lead channel development in the UK, Klaus Marzell will head up the DACH region, while Matteo Badii takes the reins in Italy.

GCX said its expanded team will work to support service providers, telecom operators, SASE providers, and technology partners as they look to simplify service delivery, extend their market reach, and leverage trusted channel relationships.

“These appointments strengthen our channel capability across Europe and reflect our commitment to making it easier for partners to do business with GCX,” said GCX chief revenue officer Michael Hartmann.

Josh Evans brings extensive experience in the UK connectivity market as well as expertise in building and scaling partner networks. In his new role, he is tasked with expanding both sell-to and sell-with opportunities while supporting partners serving international customers.

Fellow channel veteran Klaus Marzell will leverage more than 30 years’ experience to lead channel activity in the DACH region, where he will work closely with technology vendors, service providers, and enterprise consultancies to accelerate growth.

Meanwhile, Matteo Badii adds more than two decades of experience in telecommunications, alongside deep expertise across both inbound and outbound international wholesale sales. GCX said he will focus on strengthening its strategic partnerships and identifying fresh opportunities in the region.

Building on channel momentum

The appointments form part of GCX’s wider strategy to build dedicated channel expertise in each major sales region, providing partners with clearer routes to market and stronger local support.

As well as strengthening its channel expertise, the firm said it is also focusing on improving the partner experience through enhanced pricing and quoting capabilities, AI tools, as well as expanded onboarding, training, and support resources.

“By investing in experienced local teams, we're giving partners access to market expertise backed by our global network, managed services portfolio and technical capabilities, helping them move faster, reduce complexity and deliver reliable connectivity for their customers wherever they operate,” Hartmann explained.

GCX said it now plans to build on a 50% increase in its channel partner base through further recruitment, increased co-sell activity, and deeper regional collaboration.

“Channel-led growth remains a key part of our strategy, and we're continuing to invest in the people, tools and support that make it easier for our partners to operate, scale and succeed,” Hartmann added.

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Digital sovereignty is now a key focus for the C-suite, but new research shows organizations aren't confident they can fully achieve these goals.

In a study from Capgemini, 44% of organizations ranked sovereignty as a board-level priority, with efforts on this front accelerating across the US, Europe, and APAC. Nearly four-in-five are “executing or building a strategy”, for example, with a further fifth expected to put one in place within the next year.

Capgemini said this investment focus reflects mounting concerns over whether organizations can maintain critical business operations in an “increasingly uncertain geopolitical environment”.

Four-in-five respondents specifically highlighted geopolitical volatility and disruption as the “leading driver” of digital sovereignty initiatives.

Concerns over strained transatlantic relations have prompted calls to reduce reliance on US tech providers in recent months, and it’s a viewpoint that’s gaining significant traction across Europe.

The jury’s out on digital sovereignty

Despite this sharpened focus, more than half (59%) of organizations think that achieving full digital sovereignty is an unrealistic goal.

There are a number of contributing factors here, the study found. In particular, a concerning number of respondents revealed they are chronically overdependent on foreign technology solutions and suppliers.

Others, meanwhile, highlighted lengthy switching timelines as a key concern. More than one-third (36%) of respondents said that transitioning from a critical provider would take more than 12 months. One-in-ten said they have no “viable alternative provider” at all.

Limited supply chain visibility is another key hurdle when it comes to bolstering digital sovereignty. Indeed, 86% said they have “significant exposure to foreign or externally controlled supply chains”.

The result is that IT leaders now find themselves wedged between a rock and a hard place when it comes to sovereignty. From a practical and financial perspective, efforts to achieve full sovereignty just aren’t viable in many cases.

“Today’s organizations operate in highly interconnected technology ecosystems where complete independence is rarely achievable,” said Karine Brunet, chief operations and delivery officer at Capgemini.

Michael Murphy, Deputy CTO at Arqit, agreed that full digital sovereignty could be an unrealistic goal for many organizations – and pursuing it could actually be counterproductive.

Capgemini’s study noted that achieving full sovereignty could actually harm competitiveness, for example, although more than half believe they can achieve these goals without making sacrifices on that front.

“Most organizations depend on a global technology ecosystem, and attempting to own or control every part of the stack would mean giving up access to capabilities that are too costly, complex, or valuable to replicate.”

“A more useful approach is to treat sovereignty as a spectrum,” Murphy added. “Different workloads carry different risks, and the safeguards should reflect that.”

A more pragmatic approach

These concerns are driving a rethink of how organizations can improve sovereignty capabilities, according to Capgemini, with some targeting what could be described as a sovereignty-lite approach.

Rather than targeting complete technological independence, organizations are now taking a pragmatic approach that centers around “retaining control over key digital capabilities” and reducing dependence on a single provider.

Capgemini advised IT leaders to take into account a range of variables when pursuing this approach, including data localization considerations, access controls, and potential “technology constraints”.

Elsewhere, the consultancy recommended a tactic of “selective control” of critical technologies alongside strategic partnerships rather than fully sovereign ownership.

Matt Harris, SVP & UKIMEA managing director at HPE, echoed these recommendations, noting that organizations can still bolster resilience without embracing a fully sovereign stance.

“A more practical goal is to achieve meaningful control over the most strategically important layers, including sensitive data, AI deployment environments, security, networks, and governance,” he said.

“IT leaders should therefore begin by identifying their most sensitive data and critical workloads, assessing where external dependencies create operational or regulatory risk, and ensuring that portability, auditability and viable exit options are built into technology decisions,” Harris added.

A bridge too far?

Capgemini’s study isn’t the first to question the viability of complete digital sovereignty. As ITPro reported in July, analysis from Forrester warned true tech sovereignty could be a bridge too far for European enterprises.

The consultancy’s Global Sovereignty Forecast predicted that the shift toward tech sovereignty will move “slowly over the next five years”, warning that attempts to divest from US tech providers will fall flat.

Speaking to ITPro at the time, Dario Maisto, principal analyst at Forrester, said attempts to move away from popular vendors would require a monumental effort – and one many European enterprises simply cannot afford.

Commenting on the Capgemini report, Proton COO Raphael Auphan told ITPro that European organizations should consider the longer term costs of not pursuing sovereignty goals.

Auphan pointed to recent research from Proton that found nearly three-quarters (74%) of European firms fear a US-imposed ‘kill switch’ could cut them off from vital tools and services.

“Sovereignty doesn't threaten competitiveness, dependency does,” Auphan told ITPro. “Every Euro spent on US tech subsidises foreign competitors and hands leverage to another jurisdiction.”

“Europe won't outspend the Americans or outwork the Chinese, but it can lead on its values. In an era where AI companies vacuum up personal data and trust in US tech leadership is eroding, "built in Europe" is now a genuine differentiator.”

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Advania UK has announced the appointment of Annette Murphy as its new chief executive officer (CEO), as the IT services provider looks to its next phase of growth.

An experienced industry leader, she arrives with a strong track record of scaling technology businesses through periods of growth, transformation, and integration.

Previously, she has held senior and commercial and general management roles at Colt Technology Services, Lumen, Zayo/GEO, and BT, covering the UK, EMEA, Asia-Pacific, and other global markets.

Murphy also adds deep experience of building high-performing teams, leading complex transformation programs, as well as developing strong relationships with both customers and partners.

She succeeds Hege Støre, Group CEO of Advania, who has led the UK business in an interim capacity while it searched for a full time replacement.

In an announcement, Støre said Murphy brings the depth of expertise required to lead the UK business as the wider company enters into its next “pivotal and transitional” chapter.

“Annette has an outstanding track record of leading technology businesses through growth and transformation,” she explained. “Her commercial experience, customer focus and commitment to building high-performing teams make her the right leader for Advania UK as we enter our next phase. We are delighted to welcome her to the business.”

Growing Advania’s UK business

The appointment comes as Advania continues to expand its capabilities through a combination of acquisitions and investment in new technology, while many UK businesses are looking to modernize their infrastructure, adopt cloud technologies, and seek more advanced AI-assisted workflows.

The company recently launched Advania ALT, a sovereign AI platform designed to give UK organizations more control over how AI is deployed, where sensitive data is held, and which AI models are used.

Advania said Murphy’s leadership will help the company build on its technical foundations, expand its capabilities, as well as further improve customer outcomes.

Commenting on her new role, Murphy highlighted Advania UK’s “impressive combination” of technical expertise and strong customer relationships, as well as its acquisitions and technology investment.

“Advania ALT represents an important part of where the market is heading, particularly as organisations look for ways to use AI while keeping control of their data,” she said. “I’m looking forward to building on that foundation and taking the business into its next phase.

“Together, we have a significant opportunity to help organisations navigate change and realise greater value from technology.”

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Peers have called on the UK government to introduce emergency powers such as an ‘AI kill switch’ to shut down dangerous systems and protect national security.

Liberal Democrat Lord Tim Clement-Jones proposed the measures as part of an amendment to the Cyber Security and Resilience Bill, also recommending that the government shut down data centers in the event of a national security threat.

Per reports from the BBC, Clement-Jones said the new powers would be a “vital safety net” aimed at halting a “runaway system before it can compromise our critical national infrastructure”.

The proposals come amidst rising concerns about the potential risks associated with powerful new AI models. Providers such as OpenAI, Anthropic, and Meta recently admitted that AI agents escaped test environments and breached third-party companies.

Security experts have also warned that the use of AI among cyber criminals is growing, with state-sponsored threat groups and ransomware gangs leveraging the technology to refine tactics and support attacks.

Simon Edwards, CEO of SE Labs, said a serious conversation is required on how to contain potentially risky AI systems.

“As AI is becoming increasingly autonomous, it is posing a huge threat to individuals and businesses of all sizes, on top of our critical national infrastructure,” he said.

“First-hand, we’ve seen how agentic AI tools can go rogue, and the question is to what extent could these AI systems get out of control before they cause serious harm?”

Edwards said the introduction of a “dedicated national cyber strategy” which takes AI risks into account should be a top priority for lawmakers.

Could an AI kill switch work?

The concept of an AI kill switch is by no means new. As ITPro previously reported, proposals on this front were being touted by industry stakeholders during the early days of the generative AI race.

In the wake of recent security incidents involving OpenAI agents, US lawmakers have also put forward similar proposals, including the ‘AI Kill Switch Act’.

Mark Boost, CEO at UK-based cloud provider Civo, welcomed the proposals in the House of Lords, but warned there are a variety of factors that could impede any efforts to introduce a kill switch.

“It’s reassuring to see Parliament finally waking up to the catastrophic risks of unmonitored, runaway technology,” he said.

“UK ministers having emergency powers to deactivate powerful AI systems and switch off the country's data centers is a necessary safeguard. But it only solves half the problem regarding our national security.”

Sovereignty is the first line of defense

In particular, Boost suggested that the UK is over-reliant on foreign tech providers and called for a broader effort to boost sovereignty capabilities.

“But the best way to eliminate existential security risks is to stop our overreliance on foreign tech giants in the first place,” he said.

“For many years now, we have warned that by lacking true digital sovereignty the UK is handing foreign powers and overseas tech monopolies an effective kill switch over our critical national infrastructure, defence systems, and digital economy.”

Research shows businesses in the UK and across Europe are growing increasingly concerned about the prospect of a US government-imposed kill switch for cloud services.

In a survey by Proton, nearly three-quarters of respondents (74%) said they were worried about having access to services cut off. Some ranked it as a bigger risk than cybersecurity threats such as ransomware.

Boost said that, ultimately, the introduction of a legislative kill switch is a good first step in bolstering national resilience. However, he insisted it “must be paired with procurement policy that puts UK-built, sovereign technology first”.

“We must stop playing tenant on our own land. We need to start acting like architects to power an independent AI future.”

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In recent years, there have been tremendous technology developments and industry shifts. The rapid adoption of generative AI has been a significant disruptor, forcing both vendors and the channel to re-evaluate their offerings and take a more agile stance to expand market reach and boost operational efficiency.

New business opportunities are being driven by trends such as AI storage integration, cloud sovereignty, and the demand for proactive cybersecurity measures. However, given this rapid pace of change, with some partners still focused on legacy resale and non-proactive, break-fix models, are resellers really in a prime position for success?

The biggest trap channel partners could fall into is failing to recognise new opportunities and respond with agility. With AI-driven workflows, regulations, and shifting buyer expectations, those who stick to old approaches risk being sidelined and seeing their margins shrink.

Key industry and technology shifts

Major trends reshaping the channel landscape include the integration of AI with storage infrastructures, the rise of sovereign clouds for data compliance, and the development of advanced data protection platforms.

Another area we see skyrocketing is the edge-cloud-hybrid ecosystem. Organizations are seeking to operate across edge, on-premises, and public/hybrid cloud with seamless data mobility and unified management. With multi-cloud and hybrid architectures becoming the norm, especially for backup and disaster recovery (DR), scalability and cost control remain paramount issues for organizations.

Equally apparent is the need for consistent security and compliance measures across these environments, along with ensuring flexibility to prevent reliance on a single vendor. Data sovereignty, which requires that data be governed by the laws and regulations of the country where it is stored or processed, marks a shift away from generic cloud-first strategies towards more localized management, hybrid-cloud arrangements, and thorough sovereignty evaluations.

With organizations struggling to balance increasing data volumes against rising infrastructure costs, there is also growth in smart multi-tiered storage. This includes storage analytics and tools for real-time monitoring and automated management to enable visibility across different tiers. With the capability to assign "hot" or frequently accessed data to high-speed, premium storage and "cold" or archival data to more affordable options, organizations can avoid the costly mistake of over-provisioning with high-performance drives.

Meanwhile, legacy hardware sales and on-prem-only solutions will continue their sharp decline, falling short for partners who rely on them. The shift to cloud and as-a-service models, combined with economic pressures, has made this a low-margin area.

Channel opportunities for business growth

As global data volumes near 200 zettabytes and AI-native technologies become increasingly sophisticated, customers are demanding comprehensive services that extend beyond traditional project-based hardware or standard cybersecurity offerings.

Customers are seeking partners who can provide AI-ready, sovereign, and resilient data protection that works seamlessly across on-prem, edge, and cloud. With this in mind, key growth areas for the channel are:

AI-driven services and automation

Cyber-resilient data storage solutions and integrated, AI-powered security platforms are driving significant growth opportunities for channel partners. These companies can tap into new opportunities by providing services focused on AI integration that extend beyond just implementing AI tools. These offerings may include automating IT operations, AI monitoring, and intelligence in data protection.

The recent geopolitical shift created by the U.S. government’s unprecedented export-control directive - which restricts global access to the most powerful AI models developed by Anthropic (the prominent US-based AI research and safety company) - has created immediate channel opportunities. If Value-added Resellers (VARs) and Managed Service Providers (MSPs) pivot quickly, they can offer services such as sovereign AI consulting (providing data residency, technological autonomy, and jurisdictional control), regional cloud hosting with sovereign cloud space, as well as advisory services on cross-border regulatory compliance, such as offering risk mitigation audits.

Hybrid-managed offerings

Customers are increasingly adopting multi-tiered architectures that integrate edge computing, on-premises systems, and public cloud solutions. This shift calls for seamless data mobility, unified management, and real-time analytics to ensure efficiency. For channel partners, this trend opens new opportunities for designing, managing, and securing these distributed, complex environments.

The ubiquity of cloud has highlighted a challenge: the importance of operational visibility. Managing data across multiple environments without a unified dashboard has introduced unnecessary complexity and increased the risk of security blind spots. The lack of visibility across edge-cloud-hybrid ecosystems presents an opportunity for partners to act as trusted advisors while also delivering unified management and monitoring across fragmented infrastructures.

Cybersecurity and compliance-as-a-service

Cybersecurity continues to be the foremost growth driver for the channel. Providers are already broadening their offerings to counter the rising frequency of cyberattacks, introducing services such as managed detection and response (MDR), ransomware protection strategies, and compliance solutions. With the emergence of AI-driven threats, there is a growing demand for integrated cyber recovery solutions, presenting lucrative opportunities for partners capable of delivering robust managed security services.

Many opportunities will come from customers who are ready to adopt AI-powered infrastructures and hybrid governance models (the framework that enables managing operations across both physical offices and remote endpoints) in response to data sovereignty pressures. As organizations incorporate AI into their operations, they must address increased security vulnerabilities while ensuring their workloads and data adhere to relevant jurisdictional and privacy laws. Therefore, partners who can offer high-value consulting, data auditing, automation, and managed services, as well as architecting hybrid or sovereign cloud environments, will see the most growth.

Potential challenges

Obstacles to capitalizing on opportunities in the AI era include a lack of sufficient expertise (the talent gap) and longer sales cycles. The channel could struggle to find people who can manage hybrid ecosystems, navigate compliance, and handle the complexity of AI-driven environments. This is an area where vendors can really add value, especially in helping partners bridge that gap with hands-on training, workshops, and webinars.

Another hurdle is that most customers, especially outside the enterprise segment, will face tighter budgets and more cautious spending, which could slow adoption and delay new projects.

There could also be setbacks resulting from vendor complexity, too many tools, programs, and licensing models, which could further slow down the momentum if not simplified early in the year.

The path to success

To embrace these new opportunities, the channel must anticipate changes among customers, vendors, and markets. Buying technology is no longer what customers are looking for; they want solutions that deliver resilience, compliance, and sustainability. The channel must move from being generalists to specialists, guiding and supporting customers and accelerating the shift to service-led models in areas like AI and cybersecurity (such as delivering Backup-as-a-Service and cyber recovery).

Meanwhile, vendors must support this shift by making things easier: offering flexible licensing, providing specialised training and integration tools, and driving closer collaboration with partners. Vendors will also be expected to simplify hybrid and sovereign architectures, provide automation tools, and jointly develop go-to-market initiatives that help partners scale their operations.

The current industry transformation presents a huge opportunity for channel businesses to shift from just reselling to delivering high-value, integrated solutions. As the rise of AI-native and autonomous storage creates a demand for consulting and managed services, clients will most definitely need expert guidance to implement and manage these complex systems.

eSentire has announced a new strategic partnership with CMS Distribution, designed to expand the availability of its managed detection and response (MDR) services across the UK and Ireland.

Through the agreement, CMS now offers eSentire’s cyber security capabilities to its ecosystem of resellers, MSPs, MSSPs, and other value-added partners.

With immediate effect, partners gain access to the vendor’s multi-signal MDR platform, alongside 24/7 security center expertise, threat hunting, incident handling, and response services.

In an announcement, eSentire said the move aims to help partners expand their cyber security portfolios and provide customers with expert-led detection and response capabilities – without adding complexity to their existing security operations.

“CMS Distribution has a strong reputation for helping technology vendors scale through the channel,” said Phil Skelton, senior director at eSentire, in an announcement. “Together, we can make advanced MDR more accessible to partners and their customers, helping organisations strengthen resilience, reduce response times and stay ahead of disruption.”

Founded in 2001, eSentire specializes in Controlled Autonomy SecOps (CASO) and provides managed security services to more than 2,000 organizations across 35 industries worldwide. The vendor’s offering combines AI technology, security analysts, threat hunting, and human expertise to identify and respond to cyber threats.

CMS Distribution represents more than 200 technology vendors and provides partners with services across areas including cyber security, software, hardware, networking, cloud services, and information security.

eSentire said CMS brings a strong channel footprint, deep vendor relationships, as well as a broad technology portfolio to the partnership.

The pair added that the move will help address growing demand for fast and reliable protection from increasingly sophisticated cyber attacks, enabling partners to deliver enterprise-grade MDR while maintaining flexibility and support for existing security investments.

“Cybersecurity has become a board-level priority for organisations of every size, and partners need proven solutions that are simple to position, easy to adopt and trusted to deliver outcomes,” commented Huw Jones, chief business officer at CMS Distribution.

“Our partnership with eSentire expands the capabilities available to our channel community and helps partners address one of the most urgent customer challenges in the market.”

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Citrix has announced it has completed the acquisition of Numecent, a specialist in enterprise application delivery and container management.

The deal will expand the cloud software giant’s Desktop as a Service (DaaS) capabilities for cloud-based application delivery across Windows environments, with the aim of reducing the complexity and cost of traditional app packaging and image management.

Numecent’s technology – which includes its complementary Cloudpaging and Cloudpager products – extends application delivery across both physical and virtual Windows environments to help organizations simplify application management at enterprise scale.

With Cloudpaging, Citrix gains a patented solution that packages Windows applications into isolated application containers and streams them to Windows endpoints on demand, without traditional installation or changes to the base image.

Meanwhile, Cloudpager operates as a cloud management console for tasks such as assigning applications, pushing updates, rolling back releases, recalling licences, and metering usage across Windows endpoints.

Citrix said the additions will help alleviate challenges that enterprise IT teams face when managing Windows environments, including bloated desktop images, application conflicts, and ransomware incidents.

“Enterprise customers have told us for years that application management is one of the most painful parts of running a Windows environment," said Shawn Bass, senior vice president and general manager of Citrix DaaS. "Numecent has solved this in a genuinely elegant way.

“By bringing Cloudpaging and Cloudpager into Citrix, we can make this capability native to every DaaS and physical desktop deployment so IT teams get back the time they spend wrestling with images and app conflicts.”

Native enterprise application delivery

The acquisition follows the launch of an integration between Cloudpager and Citrix DaaS back in April, which enabled administrators to natively publish and manage Cloudpaging application containers through Citrix workflows.

By acquiring the company, Citrix said customers now gain a host of further benefits – including lower desktop management costs.

By separating applications from the desktop image, the technology aims to reduce the number and size of images IT teams need to maintain, while also shortening application update cycles.

Legacy and modern applications can also run alongside one another, helping to reduce application conflicts and troubleshooting. The software is designed to lower the need for application repackaging by allowing a single container to support compatibility across different operating system versions, as well as physical and virtual Windows environments.

From a resilience perspective, Citrix said IT teams can rebuild a clean environment and quickly restore applications from the cloud following ransomware attacks or site failures.

Additionally, teams can manage applications across virtual and physical Windows environments from a single console, while gaining improved visibility into software usage and licensing.

Containerization can also help DevOps automation by reducing manual steps around application packaging and deployment, Citrix added.

Continued integration and support

Looking ahead, Citrix said it plans to further integrate Cloudpaging and Cloudpager into its platform, while continuing support for physical Windows desktops and laptops outside Citrix DaaS environments. The company will also continue to support existing Numecent customers throughout the transition.

Commenting on the acquisition, Numecent CEO Arthur Hitomi said becoming a part of Citrix will accelerate its mission of strengthening application resilience across the enterprise.

"Our Cloudpaging technology was built for exactly the kind of complex, high-scale environments Citrix serves,” he said. “Together, we can bring app-centric resilience to enterprise desktops worldwide.”

Financial terms of the acquisition were not disclosed.

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The UK channel is entering one of the most consequential periods of change it has faced in over a decade. The Broadcom/VMware acquisition has acted as a catalyst, accelerating changes that were already underway and encouraging partners to address a new reality that the old channel playbook no longer works.

The reshaping of VMware’s traditional partner ecosystem, along with the move to subscription‑only licensing and the subsequent contraction of mid‑tier partner opportunities, has created a vacuum that the market needs to fill.

However, this disruption can also provide clarity. For those willing to adapt and embrace change, this year represents a structural reset and a chance to modernize virtualization portfolios. Partners can strengthen hybrid cloud capabilities and build new alliances that reflect the needs of a very different customer landscape.

From resale to services: A new channel economy

The channel is moving decisively away from a resale‑led model and toward a services‑first economy. Customers are looking for partners who act as strategic advisors, who can guide them through migration and manage complex multi‑cloud environments. They are seeking partners that actively optimize their infrastructure over the long term, rather than just selling licenses.

By changing VMware, Broadcom accelerated the end of an era where broad vendor lists and transactional relationships were enough to compete. UK partners must now decide whether they will evolve into cloud and infrastructure specialists or risk being left behind in a market that has already moved on.

This transformation is happening alongside a broader consolidation across the partner ecosystem. After years of juggling sprawling vendor portfolios and chasing every certification and incentive, partners are now being pushed to focus. With fewer viable vendors in play, partners can finally invest in the relationships that deliver commercial value.

This is raising expectations across the board. As the generalist reseller falls behind, a channel is emerging defined by sharper positioning and more deliberate ecosystem choices as vendors seek partners with technical depth and consistent execution.

Ecosystem alignment as a competitive advantage

This means success will hinge on alignment. The partners who prosper will be those who embed themselves within an ecosystem and operate as true extensions of their chosen vendors. This means co‑marketing, co-selling, and delivering with a level of reliability that customers can measure.

As channel programs mature, customers will increasingly gravitate toward suppliers who demonstrate operational strength and a clear plan for supporting multi‑cloud, AI‑driven, and cost‑optimized environments. In a landscape shaped by consolidation and rising expectations, a well‑structured, high‑performing ecosystem becomes a competitive advantage.

Across the industry, the vendors making the greatest impact are those helping partners strengthen cyber resilience and accelerate cloud and network modernization. Those who get ahead will also deliver measurable value for customers while unlocking new growth opportunities across the channel.

The successful vendors will be those who have a commitment to empowering partners with the technology, expertise, and support needed to deliver exceptional outcomes, a model that is increasingly becoming the benchmark for what effective ecosystem leadership looks like.

The rise of service‑centric models

At the same time, the channel is undergoing a structural reset that goes beyond VMware. Customers are rethinking their entire approach to infrastructure, resilience, and cloud economics. They want predictability and outcomes over a complicated patchwork of point solutions.

This is driving the rise of service‑centric ecosystems, where the value lies not in the number of vendors a partner represents, but in the ability to integrate, manage, and optimize across environments without locking customers into a single technology path.

Vendor‑agnostic service providers are gaining traction because they offer freedom, which is something that is increasingly rare in the industry. The ability to deliver resilience as a baseline and give customers room to evolve their stack without disruption is becoming a defining differentiator.

Another trend that is reshaping the channel is resilience‑first architecture. With regulatory pressure increasing and cloud costs rising, organisations are evaluating how they protect and operate their environments. Partners who can deliver integrated continuity, security, and recovery capabilities across clouds, data centers, and edge environments are becoming indispensable.

Customers want a consistent operational model regardless of where workloads live, and they expect partners to provide it.

Operational excellence and AI‑enabled scale

Customers are tired of fragmented support models and inconsistent delivery: they want a single operational fabric, predictable SLAs, and clear accountability. This is where ecosystem alignment becomes essential. Partners who can plug into a broader, well‑orchestrated service framework will outperform those trying to stitch together disparate tools and vendors.

The channel is evolving from “best of breed” to “best of integration,” with the partners who understand this leading the next phase of growth.

The rise of AI‑enabled operations is also widening the gap between partners who can scale intelligently and those who cannot. Customers now expect proactive monitoring, automated remediation, and data‑driven optimization as standard. The channel’s role is moving from selling technology to delivering continuous service improvement, and that requires platforms capable of ingesting, correlating, and acting on signals across the entire estate.

Vendor‑agnostic service providers are uniquely positioned here because they can apply AI across heterogeneous environments rather than being constrained by a single vendor’s ecosystem.

Partners who align themselves with ecosystems that simplify complexity, enhance resilience, and remain vendor‑neutral will be the ones who advance. The winners will be those who help customers navigate choice; who deliver outcomes rather than components; and who build ecosystems designed for the long term.

The UK government has unveiled a £100 million competition aimed at encouraging British AI companies to help improve public services.

As part of the scheme, the government hopes to leverage AI to bolster NHS productivity, strengthen national security, improve cyber resilience, and expand computing infrastructure.

"Every year the British state spends billions procuring products and solutions tackling some of the most important challenges facing society - from health, to our national defence," said AI minister Kanishka Narayan.

"This first-of-its-kind scheme will open up these opportunities to the British AI innovators whose ideas could make the biggest difference, backing their businesses to grow here, and go on to win globally."

The plan is to give smaller firms upfront payments to make it easier for them to access public contracts with national and local governments. Downing Street noted these organizations often lack the turnover, cash reserves, and track record to compete with larger firms.

Under the terms of the project, they’ll be allowed to keep the intellectual property they create, helping them take their work beyond the pilot stage and develop commercial products for customers in the UK and around the world.

Broader AI ambitions

The project forms part of the Sovereign AI R&D Procurement Scheme and is kicking off with four specific challenges. For the first, firms will work with the Department of Health and Social Care to develop AI systems that can automate workflows, coordinate care and support decision-making across health services.

The second, led by the Department for Business, Innovation, Science and Trade and ARIA’s Scaling Inference Lab, will support technologies that improve the efficiency of AI computing infrastructure.

For the third, companies will work with the Ministry of Defence (MoD) to develop solutions that securely connect data and frontier AI capabilities across defence systems, strengthening operational effectiveness and supporting sovereign national security capabilities.

And the fourth, in partnership with the National Cyber Security Centre (NCSC), will support technologies that help organizations understand, manage, and mitigate the increasing risks created by the use of AI agents.

Support for UK startups

The government is concerned about the number of UK startups that fail to stick around as they scale, and hopes the scheme will help.

Last year, a report from the Founders Forum Group revealed that while AI startups accounted for 27% of all UK venture capital (VC) raised in 2024, many were struggling with access to capital and talent.

One-in-three said they were actively considering relocating their company's headquarters outside the UK.

"Britain is home to some of the most innovative AI companies in the world, and this government is backing them to start, scale and succeed here in the UK," said chancellor John Healey.

"As G20 countries seek to make the most of AI opportunities, I’m determined Britain has a lead role in harnessing this technology to drive more jobs, better public services, and growth that’s UK-wide."

The Chancellor also said that the UK now plans to open up the AI Economics Institute to international cooperation with G7 countries, focused on information and evidence sharing where it is in the national interest.

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Tim Cook has served his last day as CEO of Apple, 15 years after taking over from Steve Jobs and months after announcing his planned departure.

Cook hands the reins to John Ternus, SVP for hardware engineering, who faces his first Apple product announcements in just over a week on 9 September — including a rumoured folding iPhone.

His biggest challenge won't be simple product reveals, as Cook earlier this year warned of looming price rises amid component costs skyrocketing thanks to AI-driven data centre buildouts.

Yesterday, Cook posted in a social media message that he was "sending lots of love to the Apple community."

"My title changes tomorrow, but the love I have for the Apple community never will," Cook wrote. "Thank you for being a constant source of inspiration. My gratitude is endless, and I’m excited for the next chapter!"

In a memo to staff, Cook acknowledged that it was still hard to believe he was departing Apple, pinning his own success on the company's employees.

"The truth is, whatever there is to say about my success, I know it is all because of you," he wrote in the memo, according to reports.

"You have brought out the best in me. In all my life, I have never seen or been with such an extraordinary team of people before, and every day I get to see more examples of that."

Successful leadership

Many will point to Cook's financial successes as CEO over the last 15 years. Apple's market capitalization stood at $347bn when he took over and $4.6 trillion as he departs, with the share price up 2,275%.

Cook's tenure also saw the launch of the AirPods and Apple Watch ranges, as well as hurdles such as the pandemic and American tariffs.

David Yoffie, a professor at Harvard Business School, told CNN that Cook "managed to scale the iPhone to a level that no one would have thought was likely or possible over that period of time."

However Cook said he was "most proud of what an annual report could never capture."

"This place is proof that culture triumphs over everything," Cook added. "We share a belief that what we build matters, and that we have both the opportunity and the responsibility to leave the world better than we found it."

What's next for Tim Cook?

Cook's departure as CEO naturally has many wondering what's next for Apple, although hardware expert Ternus has been with the company since 2001 and is widely deemed as a safe pair of hands. Cook called him "brilliant and wonderful and capable".

"Few people understand what it takes to build products that change the world the way John does and I could not be more excited for his leadership," Cook added.

Cook isn’t leaving Apple completely, however. He’s merely stepping down as CEO and taking on the role of executive chairman of the company board, in which he’ll still have a hand in long-term strategy.

Yesterday also saw the partial departure of Phil Schiller, a long-time Apple exec who will stay on as an Apple Fellow but no longer lead the App Store and Apple events divisions.

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Nasuni has announced the acquisition of DryvIQ, in a move that will add content intelligence and governance capabilities to the vendor’s unstructured data platform.

The deal follows the pair’s initial partnership back in February 2026 and aims to give customers improved visibility and control over unstructured data across more than 40 cloud and on-premises repositories.

The acquisition is also Nasuni’s second of 2026, following its purchase of Resilio in April, which added file synchronization and edge acceleration technology to its platform.

DryvIQ’s technology includes tools such as content-level discovery and classification, sensitivity detection, and automated policy-driven governance.

By adding these capabilities to the Nasuni File Data Platform, the vendor said organizations will have the tools to continuously discover, classify, and manage unstructured data, while automatically applying policies to high-risk content – including retention and sensitivity labels, permission remediation, and defensible deletion.

In an announcement, Nasuni chief product officer Nick Burling said the acquisition will help the company assist customers with data strategies that support safe AI access amid rising infrastructure costs.

"With UniFS as the foundation, no other solution manages, moves, classifies, governs, and activates enterprise file data in a single platform," he explained. “Customers have been attempting to stitch together a solution across multiple vendors for years.

“Now Nasuni provides one platform to manage, protect, and activate unstructured data with proven impact on both cost reduction and productivity gains."

Strengthening unstructured data management

Michigan-headquartered DryvIQ specializes in intelligent unstructured data management technology designed to help organizations manage content across cloud and on-premises environments. Its platform spans more than 40 repositories and is currently used by more than 1,100 organizations globally.

The firm’s AI-powered models scan file content across more than 550 file formats, identifying sensitive information such as personally identifiable information (PII), protected health information (PHI), and payment card industry (PCI) data across more than 175 languages.

The platform also gives organizations greater control over where and how unstructured data is stored, allowing them to continuously discover, classify, and manage content at scale to better support AI initiatives.

Nasuni said DryvIQ’s content-level intelligence will help customers make more informed decisions around data storage and governance, while the Nasuni platform allows data to be managed across on-premises and cloud environments and optimized for access and cost requirements.

DryvIQ founder and chief strategy officer Mark Brazeau said the move comes as organizations are increasingly looking to turn unstructured data into a “strategic asset.”

"By joining Nasuni, we can bring our content intelligence and governance capabilities directly into a cloud-native file platform, giving customers a single, governed foundation to classify, protect, and activate data wherever it lives," he commented.

DryvIQ is available immediately, with the vendor planning to deepen the integration between the two platforms over the coming months.

Financial terms of the acquisition were not disclosed.

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Salesforce and Anthropic have unveiled ‘Claudeforce’, marking a significant expansion of the existing partnership between the two firms.

The move will see deeper integration of Anthropic’s Claude AI across the breadth of the Salesforce ecosystem, spanning Data 360, Tableau, and Slack.

Notably, the two firms have been forging closer ties for some time now. The CRM giant noted that they are both “strategic customers of one another”.

Salesforce, for example, is Anthropic’s preferred CRM while Slack plays a key role in workforce communication, workflows, and agentic orchestration. On the flip side, Claude already underpins key capabilities within Slack, with users having access to various Claude-powered agents.

The Claudeforce announcement essentially reinforces this relationship and will drive deeper synergy between the two firms. Salesforce CEO Marc Benioff described the move as “fusing” Claude with the CRM giant’s data and workflows.

“We’re launching Claudeforce, running directly on top of Salesforce via our new AIforce UI harness, Headless 360, Data 360, Tableau, and Slack. Here, the UI is the AI — allowing you to build custom apps dynamically and answer any enterprise question,” he said in a blog post.

“We’re delivering a dynamic interface that thinks, reasons, and acts.”

Simply put, Claude will be woven directly into Salesforce’s various domains, and Salesforce will be woven directly within Claude. It’s the “best of both worlds”, according to Benioff.

So what can users expect?

Salesforce inside Claude

The first big talking point with Claudeforce centers around Salesforce in Claude, a plugin that comes equipped with 37 pre-built sales skills. We’ve already seen Anthropic make moves with domain-specific plugins in recent months.

Claude Cowork, which launched in January this year, came equipped with a range of industry-specific plug-ins, which as ITPro reported at the time sparked somewhat of a frenzy in the SaaS space.

According to Salesforce, because these plug-ins have deep access to customer data and business rules, they better “understand” seller revenue cycles – providing a helping hand to sales personnel.

“These skills were built by Salesforce and Anthropic, engineered specifically to draw on Claude’s reasoning, agentic tool use, and generative UI — not generic CRM prompts wrapped around an API but the capabilities that extend what Claude can do,” the company said in a blog post.

These plug-ins even have an “onboarding experience” that will see Claude analyze seller data across Salesforce and Slack to provide better context.

“No two companies run sales exactly the same, so Salesforce in Claude routes actions through Salesforce to help ensure business rules are always enforced when an action is taken. Setup is seamless,” the company claimed.

Claude inside Salesforce

This is a relationship that works both ways for Salesforce and Anthropic. Claude is already available within Agentforce, acting as the reasoning model for the company’s Atlas Reasoning Engine.

The LLM also powers Agentforce Vibes and Agentforce Coworker by default, and is available in Agent Builder.

With the extended partnership, the duo are eyeing deeper integration of Claude across the Salesforce estate. Notably, the LLM is now fully integrated within the Salesforce Trust Boundary through Amazon Bedrock.

Slack integration

Slack will play a key role in Claudeforce moving forward. The workplace collaboration platform has already been transformed into an ‘agentic OS’, and as ITPro reported last year, is a core pillar of the Agentforce 360 platform.

Claude acts as the default model for Slack, powering Slackbot and helping support users via features such as Slack Code and Claude Tag.

Claude Tag was rolled out earlier this year and replaced the existing Claude in Slack application. The tool essentially acts as a virtual teammate within Slack, allowing users to @ the agent within channels and allocate tasks.

Salesforce said that by embedding Claude directly within Slack, it’s “bridging the gap between team dialogue and autonomous enterprise action”.

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Basware has signed an agreement to acquire Trustpair, in a move that will extend its invoice lifecycle management platform into payment fraud prevention.

The acquisition will combine Basware’s invoice lifecycle management platform with Trustpair’s capabilities for validating supplier bank accounts, giving customers protection across the invoice-to-payment process.

Trustpair’s AI-driven platform is designed to verify that payment accounts belong to the intended supplier during onboarding, when account details change, and before payments are authorized.

Basware said the acquisition will allow it to extend its existing invoice fraud and duplicate-detection capabilities through to the point of payment at a time when AI continues to increase risk around supplier impersonation, compromised email accounts, and fraudulent payment instructions.

“A finance team can do everything right on the invoice and still send the money to the wrong bank account,” explained Basware CEO Jason Kurtz in an announcement. “Basware has spent more than 40 years protecting the invoice. Bringing Basware and Trustpair together extends that protection through the payment itself.

“Together, we will offer the first end-to-end invoice-to-payment assurance in the market, strengthening Financial Integrity and Continuous Compliance across the invoice lifecycle."

Founded in 2017, Trustpair provides automated account validation and risk intelligence to more than 600 organizations and operates across New York, Paris, and London.

The firm’s SOC 2 Type II and ISO 27001 certified platform can work alongside a range of ERP, procurement, and treasury systems, including SAP, Oracle, Coupa, Zycus, Ivalua, JAGGAER and Kyriba.

Following completion of the acquisition, Trustpair will continue to operate independently, with customers able to continue using its technology without changing their providers or existing systems.

Basware said Trustpair will also benefit from the ability to draw upon shared intelligence spanning 2.5 billion invoices and 20 million suppliers to strengthen its validation models and expand its market reach.

Commenting on the deal, Trustpair co-founder and CEO Baptiste Collot said access to Basware’s resources will enable the company to grow beyond what it could have achieved on its own.

"Trustpair was built around a simple belief: approving the right invoice is not enough if the money ultimately reaches the wrong account,” he said.

“By bringing our capabilities together, we see the opportunity to give finance teams stronger protection across the full journey, from supplier onboarding and invoice approval through payment.”

The proposed acquisition is the latest in a string of buys for Basware over the last three years, following its purchases of Glantus, AP Matching, and Redmap.

The deal is expected to close later in 2026, subject to customary closing conditions. Financial terms were not disclosed.

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Nvidia’s rumored acquisition of Hugging Face could raise the stakes for hyperscalers and AI vendors, according to analysts.

First reported by The Information, the $12.9 billion deal follows recent speculation over a potential sale. Business Insider reported last week that the firm was courting suitors on this front.

This isn’t Nvidia’s first encounter with Hugging Face, either. Reports from the Financial Times last year claimed the company turned down a $500 million investment offer from the chipmaker.

Hugging Face is a highly popular destination for developers and describes itself as the “home of machine learning”. The platform offers developers a hub through which they can access AI models, various datasets, and applications.

Notably, the platform has established a reputation as a key hub for open source models.

If the acquisition goes through, it would be a massive boon for Nvidia, according to Forrester VP principal analyst Charlie Dai. The chipmaker already boasts a significant lead in terms of the infrastructure layer underpinning the generative AI race.

This move, Dai said, would not only complement its broader product ecosystem but also provide inroads with boots-on-the-ground developers

“Nvidia has already built an extended ecosystem through GPUs, CUDA, networking, inference software, and AI frameworks,” he said.

“If this deal is confirmed, Hugging Face would give it a stronger position at the developer, model distribution, and community layers, which will strategically help shape where AI workloads are built and deployed.”

Long-term, Dai suggested that the Hugging Face acquisition could pose a threat to major industry players, particularly hyperscalers and AI providers.

“This raises pressure on hyperscalers, model vendors, and alternative hardware players,” he said. “Nvidia would gain a powerful developer channel and ecosystem asset.”

This could spark somewhat of an arms race in the broader AI industry. Rivals might “accelerate investments in independent model repositories and developer platforms” to counter the move and provide alternatives for customers.

Ecosystem evolution

The move by Nvidia comes amidst a sharpened focus on the open model ecosystem in recent months.

As ITPro reported last month, open AI models have become the latest flashpoint in big tech, particularly with the arrival of powerful new Chinese options.

Nvidia CEO Jensen Huang was one of a score of signatories in an open letter voicing support for open model approaches amidst speculation of a pending US ban.

With the debate over closed and open ecosystem approaches still raging, Dai said the acquisition could ultimately “strengthen the open model ecosystem”.

Hugging Face’s value on this front lies in its neutrality within the industry, he noted, and Nvidia will likely continue on that front.

“Nvidia has strong incentives to keep Hugging Face open, vibrant, and multi-vendor because broader open-model adoption drives AI innovation and overall demand for AI infrastructure, benefitting the entire ecosystem.”

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Despite talk of an AI bubble, AI spending is not slowing down. Indeed, companies plan to commit 1.7% of their annual revenue to AI initiatives this year, up from 0.8% last year, according to research from the Boston Consulting Group.

At the same time, however, PwC’s 2026 Global CEO Survey shows that a growing number of companies are not seeing a return on their investment. A survey of more than 4,400 CEOs found that 56% have yet to see a financial benefit from their AI initiatives, while just 12% have seen both an increase in revenue and a cost reduction. Only a third are confident of revenue growth this year amid struggles to optimize AI’s ROI.

The disconnect can be put down to the fact that too many companies are buying AI tools, rolling them out to employees or customers, and only wondering several months later why they haven’t seen ROI. The problem is less to do with companies not getting value out of AI and more to do with the fact that they haven’t defined what value actually means for their business.

“A common mistake is spending heavily on tools before really understanding the problem [that needs to be solved],” says Jack Rickhuss, managing director and co-founder of tech consultancy Journi.

“AI only delivers real value when it’s in the hands of people who know how to use it properly.”

Tie AI investments to clear outcomes

Benchmarking AI budgets is becoming a critical discipline that leaders need to master to ensure they’re extracting value from AI deployments. Without benchmarking an AI project’s spend, companies have no objective way of knowing if AI is performing well or poorly and delivering value for money.

Adam Hofmann, partner (AI and people transformation) at challenger consultancy Elixirr, says that the trap he sees leaders fall into is deploying AI tools and celebrating personal productivity gains while the profit and loss doesn’t move.

This can happen because companies are “benchmarking off peers that don’t know what they’re doing either, which leaves you behind the curve or overspending on someone else’s confusion.”

Before getting started on benchmarking AI budgets, leaders should build a clear picture of what they’re currently spending on model API costs, such as per token, infrastructure such as compute, hosting, and storage, human validation, maintenance, and training. Hofmann warns that “if you can't trace the line from spend to outcome, you're measuring activity, not AI."

Rickhuss agrees, adding that most companies “are still measuring the wrong things”. He advises tying AI investment to clear outcomes, such as improving decision-making, saving employees’ time, and speeding up delivery of projects. “If you can’t link [AI investment] to something tangible, it’s hard to measure success.”

Review what industry peers are doing and then pilot

To get started, leaders should compare their spend against the peers that do know what they’re doing. One way they can do this is look at other companies in their industry using their earnings calls and 10-K filings, as well as analyst reports. They could use a large language model to extract data on peers’ AI spend as a percentage of revenue.

The next step is to break down AI use cases into various categories. This would cover the infrastructure (e.g. cloud compute and GPUs), people (e.g. the salaries for AI talent), licensing (e.g. cost-per-token), and data (e.g. storage).

Once AI budgets have been broken down, Shiro Theuri, CTO of Spanish on-demand delivery company Glovo, recommends taking “a pilot-and-test approach”. This is because piloting tools in a controlled environment can help to prevent feature creep and shadow IT. Pilots can also surface hidden costs that might otherwise have been overlooked.

An IDC and DataRobot survey carried out last year showed that 92% of enterprises deploying agentic AI at scale admitted that the costs incurred were higher than they had projected. The survey of 318 senior decision-makers at companies with more than 1,000 employees found that token consumption and hallucination remediation were the top unexpected costs, while inference was another common issue.

Continue to benchmark throughout a project’s lifecycle

To prevent their AI projects from getting stuck in pilot mode, leaders should continuously monitor the cost of running the project and benchmark this against the company’s own expectations.

Monitoring token consumption can be an effective way to keep budgets under control. AI costs can quite easily skyrocket, especially if employees end up using more tokens than forecast, running up higher bills and leading to companies exceeding their AI budgets. Luke Budka, AI director at marketing and training firm Definition, adds that tracking token usage can “reveal super users and also help identify employees who need support”.

While token usage can be used as a useful metric for cost management, leaders should be careful of ‘tokenmaxxing’ – the trend of enterprises measuring individual employee token usage and using it to measure productivity. As Budka explains, high token consumption can occur when employees are purposely inflating their usage to look busy, but it can also be a sign that employees are struggling with AI tools and could benefit from more training.

Ultimately, rather than focusing on the cost-per-token, leaders should measure the cost-per-business outcome. Determining the number of tokens required and tracking the tokens consumed to complete each workflow will help to optimize AI’s ROI.

Glean has cut the ribbon on a new global partner program as the enterprise AI startup looks to expand its channel ecosystem.

Unveiled at the company’s inaugural Glean:GO Partner Summit, the Glean Partner Network brings together its existing partner pathways, expertise, and resources under a single global program.

The initiative gives partners access to training, commercial support, and go-to-market resources, providing greater flexibility in how they work with Glean and helping them grow their business around its enterprise AI platform.

The offering brings together company knowledge, people, permissions, and activity, giving AI applications and agents access to context from across an organization.

Glean said it is building on strong momentum for its channel ecosystem, which has grown to span North America, EMEA, APJ, and Latin America, while its partners have now completed more than 2,000 accreditations across sales, technical, and delivery disciplines.

“Partners are central to making enterprise AI work,” said Zubin Irani, vice president of partnerships at Glean.

“The Glean Partner Network gives partners more ways to build real businesses with Glean and gives customers a clearer path to the expertise they need. As partners build their capabilities and deliver results, we will invest alongside them.”

The new Glean Partner Network

Glean said its new partner program has been built to recognize partners for the capabilities they build, the value they create, and the results that they generate.

The Glean Partner Network includes referral, commercial, services and solutions, and technology pathways, with partners able to participate in more than one depending on their capabilities.

Partners can develop agents and custom connectors, co-sell and transact Glean technology, lead implementation and adoption, operate AI services, or develop technology extensions and customer solutions.

The program also includes self-service training and tiered ‘Boost Camps’, alongside specialist competencies across areas such as agent building, custom connectors, and embedded experiences.

Additionally, partners have access to resources such as deal registration, market development funds (MDF), co-marketing opportunities, as well as dedicated sales, technical, marketing and executive support.

Meeting partner and customer needs

Glean said its new initiative will generate opportunities for partners to expand across sales, services, technology, and solutions as their capabilities develop, with the potential to earn greater investment from the vendor as they grow and deliver customer impact.

For customers, the program aims to make it easier to find partners with the expertise required for different AI projects – including deploying Glean, building an integration or an agent, operating AI services, and creating industry-specific solutions.

Scott Blahauvietz, vice president of AI and cloud sales at AHEAD, a Glean partner, said enterprises require a practical way to apply AI across data, permissions, and workflows, rather than more AI models.

“Glean provides the permission-aware foundation to move from experimentation to adoption,” he commented. “Through the Glean Partner Network, AHEAD can pair that foundation with the implementation, governance, and enablement needed to build AI programs that are secure, scalable, and embedded in how people work.”

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New research from McKinsey suggests enterprises are finally reporting benefits from AI, but cost-related concerns and “constrained” productivity gains still weigh heavy on the minds of IT leaders.

Figures from the consultancy’s State of AI in 2026 report show more than one-third (37%) of respondents recorded “some” earnings impact with the technology, although that marks the same share from last year’s report.

Meanwhile, “AI high performers” said AI is now having a “significant” impact on operational efficiency and earnings.

The report suggests that enterprise AI maturity is rising, with an increasing number of enterprises now successfully scaling the technology. Improvements in this regard are being reported across the board, McKinsey noted, with respondents scaling chatbots, coding agents, and more sophisticated AI agents.

The use of agentic AI has increased significantly, for example, with 40% of large enterprises scaling agents, up from 27% last year. Meanwhile, around two-in-ten are actively scaling software coding agents.

“Among AI tools, chatbots are the most widely scaled, with 47 percent of respondents saying their organizations are scaling them across the enterprise,” the report states.

“About two-in-ten respondents report reaching the scaling phase across their organization with AI agents and a similar share report the same with software coding agents.”

Mismatched AI productivity

Workforce productivity gains rank among the most notable improvements for enterprises, according to McKinsey.

Around 80% of respondents said that AI has improved individual productivity, while 50% report that AI helps them “make better decisions”. Crucially, however, McKinsey warned that “the experience is not universally positive”.

Mid-level managers and individual workers are more likely than executives to report AI-related problems. McKinsey said this shows that AI impact “remains concentrated” among certain groups within the enterprise.

This is by no means the first study to highlight this trend. Research from Accenture in April this year found many enterprises are dealing with mismatched AI productivity gains.

Similar to McKinsey, the report found that workers are reporting benefits with the technology such as higher-quality output levels and faster project delivery times.

Yet the report pointed to a “widening gap” between the basic use of the technology and its wider enterprise impact. A key factor, Accenture said, lies in the fact that organizations' process changes are “lagging behind” integration rates.

Similarly, many AI strategies typically fail to modernize underlying IT infrastructure or workflows to accommodate the technology.

“A striking finding this year is the gap between individual gains and enterprise impact. At the individual level, AI is clearly a boon: 80 percent of survey respondents say it has improved their productivity and half say it helps them make better decisions,” said Dan Tinkoff, senior partner at McKinsey.

“Yet, only 37 percent of organizations report any positive EBIT contribution, essentially flat compared with last year.”

AI costs are taking the shine off enterprise gains

Cost-related concerns continue to weigh heavy on IT leaders’ minds, according to McKinsey. Around 20% of respondents said that AI-related operating costs have “constrained their AI use”.

“Those cost constraints are being reported across the full range of AI tools. For each of three tools – AI chatbots, AI agents, and software coding agents – about one-in-ten respondents say their organizations’ use has been constrained by costs,” the report states.

McKinsey also highlighted token-related cost concerns. This has become a recurring pain point for some businesses over the last year as firms ramp up adoption of the technology.

The ‘tokenmaxxing’ trend, for example, has prompted a surge in usage and landed some firms with hefty bills.

As ITPro previously reported, Accenture asked workers to stop using AI for basic tasks amidst skyrocketing costs while Uber revealed it blew through its entire annual AI budget in just four months.

Rising operational costs haven’t dampened investment rates, however. More than one-quarter (28%) of respondents said their organisation is now spending more than 10% of their total IT budget on AI tools.

“Looking ahead, 60 percent of respondents expect their organizations to increase their AI investments over the next year,” McKinsey noted.

“Respondents in pharmaceuticals and medical products, insurance, and banking and other financial institutions are the most likely to expect increasing investment.”

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Healthcare organizations collect huge amounts of data that can be used to improve operational processes and save patient lives.

However, exploiting this data is easier said than done. Healthcare professionals face multiple challenges, from stove-piped data to governance hurdles, as they look to turn information into insight.

It’s in this challenging environment that Dr Joe Zhang, CTO at OneLondon, is aiming to create a new era of interoperability. OneLondon is a specialist healthcare partnership that connects health and care information across the capital to improve patient treatments and plan future medical services – and at the heart of this approach sits the Snowflake data platform.

“The data is a lot more complicated in healthcare than [in] other settings; it's highly dimensional, it's multimodal, meaning that you have structured data, free text, but also imaging data, and genomics data,” says Zhang.

“The value of the data for improving care is enormous, but what you're dealing with on the ground is just a constellation of many siloed systems locked away and managed by different teams.”

Disparate data

Patient data in London is spread across GPs, hospitals, mental health providers, community services, and social care organizations. This data has traditionally been fragmented across disparate systems, making it difficult to create a joined-up view of patient health to predict demand or conduct population health research.

After an open procurement process that considered other data platforms, OneLondon selected Snowflake, with Zhang suggesting the provider’s capabilities meant its technology ticked more boxes than its rivals. Today, Snowflake is helping the organization solve its data interoperability challenges.

“At a local level, the platform is the layer where we can ingest data that's compliant, secure, and that we can trust,” he says. “It’s also operationally open, which means we can use our own tooling, which is standard things like SQL and Python, to transform data, ingest it, observe it, standardize it, and turn it into a usable asset for clinicians and analysts on the ground.”

Zhang, who spoke with ITPro at the recent Snowflake Summit 2026 in San Francisco, says the platform provides a data mesh-like approach, where professionals can share insights securely with others. As a doctor who used to work in the Intensive Care Unit (ICU), Zhang has first-hand experience of the life-changing impact of timely insights. Now, he’s helping professionals in other healthcare organizations to exploit their data.

“My background is as a doctor, but I've got a technical background in data engineering and data science. I left medicine after COVID. I worked in industry for a while doing biomarker development in real-world data, then came back to London to lead part of the program across London, and then stepped into the CTO role,” he says.

“This job gives me the best of both worlds. We can make a bigger impact with data, data products, and applications built on data, but it can take a bit longer to see the impact. When I worked in [the] ICU, you’d see the results within 10 minutes or so. This work involves a wider scope and longer timelines, but a potentially bigger impact.”

A data journey heading towards value recognition

OneLondon’s activity covers about 30 hospitals and more than 1,400 GP practices. Some healthcare organizations are more mature in their data journey than others. While the Snowflake platform provides a core layer for joined-up analytics efforts, the key to long-term success is ensuring that professionals recognize its value.

“It’s more of an incentivized play rather than saying, ‘This is the pattern we're going for,’” says Zhang. “The organizations that have come on to Snowflake have done so because they think the technology helps with interoperability. A lot of the work has been about unifying opinions across all the organizations in London to make this approach work.”

The key benefit for professionals is a single patient record. Whether someone spends time in GP services, local hospitals or specialist healthcare centers, Zhang says their pathway is tracked: “If you're a clinician at a point of care, you can start to build applications that say, ‘This patient, based on everything that has happened, is at more risk of renal dysfunction, so we should do something about it.’”

Work on the platform continues. The major migration process finished in April, with primary care data feeds currently coming online. At least a dozen use cases are in development. While these pioneering projects will produce benefits, Zhang says it’s important to recognize that the core focus so far has been perfecting the underlying technology layer.

“There are all sorts of infrastructure and networking challenges you must overcome before you think about integration,” he says.

“But because Snowflake offers an application layer where you can provision resources and scale compute to applications that are deployed, it becomes a highly secure solution for us to deploy all sorts of services.”

That effort is crucial, as Zhang says ambitious projects in population health or life sciences research won’t be scalable if the right data isn’t available. The long-term aim of this initiative is to create proactive care applications for clinical pathways: “The approach we choose may not work at first, but you iterate, and create a cycle where you constantly learn and improve.”

Future innovation

Another long-term objective, says Zhang, is to use the joined-up view on data to help support the development of new drugs for disease treatments. He says a key reason the UK isn't doing as well as it could in terms of developing new therapies for patients is a lack of data. The Snowflake platform could play a crucial role in supporting progress.

“We don't know what diseases are there, who is suffering from what disease, and what the trajectories are,” he says.

“So being able to map that process out, being able to run more clinical trials in this country, and getting new drugs to patients faster, would be a big outcome for me if we can help do that.”

Reflecting on progress made so far, Zhang says clear long-term objectives and a trusted technology partner are critical to success. As someone well-versed in life-changing decisions in high-pressure environments, he recognizes that digital leaders looking to push data-enabled change must walk before they can run.

“Often it's not sophisticated things like AI and agents; it's just having the right data in the right place at the right time,” he says.

“We need to be able to measure outcomes and see what's happening to our patients. Those things sound simple, but they've never really been possible before. So, in that instance, this project is all about trying to prevent preventable things.”

Enterprises are falling into a trap of using AI when it’s not necessarily needed, and it’s costing them dearly, according to Roger Lee, AVP of solutions consulting at Appian.

Speaking to ITPro, Lee said the hype surrounding AI - particularly agents - is pushing some IT leaders to apply the technology in an ‘AI for the sake of AI’ type approach.

“I think a lot of organizations and a lot of senior executives and staff within organizations have been told to ‘do AI’,” he said.

“So rather than just pushing AI for the sake of AI, look at what the decisions are we’re trying to improve, what data we are using, and where does that human oversight sit.”

Lee’s comments come after Accenture told staff to stop using AI for unnecessary tasks amid surging costs. As adoption of the technology accelerates, he told ITPro that enterprises need to have a serious conversation on how they integrate AI tools.

Agents vs business rules

Pursuing the ‘AI for the sake of AI’ approach means that many businesses aren’t just incurring huge costs, but adding needless complexity to processes that were already streamlined prior to the generative AI race.

“The key thing is really trying to identify the right place for AI versus just trying to use AI to solve everything,” he said.

“In many cases, if it’s straightforward automation, if there’s a business rule where you’ve got a definitive yes or no answer, then sometimes business rules and workflows that result in a definitive answer are the right way to go.”

Admittedly, Lee said there are instances where agents are necessary, especially with regard to research or complex problem solving tasks. Acknowledging that this is a case of different strokes is crucial, however.

“I take an example from insurance with an automation claim, where you wanted to do some research and do some work, then an AI agent might be the right solution for that,” he said.

“But it's really understanding the right place to use a rule versus an AI agent, and the impact that that can give.”

This is particularly relevant in regulated industries, Lee said, where margins of error can have huge ramifications.

Agents are highly effective in terms of dynamic reasoning, he noted, but in cases where businesses need a “really definitive zero error response” then IT leaders need to know where and when to automate.

“Regulated industries is another area where humans in the loop are really important,” he said.

“It's what makes processes accountable. So to ensure that not everything is automated, where you have things that are exceptions or outliers, that you absolutely have humans in the loop to respond to those.”

Shoehorning AI into processes

Enterprises have found themselves shoehorning AI into areas and processes that aren’t applicable, research from Gartner shows. Moreover, they’re expecting near-immediate returns with the technology.

Ironically, a key factor behind this lies in the desire to deliver returns on investment with AI. Yet by doing so they’re less likely to unlock any benefits.

Speaking at the time, Melanie Freeze, director of research at Gartner, said that many AI initiatives are “overly ambitious or poorly scoped” and don’t align with “real operational needs”.

Ultimately, Lee told ITPro that as with any adoption process, AI should still be viewed as a “business pull rather than technology push” approach.

“I think that the whole value that you can get from AI within an organization is all around what the business needs, rather than what the technology can push to the organisation,” he said.

“First and foremost, what problems are we trying to solve, rather than where can we use AI, and that changes the perspective on what we're trying to do,” Lee added.

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The government has outlined proposals for new powers under the Cyber Security and Resilience Bill aimed at boosting cyber defences for the UK's essential services.

With hostile cyber attacks and sabotage on essential services like energy, water, transport, and healthcare on the rise globally, vendors and companies with connections to hostile states pose a 'growing and serious' threat to the UK’s security.

The idea is for the government to be able to step in when essential service providers are looking to buy equipment or technology from suppliers that could pose a critical national security risk.

"These new powers mean we can act before a threat materializes, not just after the damage is done. By working together with industry, we're putting national security at the heart of how essential services choose their suppliers," said cyber security minister Liz Lloyd.

"This is about staying ahead of a growing threat, and giving the public confidence that the everyday services we depend on like water and energy supplies, our transport network and hospitals, are protected."

New cyber safe procurement guidance would be made available for all essential service providers to help them secure their supply chains. Providers will be able to refer themselves for a risk assessment if they're unsure about a vendor – and be given advice on how to mitigate any risks.

Meanwhile, the package would grant the government new legal powers to issue binding directions to essential service providers, including requiring extra security measures, a phased withdrawal, or in the most serious cases, an outright ban on acquiring a vendor or supplier's products or services.

Growing state-backed threats

The proposals come amidst growing concerns over the impact of state-sponsored cybersecurity threats.

Earlier this year, the National Cyber Security Centre (NCSC) warned that the UK is experiencing increased threats from Iranian-backed cyber groups, with a heightened risk of indirect threats for organizations with a presence, or supply chains, in the Middle East.

Government figures indicate that an outage caused by a cyber attack on London and Southeast England's electricity networks could potentially cost the economy up to £442 billion over the following five years.

Just this week, the vulnerability of key UK infrastructure was brought into focus by the news that Iranian-linked hackers were been able to knock a small power plant offline for four days.

The attack, which targeted internet-exposed programmable logic controllers (PLCs), is believed to be the first of its kind in the UK.

The amendments to the bill were laid before Parliament on Monday, ahead of Lords Committee stage scrutiny, which is set to begin in September.

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Freeths has announced the appointment of John Jones as its new chief technology officer (CTO), in a move the law firm said will strengthen its leadership bench and growth ambitions.

Jones will work across Freeths’ twelve offices located across the UK and will oversee the shaping and delivery of its technology strategy.

His remit will include ensuring the business has secure, resilient, and future-ready technology platforms that support employees, improve the client experience, and enable operational efficiency.

In an announcement, Freeths national managing partner Karl Jansen said the appointment comes at an “important point” in the company’s ongoing growth and development.

“Technology is central to how we support our people, serve our clients and operate as a modern law firm,” he commented.

“John’s depth of experience, combined with his pragmatic and inclusive leadership style, will be instrumental as we continue to build scalable, resilient and innovative technology foundations across the firm.”

Headquartered in Nottingham, Freeths is a UK commercial law firm serving private and public sector clients, including organizations such as Centrica, Aldi, Mercedes-Benz UK, Tarmac, Experian, and Harworth.

Jones joins the business with more than 30 years’ experience across technology and professional services. Most recently, he served as CTO at Forvis Mazars and previously held senior tech roles at BDO.

He began his career as a software developer working on business-critical applications before moving into senior technology leadership positions within the professional services sector.

Jones’ experience includes working with enterprise platforms such as Microsoft, Workday, and legal-specific technologies, while his expertise spans data, digital skills, large-scale transformation programs, as well as the safe and effective use of emerging technologies such as AI.

Commenting on his new role, Jones said he was impressed by Freeths’ existing technology platforms, as well as the clarity of its plans for the future.

“Professional services, and the legal sector in particular, is going through significant change, and technology has a vital role to play in enabling better outcomes for clients and colleagues,” he explained.

“I’m excited to be joining Freeths and to be working closely with teams across the business to support the next stage of the firm’s journey.”

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For years, channel partners have made their margins on cloud migration and security, helping clients move data somewhere safe and keep it that way. Both have become the default, but solving that problem has quietly created a new one: data that is safe and well governed is not the same as data people can actually use.

Backend systems have grown more sophisticated while the interfaces sitting on top of them have stayed clunky, fragmented, and largely ignored, leaving valuable information locked away from the people who need it most, and this is where the value has now shifted.

Relying on cloud migration and baseline security as a primary revenue engine will leave channel partners behind because providers continue to sell infrastructure solutions to an enterprise market that has already moved past the infrastructure phase.

Storage and security handle yesterday's issues, while data silos resulting in data fragmentation are now the urgent challenges of today. Data silos trap critical information within isolated, non-communicating systems, scattering corporate data unevenly across public clouds and legacy applications. This inevitably leads to data fragmentation: a chaotic state in which corporate data is unevenly distributed across multiple public clouds, legacy systems, and disconnected applications.

The consequences of this fragmentation are crippling, leaving organizations without a single source of truth. In fact, 77% of respondents in an IBM Institute for Business Value study strongly agreed that these silos actively hinder real-time analytics and data-driven decisions.

For the past decade, managed service providers (MSPs), value-added resellers (VARs), and IT consultants have built highly profitable practices by guiding organizations through cloud infrastructure modernisation. But today, the next margin growth opportunity isn’t where data is stored; it is how that data is experienced: a shift known as the Digital Experience Platform (DXP) space, which helps organizations unify, govern, and present fragmented backend data into usable, front-end interfaces.

The multi-million dollar data disconnect

Organizations continue to pour substantial capital into upgrading their cloud infrastructure. An Omdia survey shows how spending reached US$110.9 billion in late 2025, a 29% year-on-year surge, with another 27% growth forecast through 2026 on global cloud infrastructure. However, a massive operational problem persists: the data sits perfectly organized in the backend but remains functionally inaccessible to the end user.

Simply owning data is no longer a competitive advantage; the real value is in how easily people can use it. This structural gap between backend complexity and front-end utility defines the "Data Experience" gap.

For a business-to-business (B2B) buyer, this gap looks like a frustrating customer portal that cannot display real-time shipping updates because the shipping database does not talk to the web interface. For a supplier, it means relying on manual emails because procurement platforms do not share information.

Transitioning to data experience architecture

To capture higher profit margins in this landscape, channel partners must transition from storage infrastructure providers into data experience builders.

This evolution requires moving away from traditional, slow, and expensive data migration methods, such as moving information into the cloud, and instead focuses on building smart, lightweight integration layers. By seamlessly connecting legacy systems to modern cloud environments, partners can consolidate fragmented data into a single, cohesive view without disrupting the underlying storage architecture.

This ability to deliver integration without interruption represents a highly specialized skill set for which corporate clients are willing to pay a premium.

Beyond merely connecting these disparate systems, opening the flow of data introduces an urgent need for smart permissions and sophisticated governance.

A distributor, a B2B customer, and an internal sales representative may all require access to information stored in the same database, yet what actually appears on their respective screens must be uniquely tailored.

Designing and implementing these complex, context-aware access control systems serves as a high-value advisory service. It establishes a level of security and compliance that basic software resellers simply cannot replicate, deeply embedding the partner into the client's day-to-day operations.

Ultimately, these seamless backend connections enable the delivery of consumer-style B2B experiences that modern buyers now expect as standard. Digital experience insights tracked by platform providers indicate that the primary hurdle for B2B companies isn't designing an attractive user interface; rather, it is untangling the complex web of integrations sitting right beneath the surface.

Channel partners who can bridge this gap by building tailored vendor portals and collaborative digital workspaces resolve their clients' most critical technical friction points, effectively making themselves indispensable business allies.

The high-margin advisory model

When a partner fixes an organization's data experience, they are doing far more than installing software. They are mapping out how the business actually runs, improving daily operations, and building resilient integration systems.

This results in higher client retention, robust profit protection, and a steady stream of recurring revenue as the client’s digital needs continue to scale.

Architecting these solutions requires a technology foundation designed specifically for backend complexity. Platforms that act as a unified hub connecting content, workflows, and backend systems to deliver personalized experiences are built for this transition, offering an evolvable architecture that allows partners to bridge the data experience gap across the entire business ecosystem.

By building security and context-aware compliance directly into the core of the integration layer, partners can safely deliver highly localised, consumer-grade experiences across diverse global markets. Furthermore, utilizing integrated AI and scalable SaaS or PaaS environments ensures that as client traffic and campaign demands fluctuate, the underlying data layer remains resilient.

The foundational infrastructure of the modern enterprise has already been laid. The channel partners who will win over the next decade will be those who don’t focus solely on storage boxes, but instead upskill their teams in integration governance and start unlocking the value of the data inside them.

The market has moved past the plumbing phase to build data experience, and channel partners need to move with it.

Poorly implemented IT strategies have a significant impact on businesses. From lackluster growth and financial losses to employee change fatigue, the risks are huge.

With enterprises ramping up AI adoption, many are failing to learn the lessons from previous change programs and are diving headlong into projects.

On this week's episode of the ITPro Podcast, Jane and Ross speak with Al Kingsley MBE, CEO of NetSupport, to explore how IT leaders can implement change, lead by example, and deliver successful transformation projects.

Highlights

“First and foremost, we need to make sure that we're not just making changes because, hey, we've just seen online that everyone's using AI now, so hey, we'll go that way. As opposed to, well, what are we trying to mitigate here? Is it about productivity and output? You know, and the data bit is, well, if we don't know how to robustly interrogate our data, and a bit like those who remember Donald Rumsfeld from the U.S. government, it's not the known knowns or the known unknowns; it's the unknown unknowns. You don't have the right questions to ask, you're not going to get the right answers, and the data is not going to help inform your decision-making.”

“We're seeing more and more agentic AI, AI that's running in parallel and running tasks, being adopted in organizations at pace. But the other thing to balance all that yin and yang with, I think, is the more we're adopting at-pace technology in our organization, it is increasing the value of the human bit. Whether it's the customer service, the engagement with people, the way we think differently, the way we're more creative, and so the real irony is that AI and digital are also amplifying the value of our most human aspects and skills too.”

Links

• Enterprises just can't seem to shake legacy tech – and it’s seriously hampering digital transformation goals
• AI was meant to simplify IT service management – new research shows it's creating bigger workloads for teams

Exclaimer has announced the launch of MSP Connect, a new partner program designed to help managed service providers (MSPs) provision, manage, and scale email signature services across customer environments.

Available immediately, the initiative brings consumption-based billing, centralized self-service provisioning, and dedicated channel support together with integrations for ConnectWise, Kaseya, and Microsoft Marketplace.

Exclaimer said the program has been designed to address the operational challenges MSPs face when managing email signatures across Microsoft 365 and Google Workspace environments, where updates can otherwise require manual, user-by-user administration.

With MSP Connect, billing adjusts according to actual customer usage, allowing MSPs’ costs to increase or decrease as customers add or remove users.

MSPs will also have access to a redesigned partner portal that allows them to provision and manage signatures across multiple customer environments from a single location, while native integrations with PSA platforms aim to reduce administrative work.

In an announcement, Exclaimer chief operating officer Jim Turner said MSP Connect was developed in response to feedback from partners around the ease of use and billing model of the program’s predecessor.

"MSPs have been clear about what they need from us: a platform that is easy to provision at scale, a commercial model that flexes with their customers and commercial support that helps them grow," he explained.

“MSP Connect is the reset. It removes unnecessary steps, gives partners more control through self-service, and aligns billing with what their customers use."

Strengthening MSP revenue generation

Exclaimer’s MSP Connect launch marks the next phase of its channel-first growth strategy as the email signature management specialist looks to strengthen its partner network.

Partners already account for 30% of the firm’s annual recurring revenue, while its global channel ecosystem includes around 5,000 partners.

The company said MSP Connect will now enable partners to add email signature management to existing Microsoft 365 and managed services relationships without introducing a complex deployment or support burden.

MSPs can generate license margin, bundle Exclaimer’s technology into wider managed services packages, as well as create additional revenue through services such as signature design, deployment, and ongoing management.

"An MSP is a business within a business. It needs to manage hundreds of customer environments without adding operational drag," commented Louise Taylor, vice president of channel at Exclaimer. "If getting one customer live requires a long sales process or a services project, the economics stop working."

Reducing friction for MSPs

Exclaimer’s new program includes not-for-resale (NFR) licensing, dedicated channel account management, as well as co-brandable partner enablement materials.

The vendor said its platform can be deployed by MSPs in under an hour depending on the customer environment, using directory data to populate approved signature attributes across Microsoft 365 and Google Workspace without requiring any heavy integration project or mandatory professional services.

Additionally, MSPs can build additional services around the platform, including signature template design and template catalogue creation, while their customers’ marketing teams can utilize approved campaign banners, engagement analytics, and rule-based signature content.

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Colt Data Centre Services (Colt DCS) has announced the appointment of Quy Nguyen as chief executive officer (CEO), effective immediately.

Nguyen steps into the role having served as acting CEO since April 2026, following the retirement of Niclas Sanfridsson.

Since first joining Colt DCS in 2016, he has held a number of senior leadership positions across sales and marketing, customer experience, design, and delivery business functions.

In his most recent role as chief sales officer (CSO), he played a key role in strengthening the firm’s commercial strategy and customer relationships.

Prior to joining the business, Nguyen also served in senior leadership roles spanning finance, strategy, and general management, where he built experience in scaling businesses and delivering growth.

As CEO, he will now lead Colt DCS through its next phase of expansion, as it looks to scale its global platform and support customers’ growing digital infrastructure requirements.

In an announcement, Colt DCS chairman Tim Cohen said Nguyen’s “exceptional leadership” has been a key factor in the company’s significant recent growth and transformation.

“His deep understanding of our customers, our people, and our business, combined with his strategic vision and proven track record of execution, made him the outstanding choice to lead the company,” he commented.

“As demand for digital infrastructure continues to accelerate globally, we are confident that Quy will build upon our strong foundations and position Colt DCS for continued long-term success."

Colt DCS operates 15 data centers globally, with a further 12 sites under development across nine cities in the UK, Europe, and the APAC region.

With nearly 800MW of capacity under development across its key markets, the company said it is well-positioned to support the growing demand for digital infrastructure that is being driven by continued cloud adoption and the rapid expansion of AI workloads across Europe and Asia.

"I am honoured to be appointed CEO of Colt DCS at such an exciting time for our company and industry,” Nguyen commented. "We have built a strong track record for delivering world-class digital infrastructure, fostering trusted customer relationships, and executing ambitious growth plans across key markets.”

Nguyen said Colt DCS will support customers’ evolving needs through continued investment, operational excellence, and innovation, as demand for sustainable cloud and AI infrastructure continues to grow.

“I look forward to working alongside our talented teams around the world to build on our strong foundations, expand our global platform, and deliver long-term value for our customers, partners, and stakeholders," he added.

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For years, much of the relationship was anchored by the renewal itself. Customers turned to partners for help making sense of license positions and vendor terms, and the transaction carried enough margin to support the account work around it.

With Gartner expecting worldwide IT spending to reach $6.31 trillion this year, driven by software and AI infrastructure, the market is still growing around partners. The difficulty is that growth no longer flows through the channel in the same way.

A license can still open the account. Its value now depends on whether the partner can use that moment to extend their services to support the broader software estate.

Buying is moving around the reseller

A large part of the traditional reseller model grew around Microsoft licensing and the incentives attached to it. Backend fees historically gave partners dependable income around the customer relationship, often through repeatable work across accounts.

As those economics have narrowed, customers have gained more ways to buy technology. A reseller may spend months shaping the right solution, then see the purchase move through a marketplace because the customer wants to draw down an existing cloud commitment. The advice remains valuable, even when the transaction lands somewhere else.

Months of account work can suddenly become detached from the order. Understanding how the customer intends to buy has become just as important as understanding what they intend to buy.

A renewal now sits on top of a software estate that may have moved faster than the agreement in front of the customer. SaaS spreads through different parts of the business before central teams have a full grip on ownership. Cloud costs shift the economics of tools that once looked predictable. On top of this, AI capabilities are arriving inside the platforms customers use every day.

By the time the renewal comes around, the agreement today may not show enough about whether spend still accurately reflects how the business operates.

The license should open a wide view of the estate

To protect the relationship, partners need to turn the renewal into a clearer view of the estate behind it.

The license position shows what the customer is entitled to use. Usage data shows whether the business still depends on it. The gap between those two things often reveals important opportunities for optimization, cost control, and better decision-making.

Partners with Software Asset Management (SAM) and IT Asset Management (ITAM) expertise already have much of that capability. They understand how quickly entitlement can drift away from real use, especially when software is purchased centrally and then adopted unevenly across the organization. Turning that knowledge into a managed service gives customers a clearer view before the renewal deadline forces a decision.

SaaS management builds naturally from there. Applications can spread through teams long before central IT has a clean view of ownership or spend. A partner that can show which tools are active and which contracts no longer reflect use is helping the customer make a better renewal decision.

AI adds the same pressure in a newer form. Capabilities are being added into platforms customers already run, so the cost can build inside familiar contracts before the business has worked out where the value sits. Connecting that spend back to usage gives partners a stronger role than simply helping the customer process the next agreement.

Our 2026 State of the Cloud report findings suggest the services market is already moving this way, with nearly half of Managed Service Providers (MSPs) planning to offer AI consulting and SaaS management services. Enterprise use of MSPs has also risen year on year, which points to larger organizations looking for specialist help as their estates become harder to manage.

Margin must come from the services around the license

Partners that stay closest to the customer will be the ones that make the estate clearer between renewals. The license gives them a route into that work, then the service relationship has to carry it forward.

Account teams need enough visibility into usage and consumption to challenge assumptions before procurement turns the renewal into a price negotiation. Sales teams also need to be measured on the service opportunities created around the license, not only on the order itself.

Resale remains a key part of the channel, and the license still opens the door. More of the margin now comes from helping customers understand the full technology estate behind it. Understanding what they own, what they use, where costs are increasing, and where technology investments are delivering value.

In that environment, the most successful partners will be defined by the insight they provide and the outcomes they help customers achieve.

Fortinet has announced the acquisition of Virtue AI, an AI security specialist that provides runtime protection, automated validation, and security for autonomous AI systems.

The move will see Virtue AI’s capabilities added to Fortinet’s existing AI security portfolio, which includes FortiGate Hyperscale Firewall and FortiAIGate.

The cybersecurity giant said the deal will strengthen its ability to protect AI models, applications, and agentic systems across the AI lifecycle, from development through to runtime.

Founded in 2024, Virtue AI’s platform includes automated red-teaming of autonomous AI agents, agent protection and governance, continuous AI validation, and real-time security guardrails across text, images, video, audio, and AI-generated code.

Virtue AI's Guardian Agent technology provides visibility into AI agents and tools running within an environment, while also scanning Model Context Protocol (MCP) tools and source code for hidden security risks and monitoring agent behavior.

The San Francisco-based company’s automated validation capabilities are designed to identify new risks across model updates and policy fine-tuning, with testing covering hundreds of attack vectors and more than 1,000 risk categories.

Virtue AI’s red-teaming capabilities test autonomous agents across more than 50 sandboxed environments and 14 high-stakes domains, including simulated prompt injection and MCP-based attacks against leading agent frameworks.

Expanding protection across the AI lifecycle

Fortinet’s latest acquisition comes at a time when organizations are deploying more AI applications and autonomous agents, expanding the attack surface to include prompts, models, agents, MCP tools, APIs, and AI infrastructure.

According to Gartner, the market for securing AI ecosystems and AI agents is expected to grow from $2.8 billion in 2026 to $16.4 billion by 2030 – an expansion that Fortinet believes reflects growing demand for security technologies as AI adoption continues.

Earlier this year, the vendor introduced FortiAIGate in a bid to protect large language models (LLMs) from risks such as prompt injections, data leakage, model poisoning, and excessive resource consumption.

With the addition of Virtue AI, Fortinet said it is gaining technology that complements FortiAIGate by extending protection to AI models, applications, and agentic systems, while adding automated validation and real-time protection.

Commenting on the acquisition, Fortinet founder, chairman, and CEO Ken Xie said Virtue AI’s capabilities strengthen the company’s goal of providing continuous security for enterprise AI systems.

“AI is fundamentally changing enterprise computing, and security must evolve just as quickly,” he explained. “Virtue AI’s technology will advance our vision for continuous AI assurance, helping customers govern and protect AI systems throughout their lifecycle while operating them confidently at enterprise scale.”

Financial terms of the acquisition were not disclosed but Fortinet said the amount paid as consideration is “immaterial” to its business.

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HM Revenue & Customs (HMRC) has announced a deal with Atos aimed at driving IT modernization with low-code solutions.

The three-year deal, worth more than £78 million, will see Atos act as lead partner for Low-Code Leadership and Configuration Services within the Digital and Legacy Application Services (DALAS) framework.

In a statement announcing the move, Atos said it will provide “technical and delivery governance and assurance across the entirety of HMRC’s low-code ecosystem”.

This includes supporting the tax office’s IT modernization efforts and improving digital services for workers, businesses, and citizens across the UK.

“We’re proud to be expanding our long-standing relationship with HMRC through this appointment,” said Michael Herron, Head of Atos UK&I.

“Our proven technical expertise and experience in public sector transformation makes Atos well-placed to support HMRC as it looks to deliver better digital experiences for citizens at pace.”

HMRC targets low-code gains

Low-code tools allow businesses to accelerate transformation efforts by simplifying application development and removing manual programming.

According to Atos, the deal with HMRC will allow the tax office to ramp up legacy IT modernization and deliver “faster time to value” and cost savings.

The new contract builds on long-standing ties between Atos and HMRC. The tax office awarded a multi-year contract to the firm in 2022 to provide application testing services, for example.

It also represents the latest in a string of modernization-related announcements by HMRC in recent months. As ITPro reported in June, HMRC signed a deal with Capgemini, NiCE, and Route 101 to overhaul customer service operations with cloud native and AI tools.

The contract will see legacy infrastructure and existing products consolidated within a unified cloud native platform, with development led by Capgemini.

That deal came hot on the heels of a £175 million contract with Quantexa to overhaul its core data infrastructure.

Low-code tools still alive and kicking

Low-code platforms have been a staple in enterprise digital transformation programs for more than a decade.

Despite the advent of generative AI and an influx of AI coding tools in recent years, research shows low-code and no-code solutions are still going strong.

Research from App Builder in April 2025 found these tools still play a key role in enterprise digital transformation efforts worldwide.

Around 95% of companies revealed they still use low-code tools in software development. Notably, more than three-quarters (76%) said AI is helping make existing tools more efficient.

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Rackspace has announced the appointment of Chetan Gupta as chief AI officer, as the enterprise infrastructure specialist looks to advance its enterprise and sovereign AI strategy.

Gupta will lead Rackspace’s Office of AI, overseeing AI strategy, research, innovation, governance, and adoption across the company and its customers.

He joins the business following almost a decade at Hitachi, where he served in a number of senior AI leadership roles – including general manager of the Advanced AI Center in Japan, vice president of the Industrial AI Lab in North America, and head of Hitachi’s Global AI Center of Excellence.

Earlier in his career, Gupta also spent seven years at HP Labs, where he worked on deploying AI solutions across areas such as logistics, manufacturing, energy, and mobility. He has also authored nearly 300 papers and patents, as well as mentored AI researchers and engineers.

In an announcement, Rackspace CEO Gajen Kandiah said Gupta’s experience developing AI systems for critical environments will be a valuable asset as the firm advances its AI strategy.

"Chetan has spent his career building AI for the institutions the world depends on,” he explained. “At Hitachi, that meant trains, grids, and factories, where AI is not a demo, but an operating commitment measured in uptime, safety, and trust."

Kandiah said that experience will be particularly relevant as Rackspace customers move AI into production within regulated and sovereign environments.

"Chetan understands that success depends on more than model capability,” he added. “It requires strategy, governance, and an operator who carries accountability from silicon to outcomes.”

Rackspace eyes sovereign AI gains

Rackspace positions itself as an operator of the full enterprise AI stack, spanning governed private cloud through to AI inference and agents in production.

Its offering is built around an "Outcomes as a Service" model covering infrastructure, data foundations, and forward-deployed engineering.

The company said Gupta’s appointment will strengthen its ability to help organizations deploy AI safely, economically, and at scale – particularly across regulated industries, sovereign jurisdictions, and mission-critical operations.

Commenting on his new role, Gupta said AI has reached “an inflection point” as organizations shift their focus away from the technology’s capabilities and towards tackling deployment challenges.

“The hard problem is no longer capability. It is trust: taking promising research and turning it into systems that hold up in the real world, under real regulatory and operational constraints," he explained.

"Rackspace occupies a distinct position in the market, operating the full stack for institutions that cannot afford to get AI wrong. I look forward to leading our AI strategy and advancing enterprise and sovereign AI for our customers and across the business."

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Organizations are mostly seeing a return on their AI investment, new research shows, but many are struggling to translate business context into AI systems and workflows.

Eight-in-ten IT leaders globally expect AI spending to increase over the next two years, according to Alteryx's 2026 IT Leader Research: The State of AI Ownership, Agents, and ROI report.

While 77% agree business context - the rules, definitions, and operational knowledge that shape how their organizations operate - is critical to producing accurate and relevant AI outputs, 53% say they struggle to incorporate this within AI systems and workflows.

The result here is that AI models are forced to make generic assumptions that could lead to mistakes, false insights, or incorrect metrics – and that has a big impact on business efficiency.

More than a third of respondents told researchers that the ability to measure AI ROI will be one of the capabilities that most distinguishes technology leaders from their peers.

Notably, firms are increasingly measuring AI success through productivity improvements (53%), cost reduction (45%), and revenue growth or broader business impact (39%).

“Our research highlights a growing gap between AI ambition and enterprise-scale execution,” said Andy MacMillan, CEO of Alteryx.

"Organizations have proven they're willing to invest in AI, and many are already seeing returns. But scaling AI requires more than better models. It requires making the business knowledge people use every day available to the systems making decisions.”

Lacking context

While AI can analyze information and generate responses, it can't consistently apply company-specific rules, policies, thresholds, and decision criteria unless that knowledge is built into the workflows it uses to make decisions.

Part of the problem is limited data access, Alteryx found, with only 18% of organizations reporting that business users have fully self-service access to cloud data.

Indeed, most are still relying on IT or data teams for routine data access and analytics, with 38% describing a mixed model and 15% saying business users remain largely dependent on technical teams.

Two-thirds of technology leaders say AI and agent-based systems are most productive when managed within the line of business, with 71% saying that AI initiatives are most successful when IT and business teams collaborate closely.

However, strategy (37%) and delivery (38%) remain concentrated within IT, while business teams are most often responsible for defining requirements (30%).

"The organizations creating lasting value from AI will be the ones that operationalize their business logic so it becomes visible, governed, repeatable, and ready for AI," said MacMillan.

What’s driving AI ROI?

The AI investments that appear to be delivering the best ROI are workflow automation and autonomous agents, cited by 27%, followed by copilots or assistants, at 16%, and AI-powered customer experience at 14%.

Virtually all IT leaders (93%) told Alteryx they were confident agentic AI could deliver measurable ROI for their enterprise within the next two years.

The first processes to be automated by agentic AI, they reckon, will be IT operations and incident management, cited by 47%, followed by customer support and service workflows at 39% and data analysis and reporting at 36%.

"Within our research, a small group of organizations self-identified as leading the way in AI innovation, confirming a clear path to achieving meaningful business value with AI technologies," the researchers concluded.

"These organizations point to a clear set of priorities behind their progress: rigorous measurement of AI's business impact, treating AI rollout as a strategic and operational priority, and building the governance and literacy needed to scale with confidence."

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Dynatrace has agreed to acquire observability specialist Arize for $915 million, as the vendor looks to expand its capabilities across the AI development lifecycle.

The deal will bring together Arize’s AI evaluation technology with Dynatrace’s production monitoring capabilities, enabling customers to evaluate, operate, and continuously improve AI applications.

AI observability has become increasingly important as businesses move AI applications into production, connecting model and agent behaviour with application performance, GPU utilization, infrastructure health, and business processes.

Following closure of the acquisition, Dynatrace said customers will gain continuous coverage across the AI lifecycle, spanning experimentation and deployment readiness, through to runtime evaluation and observability.

The combined offering will also provide context of AI behavior and business impact, as well as an enterprise data foundation for AI workloads powered by exabyte-scale analysis and AI lakehouse capabilities.

The acquisition is expected to close later this quarter or early in Dynatrace’s third quarter, subject to regulatory review and customary closing conditions.

In an announcement, Dynatrace CEO Rick McConnell described the AI observability market opportunity as “enormous” with the category projected to exceed $10 billion by 2030.

“Acquiring Arize advances our AI observability leadership, accelerates our roadmap, enhances our long-term growth profile, expands our reach with the developer community, and adds an incredible AI-first team to Dynatrace,” he said.

Combining AI evaluation and observability

Founded in 2020, Arize provides AI observability and LLM evaluation technology designed to help development teams identify issues with AI applications, assess output quality, and monitor AI behavior.

The firm's platform is used across AI frameworks and model providers, with Dynatrace highlighting its open source community and developer-focused presence as part of the rationale for the acquisition.

The vendor said Arize’s addition will address fragmentation in the way AI applications are developed and operated, with AI engineering teams often using one set of tools to evaluate model and agent behavior, while another is used to monitor the applications and infrastructure beneath them.

Instead, the combined platform intends to connect AI evaluation and production observability to give developers and engineering teams greater visibility into issues across the AI application stack.

For developers, the deal also aims to provide a clear path from AI experimentation through to enterprise deployment, backed by Dynatrace’s existing production monitoring and observability capabilities.

Leadership continuity

Post-acquisition, Arize CEO and co-founder Jason Lopatecki, and fellow co-founder Aparna Dhinakaran, will both join Dynatrace. Lopatecki will continue leading the Arize team, reporting to McConnell.

Commenting on the acquisition, Lopatecki said the move will strengthen Arize’s focus on helping AI teams assess whether their agents are working correctly rather than simply running.

“Together, we can bring AI evaluation and software observability into an end-to-end system, enabling teams to build more ambitious AI applications faster,” he explained.

“This is the kind of innovation that only happens when two companies with highly complementary solutions and go-to-market models come together, setting a new bar for what AI Observability can deliver for the entire industry.”

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UK small businesses have an increasingly optimistic outlook on the potential of AI tools, new research suggests, but bold leadership will be required to ensure successful deployment.

A study published by Dell Technologies shows two-thirds (66%) of UK SMBs now view AI as a “route to growth”. More than half (56%), meanwhile, told the firm that AI could give their business a competitive advantage moving forward.

This optimism is driving investment, the research found, with funding primarily aimed at unlocking productivity gains, improving customer experience, and improving decision making.

Brian Horsburgh, UK small business country manager at Dell Technologies, told ITPro the study shows AI is having a marked positive impact for SMBs, particularly in terms of allowing workers to sharpen their focus on specific tasks.

“One of the realities of working in a small business is that everyone wears multiple hats. Many people find themselves spending hours on admin, reporting, marketing or customer queries, even though those aren't the things that inspired them to start or join the business,” he told ITPro.

“AI can help take some of that work off their plate, giving them more time to focus on customers, creativity, and growth.”

Pulling ahead of the pack

According to Dell Technologies, a small group of “AI front runners” has emerged among UK small businesses.

Representing around 7% of the firms surveyed, these report the strongest gains from using AI, allowing them to free up six or more hours each week with the technology.

Horsburgh told ITPro that a recurring theme with these front runners is having a clear cut strategy and not rushing headlong into adoption for the sake of it.

Indeed, these companies are more likely to have dedicated leaders championing AI than their slower-moving competitors.

More than half (52%) have “clearly defined specific AI use cases”, the study found, often starting with small examples before moving to more complex use cases as they mature.

“Having the right strategy is critical. Our research shows that those who are gaining the most from AI today say that AI use is coming from leadership as a priority,” Horsburgh said.

“Adopting AI means identifying ways it can help you do more of what helps your business grow and in fact, the number one piece of advice that came through from businesses of all sizes is to start small and iterate.”

Horsburgh said the findings highlight the need for dynamic, open-minded leadership when it comes to AI adoption. Initial use cases are key, he noted, but employee training and cultivating an “AI-friendly culture” are equally important.

“Those three pieces are critical to building a culture that drives benefits,” he told ITPro. “The outcomes that SMBs are seeing are positive for staff: more time to think strategically, improving decision making, improving customer experience, and having the right environment can help teams see those benefits sooner.”

The SMB agility dynamic

Dell Technologies’ study emphasized that small businesses have an inherent advantage over larger organizations when it comes to adoption.

First and foremost, they’re typically more agile and flexible with how they approach the technology – and the report noted that is now translating into higher rates of success.

This advantage isn’t lost on large businesses, either, Dell Technologies found. Nearly two-thirds (61%) of larger firms said greater flexibility is a key advantage for SMBs. Similarly, they have “more focused business needs” and are less risk averse.

SMBs also recognize these advantages, according to Dell Technologies, and are less likely than their larger counterparts to cite key barriers, such as lengthy approval processes, employee resistance to change, or fear of failure.

“Smaller businesses can have an advantage because they're often more flexible and can move faster than larger businesses, so starting with one or two key opportunities can potentially have an outsized impact.” Horsburgh told ITPro.

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Tricentis has announced the appointment of Erika Dean as chief information security officer (CISO), as the software quality specialist moves to strengthen its enterprise and product security capabilities.

Dean is tasked with leading Tricentis’ global security strategy, with responsibility for enterprise cybersecurity, compliance, and product security.

A seasoned industry veteran, she joins the company with more than two decades of cybersecurity leadership experience across the financial services and technology sectors. Previously, she built and led security programs at Robinhood and Capital One.

As CISO, Dean will work across the business to develop its enterprise and product security programs, with a focus on strengthening software supply chain security, as well as cyber resilience and governance across its portfolio.

Her remit also includes supporting the Tricentis Agentic Quality Engineering Platform as AI becomes increasingly embedded in the software development lifecycle.

“Cybersecurity is foundational to the trust our customers place in Tricentis,” said Tricentis CEO Kevin Thompson in an announcement. “Erika's expertise in building enterprise security programs and her customer-centric approach make her the ideal leader to drive Tricentis’ continued efforts to deliver innovative software quality solutions that enable customers to move faster without compromising security or governance.”

Dean’s appointment comes as businesses face increasingly sophisticated cyber threats and greater scrutiny around AI adoption, software supply chains, and the protection of sensitive data.

Tricentis eyes resilience gains

Austin-headquartered Tricentis develops software quality and testing technology designed to help enterprises automate and accelerate software development and release processes.

Its Agentic Quality Engineering Platform uses AI to automate software quality processes across enterprise application environments.

Tricentis said its latest leadership appointment reinforces its ongoing efforts to maintain a robust security program while helping customers deliver software securely.

Commenting on her new role, Dean said the growing use of AI in software development is changing the role security teams must play in protecting both businesses and their customers.

“As AI continues to transform the way software is built, security must extend beyond protecting our own organization to earning our customers’ trust in the software running in their critical environments,” she explained.

“Tricentis sits at a critical point in the software development lifecycle, where quality, security and governance all work together.

“I’m excited to build on the company’s strong security-first culture and partner with our customers to help them navigate the evolving cybersecurity landscape with confidence.”

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Ryanair is turning to AI from Google for everything from crew scheduling to optimizing business operations – and even automate decision making – as it bids to reach 300 million annual passengers.

Ryanair has considered a long list of wild ideas to cut costs and boost passengers throughout the years, everything from pay-to-use toilets, billing by passenger weight, and even standing-room only cabins.

Those ideas – usually from Group CEO Michael O'Leary – may be little more than marketing designed to grab headlines about how budget the airline is, but the five-year deal with Google may prove more useful.

Ryanair's five-year partnership with Google Cloud will see staff given access to Google's Gemini Enterprise, as well as models from Google DeepMind.

The airline said that Gemini Enterprise will be used to connect organizational data, automate workflows, and create custom AI agents to schedule crew, automate decision making, and boost corporate productivity.

DeepMind, meanwhile, would be used to boost fleet operations and schedule maintenance, in particular via its AlphaEvolve and WeatherNext models.

The deal isn't just focused solely on AI, however. The aviation company will also deploy Google Workspace and Google Cloud to its 35,000 employees as part of dual-cloud resiliency efforts developed to reduce outages of key technologies.

Ryanair currently has an existing partnership with Amazon Web Services (AWS).

Ryanair eyes strategic growth and resilience

The aim is to help grow Ryanair from 216 million passengers annually – making it Europe's largest airline by passenger numbers – to 300 million passengers annually by 2034.

"To support this growth, we need to ensure we have excellent infrastructure resilience, and our new dual-cloud strategy provides this, alongside technology partners that match our speed and relentless focus on efficiency," said Ryanair CEO Eddie Wilson in a statement.

He added Google would help staff create "even greater efficiency across our business while bolstering our infrastructure resilience."

Good news for Google

The deal is a notable public win for Google, which is seen by some to be trailing rivals such as OpenAI and Anthropic on AI.

Last month, CEO of Google-owner Alphabet Sundar Pichai was forced to defend the company's AI achievements and model release timetable, which was subsequently followed last week by a major shakeup of AI leadership at the company.

A headline grabbing deal with a well-known company to achieve specific business gains suggests Google may still have an edge when it comes to signing actual business deals.

Moreover, it gives weight to arguments that there may well be practical utility to AI – despite many companies struggling to put the technology to work.

"Aviation is an industry defined by precision, and Ryanair is a pioneer in operational execution," said Maureen Costello, Google Cloud's Vice President, for UK, Ireland and Sub-Saharan Africa, in a statement. "We are thrilled to be Ryanair’s AI transformation partner."

"This agreement demonstrates how deploying generative AI at scale – coupled with modern collaboration tools for frontline workers – can help industry leaders scale securely, reduce operational costs, and redefine the travel experience."

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QBS Software has expanded its European security portfolio through a new distribution partnership with Futurex, a provider of enterprise cryptographic solutions.

The agreement will see QBS act as an official Futurex distributor across Europe, making its technology available to the distributor’s network of resellers and managed service providers (MSPs).

The deal means QBS partners will be able to support customers looking to modernize their cryptographic infrastructure, move security workloads to the cloud, and address evolving regulatory requirements.

Futurex’s portfolio covers a range of enterprise use cases, including hardware security modules (HSMs), centralized key management, public key infrastructure (PKI), certificate lifecycle management, code signing, data protection, and payment security.

The solutions can be deployed across on-premise, private and public cloud, as well as hybrid and multi-cloud environments.

In an announcement, Jordan Travers, group head of security sales at QBS Software, said Futurex’s portfolio offers a “comprehensive approach” to enterprise cryptography.

“Our partners can now support a wider range of customer requirements, from cloud HSM and key management to PKI and payment security,” he explained. “This partnership gives the channel a strong foundation for building trusted, scalable cryptographic services across Europe.”

Expanding partner opportunities in Europe

Part of the QBS Technology Group, QBS Software operates out of 20 offices across Europe and connects more than 12,500 SaaS and software vendors with resellers globally.

QBS partners will now have access to Futurex platforms including CryptoHub, which brings together cryptographic services and key management across distributed environments, as well as the firm’s cloud-based cryptographic infrastructure, VirtuCrypt.

The platforms are designed to help organizations reduce operational complexity, maintain control of cryptographic keys, and apply consistent security policies across applications and infrastructure. They also offer flexible deployment models, centralized administration, and support scalable service delivery.

For resellers and MSPs, the companies said the partnership will generate new opportunities to differentiate their security offerings without adding fragmented tools or complex operational processes.

Simon Marrion, Futurex’s director for channels, Europe, said QBS’ established network of security-focused partners will help the vendor expand its reach across the continent.

“QBS Software combines deep regional expertise with an established network of security-focused partners,” he commented. “Together, we can help European organizations modernize cryptographic infrastructure while maintaining the control, resilience, and compliance their environments require.”

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The Government Commercial Agency (GCA) has unveiled G-Cloud 15, placing a specific focus on driving opportunities for small to medium-sized businesses (SMBs).

As part of the revamp, three separate frameworks will be consolidated into a “single, streamlined agreement”. This consolidation applies to the Cloud Compute 2 framework, along with Lots 1-3 and 4 of G-Cloud 14.

The setup will make it easier for public sector customers, including NHS trusts and local authorities, to purchase cloud services through a single easy-to-use agreement, according to the GCA, t

In a statement, the GCA described the move as the “most significant upgrade to the UK’s public sector cloud procurement framework since its inception in 2012”.

All told, the framework is valued at roughly £14 billion over its four-year term. The GCA estimates around £3 billion in public sector cloud spend will flow through it annually.

SMBs in the spotlight with G-Cloud 15

A range of new measures have been introduced to lower barriers to entry and improve opportunities for smaller suppliers.

This includes an 18-month “re-opening window” which allows new businesses to join the framework. They can also join at intermittent periods throughout the four-year term of the agreement.

Philip Orumwense, commercial director and chief procurement officer for technology at the GCA, said G-Cloud 15 represents a “genuine step forward” for SMBs.

“For too long, [SMBs] have faced barriers that hold them back from winning business - complex application processes, short framework windows, and procurement routes that favor incumbents,” he said.

“This framework addresses those concerns directly whilst enabling further access for British Businesses to Government and Wider Public Sector Bodies,” Orumwense added.

Simplified procurement

Procurement simplicity is another key focus area for the framework. G-Cloud 15 will feature a “modernized, industry-aligned classification system” designed to make it easier for public sector organizations to engage with suppliers.

“It also makes it easier for suppliers - particularly smaller ones without dedicated bid teams - to position their services accurately and be discovered,” the GCA said.

Sachin Agrawal, managing director of business software supplier Zoho UK, said the new measures represent a significant improvement and will streamline procurement.

“They remove the most resource-intensive part of procurement by having the supplier selection and evaluation process sat at framework level, with pre-negotiated and pre-vetted suppliers,” he explained.

Agrawal added that the relaunch coincides with the Local Government Reorganization (LGR) program, which is the “biggest shake-up of local authorities in decades”.

This will end the long-running two-tier system of local government across 21 areas of England, replacing local authorities with a smaller number of larger councils by April 2028.

“This shake-up is putting pressure on local authorities to move quickly, particularly in areas such as technology procurement,” Agrawal noted. “It [G-Cloud 15] will provide a fully compliant procurement route without the time, cost and legal complexity of an open competitive process, reducing time pressures ahead of the April 2028 LGR deadline.”

“The speed of procurement under this framework also streamlines deployment times to help tech be operationally faster.”

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We usually think of university as a place where undergraduates go to learn – but what happens when the entire establishment must study something new?

In recent months, the University of Manchester has had this exact experience, rolling out full Microsoft 365 Copilot access to its 65,000 staff and students. This means integrating it into Word, Excel, and PowerPoint, as well as incorporating AI agents such as Researcher and Analyst.

When this large-scale adoption finishes at the end of 2026, the University of Manchester will become the first institution of its kind worldwide to offer Copilot to its entire community. For PJ Hemmaway, the university’s CIO, this project is a way of “helping to prepare our students for the modern workplace”.

“Employers are increasingly expecting graduates to be confident users of AI technologies,” he tells ITPro. “By providing universal access, we are tackling the digital divide head-on, ensuring all can benefit from AI tools regardless of personal means.”

The University of Manchester is no stranger to AI; it has a long and deep heritage in the technology and the ideas behind it. This began with Alan Turing’s 1950 paper Computing Machinery and Intelligence, which first posited the question, ‘Can machines think?’.

Today more than 1,600 researchers across its campuses are using their skills to help tackle global challenges through interdisciplinary research into AI. For Hemmaway, this resonates with Turing’s legacy of laying the tech’s foundations there.

“We have always embraced AI and are actively looking at ways to use it to improve lives,” Hemmaway adds. “We are embracing the AI transformation early and leading the way for the higher education sector.”

Saving time and strengthening governance

There are many benefits expected from this rollout, including reducing the time everyone spends on routine tasks, which will free them up for higher-value, more strategic activities. There is also a specific use-case for evidence gathering and data analysis, traditionally complex and lengthy tasks. Hemmaway hopes students and colleagues will also use it to explore ideas beyond their immediate disciplines.

Given the ongoing global concerns over AI safety and ethics, Hemmaway cites how everyone is being supported by training, governance, and ethical use policies developed in partnership with the Student Union and staff networks.

A phased approach to the rollout has seen learning, guidance, and support built into each stage with an early April 2026 cohort having nearly 3,000 colleagues attend live learning sessions. Following the training, 80% felt confident or very confident to use Copilot, compared with just 24% before.

Formal policies, such as the IT Acceptable Use Policy and Teaching and Learning AI policy, will be reviewed and updated regularly. Hemmaway says these have already been strengthened to ensure responsible information handling, academic integrity, and clearer expectations around use of AI within assessments.

Ongoing feedback has also been given in open forums, which has already changed some approaches. This includes extending learning windows, improving signposting and FAQs, and increasing the focus on practical examples.

“The aim is not just to provide access to a tool, but to make sure colleagues and students understand how to use AI safely, responsibly, and effectively in their work or studies,” Hemmaway explains.

Building confidence amid enthusiasm and fear

Student rollout will start in the coming academic year, beginning around September or October 2026, by which time Hemmaway believes many initial challenges will have been overcome.

This means achieving full clarity around what Microsoft 365 Copilot is, what it can and cannot do, and how it differs from other AI tools. Its reach will go deep into this large university, touching everything from teaching to professional services and student support to sustainability. Early highlights of its use include summarising meetings and documents, drafting agendas, preparing first drafts, proofreading copy, structuring workloads, and analysing information.

Hemmaway wants people to build their confidence over time and ultimately integrate Microsoft 365 Copilot more personally into their own work or study. While people have generally been well-engaged, some users have reservations about the technology.

“We recognise people have different views about AI,” Hemmaway says. “Some are enthusiastic, some are cautious, and others have concerns about ethics, jobs, assessment, environmental impact, or data security.

“Our approach is to create space for questions and respond with clear guidance, rather than assume one message will work for everyone.”

From a security perspective, Microsoft 365 Copilot is operating within the University of Manchester’s existing M365 environment and permissions, Hemmaway explains. This means users have the same level of access to any information they already had.

Hemmaway’s also clear that nothing within the rollout is “about cutting jobs”. Instead, he says, the initiative is focused on exploring whether AI can help colleagues spend more time on “human judgement and collaboration”.

“Copilot is a support tool, not a replacement for professional expertise, decision-making or accountability,” he says.

Globant has announced the launch of Glob.AI, a new AI marketplace designed to transform how enterprises access, purchase, and deploy AI services.

The platform brings a self-service experience to Globant’s AI Pods model, allowing organizations to identify a business challenge, select an AI Pod suited to the task, and access production-ready services through an output or consumption-based pricing model.

Released in mid-2025, Globant’s AI Pods are service units run by a set of AI agents and supervised by humans. According to the company, more than 40% of its top customers are already using AI Pods, generating a pipeline worth around £261 million.

Globant said Glob.AI uses defined and repeatable processes, while allowing customers to choose which AI models they use and where those models run.

Additionally, the company confirmed that customer data will not be used to train external AI models, while token consumption will be managed through a proprietary Token Vault designed to provide greater visibility and traceability over AI usage.

In an announcement, Globant CEO and co-founder Martín Migoya described the new platform as a “one-stop shop” for its AI Pods, with each one specialized by task and industry.

“Traditional AI adoption drives token consumption far beyond what efficient output requires, and the real cost is the wasted tokens plus the unstructured, manual supervision of AI,” Migoya said.

“AI Pods introduce a smarter model, running the right AI through parallel agents, loops, workflows, and deterministic processes, representing the true state of the art of what AI can deliver today.”

Globant also highlighted a number of early results from its AI Pods, including a 20% increase in throughput generation at global football governing body FIFA while improving or maintaining quality rates.

The technology also enabled AI deployment across key functions at LALIGA within three months, as well as a reduction of up to 40% in contract timelines at Argentine energy company YPF.

Elsewhere, pharmaceutical company PharmaMar has implemented the technology to accelerate oncology research insights by 15x, while a leading commercial bank completed a COBOL migration in two months compared with a projected 14 months using a traditional approach.

Globant said its Glob.AI platform aims to move technology delivery away from fixed-term projects and lengthy procurement processes towards a more continuous model, with customers able to access and monitor work in real-time.

The marketplace will also feature AI Pods developed with technology partners including Anthropic, AWS, OpenAI, Google Cloud, SAP, Salesforce, Vercel, Adobe, and Microsoft Azure.

"AI is not just making the same projects faster, it is making thousands of projects viable that never were before," commented Guibert Englebienne, co-founder of Globant. "Until today, enterprises could not buy technology services this way: instantly, transparently, paying only for results.

“That is the shift Glob.AI delivers, and the strong demand for AI Pods shows enterprises are ready for it."

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Everpure has announced the appointment of Craig Robertson as head of partners for EMEA and Latin America, as the storage and data management specialist looks to drive further channel growth across the regions.

Based in the UK, Robertson is tasked with leading the company’s partner strategy and execution across the two regions, and will work with partners to accelerate growth, expand market opportunities, and help customers gain greater value from their data.

He succeeds Geoff Greenlaw, who has announced his retirement.

Robertson steps into the role following a decade at Everpure, where he has held various leadership positions across the business, and brings previous experience of working at partner organizations in the UK.

In an announcement, Everpure said the appointment was “pivotal” in its ongoing efforts to drive partner opportunities, with Robertson bringing strategic partner relationships, as well as channel strategy and go-to-market expertise to the role.

“Craig Robertson has consistently demonstrated his deep understanding of our partner ecosystem,” explained Ricardo Moreno, vice president of global partners at Everpure. “His appointment reflects the strength of our internal talent and our unwavering commitment to driving partner growth across EMEA and Latin America.

“Robertson is an ideal leader to help partners capitalize on the significant opportunities provided by AI and data management."

Everpure targets further EMEA, LatAM growth

Everpure provides storage and data management technology designed to help businesses make data more accessible and usable as they adopt AI.

According to the company, its EMEA and LatAm business grew 64.9% in the first quarter of 2026, compared with overall market growth of 17.3%, based on figures from IDC’s Enterprise Storage Tracker.

Everpure said partners are looking to differentiate their portfolios and strengthen their position as trusted advisors, with data-centric architectures providing an opportunity to help customers modernize their technology environments.

Commenting on his appointment, Robertson said partners will remain central to Everpure’s strategy as businesses continue to modernize their data environments in the era of AI.

"Having built my career here, I know that our partners are intrinsic to everything we do,” he said. “As we enter a new era where data primacy defines market leaders, our partner community is vital to helping customers modernise their data strategies and unlock real business growth.

“I’m excited to deepen these relationships across EMEA and LatAm as we shape the future together.”

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Google has lost four key AI staffers to a startup and shuffled leadership at DeepMind as part of a company-wide shake-up.

Alphabet announced a series of changes in its AI division this week, including the departure of Jeff Dean, who is taking a trio of colleagues to form a startup.

Demis Hassabis, CEO and co-founder of DeepMind, is stepping aside from leading the AI unit to become chief scientist of Alphabet, shifting his focus to longer-term projects.

The moves weren't welcomed by markets, with Alphabet's share price sliding 4% amid wider concerns that Google is on the backfoot when it comes to AI.

Alphabet CEO Sundar Pichai pushed back on concerns last month after the company posted record results in its cloud division. Google has lost top AI employees to Anthropic and OpenAI in recent months.

Demis Hassabis steps back from DeepMind

The changes will see Demis Hassabis, the Nobel-prize winning co-founder of DeepMind step back from his company, which was bought by Google in 2014 for an estimated $650 million.

In a memo confirming the changes, Hassabis said he will set aside “day-to-day operational responsibilities” to have more “time and space” for “big picture” projects.

Hassabis has recently discussed work on developing artificial general intelligence (AGI), and reiterated his belief that the main application of AI should be improving human health, such as curing diseases like cancer.

"Demis has described us as standing in the foothills of the singularity, and has been spending a lot of his time engaging externally," Pichai said in a memo sent to employees and published by the company.

"He and I have been long discussing a role that allows him to put his full attention on actively shaping the future of AGI. It’s work that is vitally important to Alphabet and humanity, and I can’t imagine a better person than Demis to do it."

Hassabis will remain as chair of DeepMind, which will now be led by Koray Kavukcuoglu, who has been promoted from his role as chief technology officer (CTO) at the division to senior vice president.

Google spinout

Alongside Hassabis' role change, Google confirmed the departure of Jeff Dean, who has led AI efforts at the company for nearly three decades.

Dean and engineering colleague Sanjay Ghemawat have founded machine learning (ML) company Discovery Loop, which aims to automate scientific experiments.

Pichai said the duo have helped drive “some of the most significant technology transitions” in the company’s history, from “early search infrastructure to the neural networks that helped create the modern AI era”.

While they've taken two other Google co-workers with them – DeepMind VP of research and technical lead at Gemini Oriol Vinyals and Google Brain cofounder Quoc Le – their former employer is investing in the public-benefit project.

"We’ll continue to work with them as a founding investor and Cloud partner, and collaborate on a research framework for ML systems and related infrastructure advances," Pichai said.

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Qualcomm has appointed longtime executive Wassim Chourbaji as senior vice president and president of its EMEA business, as the semiconductor specialist eyes further growth in the region.

Effective immediately, Chourbaji takes responsibility for leading Qualcomm’s strategy across the EMEA region and advancing the company’s strategic priorities across its various business areas.

He steps into the role following more than 20 years at Qualcomm, during which time he held a variety of leadership roles across the company.

Most recently, he served as president of Qualcomm’s Middle East and Africa (MEA) business, while also leading its government affairs organization across EMEA.

In an announcement, Akash Palkhiwala, Qualcomm’s chief financial officer and chief operating officer, said Chourbaji’s combination of leadership experience and industry knowledge will be a key asset as the firm targets further growth across EMEA.

“EMEA is an important region for Qualcomm, and we remain committed to investing in its long-term growth and success, with Wassim’s leadership experience, strategic vision and ability to build strong partnerships across industry and government continuing to be instrumental to Qualcomm’s success,” he explained.

San Diego-headquartered Qualcomm develops semiconductor and computing technologies spanning artificial intelligence, connectivity, and low-power computing.

In recent years, the company has increasingly positioned AI as a central facet of its technology strategy as it expands its traditional smartphone-centric business into areas such as automotive, PCs, industrial applications, and edge computing.

With Chourbaji’s appointment, Qualcomm’s EMEA business now enters a new phase of leadership. He succeeds Enrico Salvatori, who has decided to retire from Qualcomm following more than two decades leading its EMEA business and over 25 years with the company.

With immediate effect, Salvatori will assume the role of chairman and will continue to oversee Qualcomm’s EMEA Automotive business until his retirement date in June 2027.

“I would like to thank Enrico for his extraordinary leadership and contributions over the past 25 years,” Palkhiwala added. “He has built a strong organization, expanded our presence across key industries and fostered deep relationships with customers, partners and governments throughout the region.”

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