As an organization, ISACA is well-versed in and has a long history of helping its members stay up to date with the latest developments in IT security, governance, and risk.

But the pace of change, particularly in the AI era, can be unrelenting. Indeed, at this year’s ISACA Europe conference held earlier this month in Munich, Germany, there was a clear sense that changes in the technology landscape are putting more pressure on the association’s membership to stay current.

ISACA oversees a range of professional certifications, including CISA and CISM, and attending conference sessions helps attendees earn CPE credits that go towards maintaining these certifications. Sessions covered at this year’s ISACA Europe Conference 2026 covered everything ranging from cross-border data privacy, operational technology and proving security ROI, to supply chain resilience, ransomware prevention and digital sovereignty. While the topics were varied, they shared a common theme. Indeed, across almost all of them, the looming specter of AI was a constant presence.

Professionals in the field are concerned about how this technology will impact their day-to-day responsibilities, and ISACA is having to adapt its own processes in order to support them. As well as speeding up the pace at which it updates its certifications and training, the association has put forward several amendments to its bylaws, including lowering the quorum for member votes, moving its legal home to Washington, DC, and moving to staggered three-year board terms.

Responding to changing member needs

Speaking at the opening session in Munich, ISACA board chair Massimo Migliuolo said the proposals give ISACA “the governance agility to respond faster to the needs of members wherever they are in the world”.

That speed is more in demand than ever. AI is impacting the industry so dramatically that not only is it difficult for professionals to keep their skills current, but it's also reshaping roles faster than they can be defined. On top of that, it's resulting in regulatory scrambles as authorities scramble to catch up.

The shift is most evident in how often IT professionals are now feeling the need to update their credentials, according to ISACA CEO Erik Prusch.

“[Previously] you got certified, and maybe five years later or six years later, you might be getting your second certification as you’re escalating through an organization,” he says.

“Now it’s much more current, and everybody’s having to stay not only trained and keep their current certifications up to date, but also bring in new technology.”

AI was inescapable across the conference. Although plenty of sessions on the agenda focused on practical, iterative work - including previews of ISACA’s updated COBIT governance framework, GRC automation, NIS2 and DORA - nearly half of the agenda touched on AI in some capacity, including keynote sessions on the first two days.

As one might expect from an audience of security and risk professionals, the response to AI wasn't entirely enthusiastic, but fears around losing their jobs to AI have largely waned.

“Even 18 months ago, there was that threat of ‘AI is going to eliminate all roles’,” says Tara Wisniewski, senior vice president of advocacy at ISACA.

“I think we’re all kind of moving away from that, but it is going to significantly change roles.”

AI through a security lens

Instead, practitioners appear to have transitioned to more immediate practical concerns, including how the rollout of these systems is affecting their security, risk, and governance posture. In her keynote, cybersecurity advisor and former CISO Monica Verma took aim at the more apocalyptic predictions about AI, calling that narrative “extremely dangerous”.

“It takes away from the actual real AI and cybersecurity risks that we do have today,” she says.

“[The ones] that are already present, that are already imminent, that you and your organizations need to be thinking about right now. There is no time to waste.”

ISACA is tapping into this need for clarity with three dedicated AI credentials (with a fourth in development), as well as integrating AI aspects into CISA and CISM. Prusch says demand is partly being driven by AI work landing on existing roles, with established professionals increasingly asked to pick up elements of AI management on an ad-hoc basis. An IT audit manager, for example, might become an IT and AI audit manager.

“I think everybody within our domains, their roles have changed to some degree,” he says.

“It just hasn’t been structured or formalized as yet. They’ve just taken on more responsibility, and there’s no other place for them to go.”

However, while ISACA members aren't worried about the immediate future of their own roles, AI has affected some jobs. In particular, AI has been blamed for a reduction in available junior and entry-level roles, and senior practitioners are concerned that this will exacerbate the industry’s existing pipeline problems. As Migliuolo noted during the event’s opening address, ENISA estimates that more than 300,000 cybersecurity positions are unfilled across the EU.

“What the hell is a 23-year-old [to do]? How are they going to get that experience?” says Wisniewski. “I fear that the gap is going to get a little bit bigger, to be honest… We’ll even see things like, ‘it’s an entry-level position, but three years’ work experience is required’. That’s a mismatch.”

A multi-pronged approach

ISACA is trying to tackle the problem from both ends. Prusch says it now tracks new roles as they emerge, to shrink the lag before training for them exists, and on the policy side, Wisniewski says workforce development is “the drum we beat every day”.

In the UK, the organization has proposed amendments to the Cyber Security and Resilience Bill to clarify its skills requirements, and more broadly it presses policymakers to consider the talent pipeline whenever they regulate, since meeting any new rules requires “a qualified workforce”.

Even the lawmakers are struggling to stay ahead of the changes, Wisniewski adds, explaining that “there are very few policymakers that actually have any technical depth”. The EU’s AI Act is among the most comprehensive AI laws in the world, but the bloc is already discussing revisions because, she says, the technology hasn’t developed the way Brussels expected, and other countries are even further behind in their journey towards AI regulation.

Meanwhile, as governments continue to argue over the best way to design and implement AI safeguards, organizations are already struggling to comply with existing rules.

“European organizations are navigating an increasingly complex regulatory and threat environment,” Migliuolo noted.

“…Through the EU AI Act and NIS2, DORA, CRA and other emerging regulations, I think Europe is setting a very good standard… The challenge in this transition is how we are going to do the implementation.”

That transition is proving slow. Despite the deadlines for NIS2 and DORA compliance having passed well over a year ago, conference delegates were still attending sessions framed around working out how to demonstrate compliance. While large multinationals with deep budgets are ahead of this curve, it’s a different story further down the market, according to Wisniewski.

“It’s still early days, especially for smaller organizations, because that’s where you see stress in the system,” she says, adding that compliance costs can squeeze other budgets.

“When the compliance burden gets too intense, the budget has to come from somewhere… Is it taking away from a training budget?”

With legislation struggling to keep up, Wisniewski believes professional bodies may end up filling part of the gap themselves, acting as de facto regulators by establishing industry-wide standards. That’s one of the reasons ISACA is investing in a more substantial advocacy program, she says; the association also wants a seat at the table in emerging debates, such as whether cybersecurity should become a licensed profession.

None of this is new territory for ISACA, though; helping professionals make sense of unfamiliar technology and shifting rules is what the association was set up to do. The difference now is how little time there is to do it. By the time one change has been absorbed, the next is already on the horizon - such as quantum, which Wisniewski expects to feature alongside AI at next year’s event.

That’s what makes the bylaw vote more significant than its modest contents might suggest. Whether it’s through its training, its advocacy, or the standards it sets, ISACA’s influence depends on keeping pace with the profession it serves. To shoulder those responsibilities, the association needs to be able to move at the same speed as the technology it hopes to help govern.

“This is not your typical kind of acceleration path [for] adoption of new technology,” Prusch says, emphasizing that the industry as a whole has a difficult task ahead of it.

“We’re not talking about two decades ago, when we had maybe 10 years to develop the infrastructure. We are already behind.”

“The reality is,” he says, “we’ve got to do this faster.”

The career ladder has never been wobblier. Thanks to AI’s impact on job roles and responsibilities, what once seemed like a challenging but progressive climb to the top is a lot more complicated. Defined rungs on the career ladder, such as moving from junior into more senior positions, are now less clear.

Take the IT profession, where generative and agentic AI are helping to automate increasing elements of the software development lifecycle. From coding to testing and onto deployment and maintenance, AI agents are fulfilling parts of the traditional IT professional role, with a commensurate impact on the career ladder.

These emerging technologies are automating routine, entry-level tasks and compressing lower rungs of the ladder. As these rungs disappear, so do the opportunities for junior staff members to prove their capabilities and move into more senior positions, according to research from Harvard University.

If you’re going to climb the ladder, it’s more important than ever to stand out from your competitors. And the good news, according to the experts who have spoken with ITPro, is that professionals with the right blend of skills can still reach the top in the AI age.

“If you think about yourself in a narrow sense, then I think AI is likely to displace you,” says Joel Hron, CTO at content and technology specialist Thomson Reuters.

“But if you view yourself as a higher-order value add to a company – and your job is to solve problems, and you can avoid putting yourself in a box as a certain type of employee – then the sky's the limit for you, especially with AI.”

Find ways to join the dots

The message is clear: yes, AI brings an existential threat to some professional roles, but its impact doesn’t have to be terminal. Smart people embrace the challenge of automation. For Hron, a promotion-worthy professional understands that tomorrow won’t look like today.

“I think adaptability is now one of the most important things, especially as the job of software engineering is changing,” he says, referring to transformations in IT roles and responsibilities.

“If you believe that the value that you bring to an organization is through the code you write, then you know you are going to be frustrated in the future.”

Career ladder changes are not confined to the IT sector. Employees in all sectors, from public sector organizations to blue-chip enterprises, are seeing labor market flux. In these fast-changing conditions, managers look for up-and-coming staff who can work across functions.

Thierry Martin, head of enterprise data and analytics at automotive giant Toyota Motor Europe, says he’s impressed when people can join the dots, particularly if they bring a new take to an established way of working.

“Success is about going beyond the obvious,” he says.

“It’s great if someone can say, ‘Hey, we have the sales data, we have this quality data, we have this manufacturing data, and look, this is what we can do with it.’ I might think, ‘Wow, I never thought about this.’”

That sentiment resonates with Bernhard Seiser, VP of digital, data and IT at AOP Health, who says the people who impress him are hungry for change. The pharmaceuticals sector is characterized by the opportunity to turn small ideas into life-changing transformations. The best professionals look to exploit their knowledge.

“Great people want to learn,” he says.

“They want to understand not just the technical parts, but also the business. That capability is critical for my business and how I see digitalization within a pharmaceutical organization. My team needs to understand how the organization operates, sometimes even better than the people in the business, ideally.”

Crucially, Seiser says, great ideas aren’t put into production in isolation. Professionals who move up the career ladder understand a challenge before others and then work to deliver ambitious solutions on time and to budget as part of an integrated approach.

“Always keeping in mind that we are part of a family is key,” he says.

“Managing our portfolio is often stressful. We have a lot that needs to be delivered, but this work also needs to be seen in a broader context – we're here as a family to serve our patients, and that's what the professionals need to keep in mind.”

Enable change for the business

The characteristics of next-generation leaders that business leaders like Seiser identify are focused squarely on high-quality delivery. For Tal Carmi, CIO at technology specialist WalkMe, AI might change the shape of the career ladder, but that impact doesn’t mean the best people transform their approach.

“In general, impressing the boss is about taking ownership,” he said.

“It’s caring about being a good partner to the business; trying to be an enabler, not a naysayer. And it’s about working pleasantly. Collaboration doesn't have to be centered on corporate-style language. Being a good partner means being someone people like to speak to.”

Encouragingly, Carmi says professionals who excel in these areas – taking ownership, enabling change, and collaborating effectively – will have plentiful opportunities to be promoted, particularly in IT. People who see your strengths will be receptive to your ideas, rather than thinking you’re just interfering.

“You will find yourself at the forefront because you will try to adopt new tools, concepts, or whatever the latest thing is to try and give the business you’re working with the best solution that you can,” he says.

Ankur Anand, group CIO at recruiter Harvey Nash, also says key characteristics define impressive professionals. First, they have a robust understanding of the business problem. Second, they explain their solution without using technical jargon.

“This structured approach is not just about technology,” he says.

“It’s about technology, governance, control, and people, which is training and learning and everything together. And the final piece is about understanding what role they play in making their solution successful, and knowing what data helps.”

In short, great would-be leaders measure and assess risks that inform decisions. Anand gives the example of software testing. Rather than testing endlessly to try and make things work, a great professional approaches their boss and explains the cost, in clear financial terms, of not getting a system up and running.

“Then the executive understands the issue and says, ‘Okay, now I get the impact, and we need to figure out why things are not working,’” he says.

“There’s a big difference between a person who understands the context and risk, and those who can then articulate those concerns in a business-focused way.”

AI tools like copilots, chatbots, and agents have rapidly taken root in the workplace in the years since ChatGPT brought the technology into the mainstream. The initial promise was that AI would lighten the load and help workers carry out tasks without having to learn new skills. In reality, that's not quite what happened.

Barriers to adoption have led to a growing AI skills gap in companies driven not by a lack of understanding of how to use the technology, but by a lack of understanding of how the technology works and what its weaknesses are.

On this week's episode, Jane and Ross are joined by Greg Hanson, VP and head of EMEA North at Informatica from Salesforce, to discuss the impact this can have on companies and whether there is a straightforward way to overcome it.

Highlights

"When we did our survey, what was very clear coming through the datasets is that organizations are actively investing in data literacy. So some of the things we've already talked about are resonating, and they recognize this is an area, a critical operational area."

"That's the first thing; let's challenge where people are and make sure we are operating from the same benchmark. You've got the right readiness to assess."

Links

• Why AI adoption is a people problem, not a technology problem
• Enterprises are 'paralyzed by a lack of understanding' with AI adoption – and there's one key factor that decides success

High job satisfaction may not be enough for employers to keep hold of their tech staff, according to new research from professional association ISACA, which warns that burnout and unclear career paths are pushing workers to look elsewhere.

According to the organisation's Tech Workplace and Culture 2026 report, which surveyed more than 1,000 tech professionals worldwide, although 76% are satisfied with their current role and 71% are satisfied with their career progression, nearly three-quarters (73%) said they would consider moving to a new employer in the next two years, or had not ruled it out.

Among respondents who had left a previous job, the most common reasons were better career prospects (29%), higher pay (28%), and more interesting work (23%). An unclear path upwards was also the most commonly cited obstacle to career advancement, named by a third (34%) of respondents and 41% of women.

Economic conditions may be masking the scale of this problem, according to Julia Hermann, head of digital platform services at cybersecurity firm Giesecke+Devrient. Speaking at a media briefing during ISACA Europe 2026, Hermann, who is also a leader of ISACA's SheLeadsTech programme in Germany, said layoffs in sectors such as the German automotive industry had led to a phenomenon known as "job hugging".

"People stick to their jobs, though they might not be totally satisfied, because at the moment it's not really easy to find a new job," she said. "The salaries are partially going down, or at least stagnating, so you're not necessarily making a big jump when you go to another company."

Long probationary periods add to the risk of moving, she added: "If you're the last to come, you're the first to go on the next layoffs."

This trend may be delaying departures rather than preventing them, however. ISACA warned that workplace pressures are feeding into the sector's retention problems, which three-quarters (75%) of respondents said were already a concern for their organisation. More than half (59%) of respondents said they had experienced work-related stress or burnout, rising to 64% among women, with the main causes being heavy workloads (48%) and a lack of resources (43%). Despite this, only a quarter (25%) said their employer offers mental health days, and 23% said it offers no support at all.

AI is adding to this pressure, Hermann explained, noting that while the technology is often deployed with the intention to reduce workloads, companies are not hiring for new roles to run the platforms behind it. As a result, she said, the work lands on existing staff on top of their day-to-day operational duties, noting that AI has created "a lot more work" for her team, which is now responsible for managing and securing the internal platforms that support the company's own AI models.

Entry-level roles may be more affected, however. Younger staff tend to move jobs more often, according to Hermann, and AI may also be squeezing the roles they start out in. ISACA's senior vice president of advocacy, Tara Wisniewski, warned this could make the industry's pipeline problems worse, arguing that organisations like ISACA and universities need to help graduates into the market, "and industry needs to be called to the table there too".

"We do believe that professions will change. We don't believe that they will be eradicated as a whole, but we do believe that they will change," Chris Dimitriadis, ISACA's chief global strategy officer, told media at ISACA Europe. He said he expects AI to take on most technical and orchestration tasks, leaving people to focus on governance, configuring and monitoring AI systems, and making final decisions.

In ISACA's State of Cybersecurity 2026 report, which surveyed security professionals globally, soft skills were the most commonly reported shortcoming among security professionals (57%), while 45% cited missing LLM SecOps capabilities, up 12 percentage points from the previous year. As AI takes on more technical work, Dimitriadis said, security staff will increasingly need the ability to explain to the rest of the business, in financial terms, how investment in security and AI will pay off.

Many teams are already short of people and money, however. The same report, published last month, found that more than half of European cyber security professionals said their teams were understaffed (56%) and underfunded (55%).

"Too often we are seeing budgets being sunk into crisis response, but there's still a distinct lack of investment in the workforce, training, and resources needed to prevent attacks and protect organisations in the first place," Dimitriadis said when the report was published.

He warned that the skills gap is likely to widen as roles change, "not just in terms of the numbers, but also in terms of the type of skills that's needed". It could grow "not because we are going to lose the people, but because... their knowledge may become obsolete very fast as digital ecosystems change".

ISACA's Tech Workplace and Culture 2026 survey of 1,025 tech professionals worldwide was carried out between 17 July and 3 August 2026. Its State of Cybersecurity 2026 report surveyed 1,888 cybersecurity professionals, including 494 in Europe, in May 2026.

Nearly one-in-four UK business leaders pretend to know more about AI than they actually do, while even more are worried that their lack of expertise will affect career prospects.

New research from Emergn found that 23% admit to bluffing about their AI knowledge, with 38% believing their career will suffer unless they drastically improve their AI skills within the next year.

Despite the fact that every respondent had been in their role for at least five years, 22% said they feel anxious or lose sleep over how fast AI is changing their industry, with the same proportion feeling out of their depth because of AI’s impact on their role.

Training, though, is thin on the ground. Only 43% of UK senior leaders told researchers they had taken part in substantial, ongoing AI training in the past 12 months.

Four-in-ten, meanwhile, said that they'd change jobs if a new employer offered better AI training.

Workers are worried about AI skills capabilities

These concerns extend to their staff, with more than four-in-ten leaders saying they rate AI skills above formal qualifications, and 36% saying delivery performance would deteriorate significantly if their most experienced transformation people left.

“It is hard to admit you do not understand something when you are supposed to be the person with the answers. But pretending leaves you with the same unanswered question tomorrow. Employers need to make it easier for people to say where they are stuck and get useful help,” said Alex Adamopoulos, CEO at Emergn.

“If someone is worrying about their career or losing sleep over AI, telling them to keep up is not much of an answer. Give them time to learn and coaching they can use in the working day. People need to see a future for themselves as the work changes.”

It's not just leaders that are bluffing about their AI skills. A survey earlier this year from Pluralsight found that 79% of tech workers pretend to know more about AI than they actually do.

Despite this, though, nine-in-ten tech workers and execs said they believed they have the necessary skills to use AI in their day-to-day roles.

Earlier this year, the government launched a new program to train 10 million people in practical AI skills for work.

The idea is to teach them to use simple AI tools effectively in the workplace for tasks such as drafting text, creating content and completing administrative tasks.

Broadly speaking, the UK is severely lacking in AI skills, according to a report from the Learning and Work Institute and The Rigby Foundation.

Comprehensive AI upskilling could help boost UK productivity by 2.3% by 2035, creating a net present value of £80 billion over the next nine years.

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Anthropic has revealed plans to train more than 10,000 ‘frontier deployed engineers’ (FDEs) by the end of 2027 as the firm looks to drive enterprise AI adoption.

The Claude Frontier Academy, backed by $100 million in funding, will see the AI firm work with Accenture, Bain, Capgemini, McKinsey, and others to ramp up training of FDEs.

Steve Corfield, Anthropic’s global head of business development and partnerships, said the investment will target heightened adoption of Claude products and improve skills capabilities for customers.

“A small team of high-agency people with the right skills, access to Claude, and a deep understanding of how their business runs can transform an entire company,” he said.

“The hard part is building that depth of talent, engineers with the highest level of AI fluency who can take Claude from an idea to a system in production and turn it into faster processes and new products and services.”

The move by Anthropic comes just months after the launch of Ode, an enterprise AI services firm launched following a $1.5 billion investment. The joint venture includes support from consulting firms such as Blackstone and Goldman Sachs, with the aim of helping customers implement AI.

How Anthropic’s FDEs will work

According to Anthropic, the academy’s first program, dubbed the ‘Frontier Deployed Engineer Residency’, follows the “medical model for building expertise”.

Engineers will learn in a similar manner to practicing physicians by training on real-world use cases and are assessed before practicing alone.

“FDE Residency engineers learn from practitioners, practice on realistic cases, and are assessed on their work before they earn the credential,” the company explained in a blog post.

“The goal is agentic systems that change how a business runs, from faster, redesigned processes to new products and services.”

The program is designed specifically for “hands-on software engineers with strong fundamentals” and those with an extensive background in working with LLMs and supporting enterprise AI adoption projects.

Participating organizations are allowed to nominate individual engineers, who then undergo a multi-day program with Anthropic engineers and instructors, the company noted.

“They work through a simulated enterprise deployment, from the right use case through security review to handover, and finish with a graded practical on a new scenario,” Anthropic explained.

“Those who pass earn the Claude Resident Engineer badge and move into the 12-week residency, where they lead a real Claude use case at their own organization, supported by Anthropic engineers and learning from their cohort as they build.”

Anthropic revealed the first cohorts under the scheme are already running in San Francisco, New York, and London.

Anthropic’s multi-pronged approach to AI adoption

If you’re wondering why the term ‘FDE’ sounds familiar, it’s because these engineers have become a primary focus for big tech companies over the last year, albeit with a slightly different terminology.

Microsoft and Amazon Web Services (AWS), for example, announced multi-billion dollar investments in ‘forward deployed engineer’ capabilities earlier this year.

As ITPro reported at the time, FDEs have rapidly become one of the most sought-after technology professionals globally as big tech providers look to accelerate integration of the technology for customers.

A key advantage of FDEs is that they’re embedded directly within customer teams to help support adoption processes and to build custom AI applications. AWS said its own strategy aims to compress integration timelines from “months to days”.

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You can lose a job to AI, but in California, a human has to make the decision to fire you.

California Governor Gavin Newsom has signed into law the No Robo Bosses Act 2026, requiring human oversight in the workplace specifically when it comes to firing or disciplining workers.

Act SB 947, as it's officially known, was introduced by Senator Jerry McNerney to push back against the use of automated decision making systems (ADS) in the workplace. In a statement, McNerney's office pointed to the rise of "bossware" products used to manage workplaces, which have led to people being mistakenly fired. The new law doesn't outright ban the use of such systems, but requires a human in the loop.

“No worker should ever be fired or disciplined by a robo boss," said McNerney, in a statement. "Artificial intelligence systems have the potential to increase productivity, but they’ve also been prone to errors, bias, and misjudgments.”

McNerney added that the aim is ensuring human oversight in workplaces. “AI must remain a tool controlled by humans, not the other way around," he said.

California has led AI regulation, with laws requiring frontier AI developers to report safety incidents and publish safety frameworks, forcing AI generated content to be labeled as such, and creating a registry for AI auditors, alongside rules targeting political and sexual deepfakes, and AI generated unauthorised replicas of performers, among others. Newsom signed into law a list of other AI rules this week, including banning lawyers from handing over core work wholly to AI and requiring educational institutions to train staff and students about AI.

"Super intelligence is clearly not coming from the White House – that’s why California continues to lead," Newsom said in a statement. "AI should expand opportunity – not come at the expense of workers and families. As this technology reshapes the workplace, California is putting people at the center, ensuring we all have a voice in the decisions shaping their future."

No robo bosses

The robo boss legislation has three points. First, it bans employers from relying solely on ADS to make firing or disciplinary decisions. Second, it requires human oversight and verification when employers do use ADS to assist in those decisions. And third, if a company does use ADS for termination or disciplinary decisions, the impacted worker must be informed.

The rules will be enforced by the California labor commissioner, state attorney general, or local prosecutors. Similar laws are in the works in a handful of other states.

The law was backed by the local labor union, with Lorena Gonzalez, president of the California Federation of Labor Unions saying the law gives "other states and the nation a clear example of how, by letting workers lead, we can stop some of [the] worst abuses of AI at work."

SB 947 originally included a provision to notify employees if an AI system would impact their work, but Newsom vetoed it saying the focus should be on misuse rather than forcing "unfocused notification requirements on any business using even the most innocuous tools," he said at the time. That aspect was removed, as were protections for gig workers.

Rise of AI workplaces

The move comes as management becomes increasingly automated or algorithmically controlled. A survey from the OECD last year found that 90% of American managers polled said they have at least one such tool in place, versus 79% across Europe and 40% in Japan.

Beyond prevalence, that study also found that US companies were more likely than European counterparts to use algorithmic management for monitoring or evaluating workers even if it involves personal data and has "consequential outcomes" such as access to work. The study added that two-thirds of managers were concerned about the impact on workers, particularly with regards to unclear accountability in the case of incorrect decisions.

One example of that playing out now regards Meta, which faces a lawsuit after the Facebook-owner attempted to apply AI to monitoring and managing its own workers earlier this year, taking into account everything from token usage to keystroke monitoring – and reportedly using that data when deciding on a massive round of layoffs.

In response, a group of former and current staff have sued.

"Meta used a constellation of internal artificial intelligence systems – including a system referred to internally as ‘Metamate,’ employee-trained ‘second-brain’ agents, keystroke- and activity-monitoring data, AI-token-usage dashboards, and algorithmically assisted performance ranking and calibration – to score, rank, and select employees for inclusion on the list," a court filing reads, noting the system disadvantaged those on leave, including for maternity or disability.

Nearly half of UK employers are planning to boost their technology teams by the end of this year, looking mostly for security, AI, and cloud skills.

According to new research from Robert Half, 47% of UK employers hope to boost their tech workforce, with 54% looking for cyber security skills, 50% agentic AI skills, 48% generative AI skills, and 44% cloud skills.

Meanwhile, another 25% are expanding contract and project-based hiring.

"Technology remains one of the most active areas of hiring in the UK labor market, with nearly half of employers planning to grow their permanent technology teams before the end of the year," said Matt Weston, senior managing director, UK & Ireland at Robert Half.

"Businesses continue to invest heavily in cyber security, cloud infrastructure, and artificial intelligence, but they're not simply looking for more people. They're looking for professionals with the right blend of technical expertise, commercial understanding and the ability to work effectively alongside AI."

According to the researchers, 45% of UK technology professionals say they're now expected to develop new AI-related skills, while 38% spend more time overseeing and validating AI-generated outputs. At the same time, 53% say AI has cut the time they're spending on routine tasks, and 37% that their roles have become more strategic.

The findings, said the team, point to a growing demand for professionals who can work effectively alongside AI systems, applying human judgment to ensure accuracy, quality, security, and compliance.

"As organizations increase investment in AI, cloud infrastructure and cyber security, we're seeing strong demand for professionals who combine technical expertise with strategic decision-making," said Weston.

"AI is automating some tasks, but it isn't replacing the need for skilled technology talent. In many cases, it's making those skills even more valuable."

With cyber threats continuing to evolve and businesses increasing investment in AI-powered technologies, the firm said it expects competition for specialist talent to remain strong, especially for those with expertise in cyber security, AI, and cloud environments.

The report coincides with the UK government's latest figures on the cyber security workforce, showing that it's expanded by only 2% over the last year – although it, too, finds that most companies are looking to hire this year.

There was a 7% increase in core cyber security job postings – roles where some aspect of cyber security is the main job function – and a rise of 10% for roles that might not be formally labeled as cyber security jobs but that still require cyber security skills.

However, 57% of businesses said they had a basic technical skills gap, up from last year's 49%.

Back in January, the government announced plans to provide 10 million workers with key AI skills by 2030 through free courses available to all, opening a skills hub that's already seen the delivery of more than a million courses. Meanwhile, the NCSC offers training courses for both novices and experienced security professionals, with courses targeted at sectors from board members to schools.

Workers with scarce skills and strong AI capabilities are pulling away from the pack, being rewarded for innovation while the bulk of their colleagues go largely ignored.

That's according to PwC's 2026 Global Workforce Hopes and Fears report. A survey of nearly 50,000 workers across 48 countries that classifies workers into four groups: front-runners, AI insurgents, indispensables, and the AI learning curve.

Front-runners, with scarce skills and strong AI abilities, account for 14% of employees, while 18% are classified as AI insurgents, whose skills are less scarce but who are using AI to deliver more.

Indispensables, with scarce skills that employers value highly but who are not far along the AI learning curve, account for 11%.

However, PwC said it's the 'engine room' workers who make up the bulk of employees, lacking scarce skills, and further behind on the AI learning curve. Of these, only two in five say they have access to the learning and development resources they need.

And, the researchers said, it's these workers – the majority of the workforce, responsible for most of the day-to-day work within an organization – that should be getting more attention.

"There is a real risk that the global workforce is starting to move at different speeds. More than half of workers are not yet benefiting from AI and skills in the same way, while those with scarce skills and strong AI capabilities are becoming more confident and more mobile," said Pete Brown, PwC global workforce leader.

"Leaders need to think hard about where they invest in skills, how they give people the opportunity to adapt, and how they hold on to the capabilities they most need."

As for the front-runner employees, they're more confident in their job security, more likely to trust management, and more confident about their ability to learn new skills.

They are one-and-a-half times more likely than average to be rewarded for challenging existing ways of working, and 1.2 times as likely as average to learn new skills.

Nearly seven-in-ten daily AI users report confidence in their job security, compared with 57% for infrequent users, and are also more likely to ask for a promotion. However, 29% of front-runner employees with strong AI capabilities and scarce skills say they are very or extremely likely to change employers in the next year.

Overall, workers are feeling significant pressure. Only a third report having money left at the end of the month, down 8% year on year. Meanwhile, 29% say they have significantly less bargaining power than three years ago, more than double the number who disagreed. For fully remote workers, the proportion is 10 points higher.

The biggest risks to job security, they say, are economic volatility (57%) and AI taking on more tasks (44%), with Gen Z more anxious across all these metrics.

And 58% of those who have experienced change in the workplace feel there has been more change in the last year than in previous years, with almost one-third saying that their productivity is suffering thanks to fatigue or burnout.

"Workers are under growing pressure from rising workloads, rapid change and external uncertainty," said Brown.

"But those using AI every day are more confident, more ambitious and more positive about their careers and prospects. The challenge for leaders is to keep developing those people – but not at the expense of the rest of the workforce."

Salaries in the UK tech sector are rising rapidly for those with AI and data literacy skills, according to new research, but demand for softer skills is declining rapidly.

New data from Michael Page's 2027 Salary Guides shows the AI boom is having a strong effect on pay, with the top salary for an AI or data architect in London up by 20% compared with last year.

Head of AI roles are now paying around 11% more, and machine learning/AI engineers are up by about 8%.

“Applied AI skills are driving movement in the market. The people who can take AI from experimentation to secure, scalable production - AI engineers, data architects and cyber specialists - are commanding a meaningful premium," said James Barrett, UK practice director, technology, at Michael Page.

"The value lies not in generic AI awareness, but in combining deep technical capability with governance, data and real-world delivery."

Declining soft skills

Notably, soft skills are in far less demand, with creativity, communication, and analytical thinking all having dropped out of the top five desirable skills in the last year.

“Businesses are investing in the skills that modernize core technology and deliver measurable value," said Barrett.

These people can be hard to find, however, with most AI specialists reluctant to switch roles. Just 38% of technology professionals are actively looking for a new role, well below the 50% national average.

Similarly, 59% of technology hiring managers cite limited availability of skilled candidates as one of their biggest barriers to hiring, while three-in-ten tech companies said they found matching candidates' salary expectations 'challenging' when recruiting new talent.

“Candidates in high-demand areas know their value and they’re negotiating the whole proposition: pay, flexibility, progression, and the quality of the work," said Barrett.

"Employers are responding with more creative packages, from flexible hours and additional leave to AI training and accelerated development pathways. Many are redesigning roles around skills rather than perfect experience."

The in-demand UK tech roles

According to the survey, tech roles in most demand include:

• Applied AI architect/engineer
• Data architect/engineer
• DevOps/SRE
• Cybersecurity architect/engineer
• Business change manager

Looking ahead, the firm said there's likely to be growing demand for AI transformation leads: not just strategists, but people who can identify viable use cases, redesign workflows, manage risks, and drive adoption.

Many organizations are looking to temporary staff to fill the gap. AI consultancy now commands the highest day rate of any tech skill set – around 24% above cloud architecture, 24% above cloud architecture and 16% above program management.

"Employers are using permanent and interim hiring together as part of the same workforce plan, with interim often the fastest route to expertise while the permanent team is built alongside it," said Barrett.

The findings partly align with the results of ServiceNow's recently-published 2026 Workforce Skills Forecast.

This survey found surging demand for Python-related capabilities and test management roles. Conversely, the ServiceNow study highlighted increasing demand for more 'human' skills such as leadership, problem solving, and collaboration.

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Despite lingering concerns over AI’s impact on the labor market, new research from ServiceNow predicts the UK tech sector will undergo a jobs boom in the coming years.

The firm's 2026 Workforce Skills Forecast projects an increase of 432,000 additional jobs in the UK’s technology, media, and telecoms sector by 2031, marking a 28.2% increase on today's numbers.

According to the study, this job growth will be partly due to a “human renaissance” in hiring practices. The company describes this as a “new phase of work” in which technologies such as AI transform roles, but human capability “determines their value”.

Put simply, human workers will still be a critical component in the workforce moving forward, regardless of increased automation. Indeed, ServiceNow said that demand for talent is still growing rapidly worldwide, with human skills spanning leadership, problem solving, and collaboration in hot demand.

Findings from the report suggest that enterprises across the tech industry will require around 16,000 more workers with problem solving skills as a key trait by 2031, for example.

On the technical skills front, demand for Python-related capabilities is also expected to surge, with the sector requiring an additional 16,000 workers with these skills.

Elsewhere, demand for test management roles is expected to reach more than twice its current level by 2031, followed by test strategy, planning, and performance.

Damian Stirrett, group VP and GM for ServiceNow UK & Ireland, said the study shows that while AI integration accelerates across the industry, top talent will still be a key focus for enterprises.

“The UK has built one of the world’s fastest-growing technology workforces, creating a significant opportunity as AI reshapes how work gets done. But organisations cannot treat their technology and people strategies as separate agendas,” he commented.

“The businesses that succeed will be those that redesign work around AI while investing in the technical and human capabilities their people need to use it effectively. Combining both will be critical to turning innovation into productivity and sustainable growth.”

Soft skills in the age of AI

The capabilities identified by ServiceNow appear to fall under the ‘soft skills’ bracket, which have become a key focus in the age of AI.

In a similar vein to ServiceNow, an August 2025 study from Multiverse highlighted the importance of a “combined approach” to AI adoption that incorporates technical capabilities alongside soft skills.

Indeed, the firm identified areas such as analytical reasoning, communication skills, problem solving, and ethical understanding as the top “human skillsets” required to support AI integration.

These ranked on-par with technical skills such as prompt engineering.

Upskilling the key to success

Crucially, UK firms have a wealth of untapped talent that could be unlocked through upskilling, according to Jayney Howson, chief learning officer at ServiceNow.

Workers in non-technical roles could play a key role in filling tech talent gaps moving forward.

“Learning must keep pace with work. Technology adoption is moving faster than skills development, and many of the fastest-growing roles sit at the intersection of technology and people. Employees will need technical fluency alongside judgment, collaboration, leadership and stakeholder engagement,” she said.

“People do not always need to start again. Many emerging roles build on capabilities they already have. Employers must help people use those skills as a springboard, while creating clear and practical development pathways that enable them to adapt and progress as work evolves.”

The findings from ServiceNow’s report follow similar research from Gartner in late 2025. While the analyst firm predicts that AI will have a marked impact on the global labor market, the technology will ultimately create more roles that it destroys.

That’s dependent on whether organizations have the capability to upskill in line with adoption rates, however. Gartner projects that around 32 million jobs will be “reconfigured, redesigned, or fused” each year from 2028 onwards.

Speaking to ITPro at the time, Helen Poitevin, distinguished VP analyst at Gartner, said the organization expects around 150,000 people will need to be upskilled every day to counter job losses.

Similar research from Box in June this year found UK business leaders also predict AI to create more jobs in the long term.

In a poll conducted by the firm, nearly two-thirds (65%) of respondents said they expect their organization’s overall headcount to increase over the next three years.

Notably, Box identified a range of dedicated, AI-focused positions to emerge as adoption rates accelerate. Nearly half (48%) of firms are actively recruiting for ‘AI agent operators’ within IT teams while 32% are hiring ‘workflow automation specialists’.

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The government should create financial incentives to encourage employers to provide AI skills training, according to a new report.

Financial modelling by the Learning and Work Institute (L&W) and The Rigby Foundation found that the UK is well placed to adopt and scale AI, but unlocking AI’s full economic potential will only be realized by increased investment in skills training.

Based on the Office for Budget Responsibility’s (OBR) central scenario, the report's financial modelling finds that comprehensive AI upskilling could help deliver an economy-wide productivity boost of 2.3% by 2035.

This, the report noted, would generate an £80 billion boost to the UK economy.

“The UK’s AI advantage depends on ensuring that the leaders and workers who make up our economy at large have the skills to make the most of these new technologies. AI has transformative potential, and the gains are within reach," said Stephen Evans, chief executive of the Learning and Work Institute.

"By building basic digital skills across the working-age population and updating technical qualifications faster, we can turn widespread enthusiasm for AI into real productivity growth. We need employers to invest in training as much as AI, backed by an agile skills system, to make the most of the huge potential ahead.”

As part of the report, a YouGov survey found that while 85% currently use AI in some capacity, only 18% use it 'extensively' within their operations.

Large firms lead the way, with 25% using AI extensively, compared with just 11% of small businesses – a quarter of whom have yet to adopt AI at all, compared with 3% of large enterprises.

Researchers said this could be improved by strengthening digital literacy and boosting leadership and management capability, most notably by incentivizing employers financially.

AI skills training in the spotlight

The UK government is well aware that its significant AI ambitions will mean boosting skills, and earlier this year announced plans to train 10 million people in AI by 2030.

Participants will learn how to use basic AI tools in the workplace, such as using AI for drafting text, creating content, or completing administrative tasks.

However, researchers are calling for more incentives for employers – including a Skills Tax Credit that would provide a 20p credit for every £1 spent on accredited training.

Under these proposals, it would have a 30p 'AI super-rate' until 2030 to drive urgent adoption.

Meanwhile, the government should create a dedicated AI Skills Intelligence Unit to provide practical AI applications and work with employers to consider quality 'kitemarks' for non-accredited training.

“AI is the biggest growth opportunity in the UK and the moment to act is now. The investment needed is minimal compared to the size of the prize," said Steve Rigby, CEO of Rigby Group and chair of the Rigby Foundation.

"An £80 billion return on investing in our workforce is within reach, and SMEs and Government together can make this AI transition a success story for the whole economy. The new administration has a golden opportunity to reform the current skills system and drive immediate, productive investment in human capital.”

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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.

As AI continues to rewrite job roles, an increasing number of employers are encouraging their employees to gain AI certification.

Back in April, Korean media and network services provider SK Broadband announced plans to train its staff as AI natives. It comes on the back of an AI proficiency certification program last year.

"We will establish a culture where employees independently develop AI agents to transform productivity and create real business value,” an SK Broadband spokesperson told The Korea Times.

More than a third of employees (35%) are interested in gaining AI certification, according to Pearson’s annual Value of IT Certification report released in April, which surveyed 505 IT and HR leaders. This figure is up from 17% in 2025.

The rising interest in AI certification should come as no surprise, according to Imran Akhtar, head of academy at talent and training partner, mthree.

“Many employers are looking for existing talent who can say they understand AI by spotting problems clearly, questioning its outputs, applying their own judgement, working safely with data, and using it effectively to improve how work gets done," Akhtar explains.

For employees, the value of AI certification is that it gives them ”a recognized way to evidence their knowledge of AI”, Akhtar adds. Certification helps to put theory into practice by testing employees’ knowledge in real-world scenarios.

The AI certifications to choose from

With so many AI certifications available, it may seem hard to know where to start. The right certification, however, is going to depend on an employee’s job role and which AI tools they need to perform that role more efficiently.

Another factor is an employee’s career plans and what AI knowledge and skills they may need as they climb the career ladder.

“Some jobs may demand certification because the role directly involves AI systems, data, risk, or governance. For others, it supports broader AI literacy and bolsters day-to-day work more holistically,” says Akhtar.

Here are a few starter AI certifications to choose from.

AWS Certified AI Practitioner

Structure: Online, 65 questions

Price: $100

Valid for: 3 years

AWS Certified AI Practitioner covers the basics of AI, genAI and machine learning (machine learning) concepts and use cases. The certificate is ideal for business analysts, IT managers and IT support, as well as product and project managers.

Google Generative AI Leader

Structure: Online, 50-60 multiple-choice questions

Price: $99

Valid for: 3 years

Google Generative AI Leader is for anyone looking to boost their business-level knowledge of generative AI (GenAI). The exam covers the fundamentals of genAI, Google’s genAI offerings, techniques for improving genAI output, and business strategies for successful genAI deployment.

Databricks Certified Generative AI Engineer Associate

Structure: Online, 45 multiple-choice questions

Price: $200

Valid for: 2 years

Databricks Certified Generative AI Engineer Associate is for anyone who wants to validate their ability to design and implement large language model (LLM) solutions using Databricks. It’s recommended that those taking the certification have at least six months of hands-on experience performing genAI tasks outlined in the exam guide.

Nvidia Certified Associate Generative AI LLMs

Structure: Online, 50-60 multiple-choice questions

Price: $125

Valid for: 2 years

Nvidia Certified Associate Generative AI LLMs is aimed at those who are looking to build on their basic understanding of AI and LLMs and learn how to develop and integrate AI applications using AI and LLMs with Nvidia solutions. It covers data visualization, neural networks, prompt engineering, and Python libraries.

These four certifications are considered foundation-level, but there are next-step certifications that employees can take to advance their knowledge and skills further.

For example, AWS suggests that those pursuing careers in AI, data and machine learning (ML) gain the AWS Certified Data Engineer – Associate. Those going down the cloud path could take the Certified Solutions Architect - Associate.

Certification can boost career and salary prospects

Research published by Revelio Labs last month found that the average salary for workers who had gained a foundation-level certification in AI or generative AI is $79,800. For comparison, the average for workers who hadn’t gained one is $72,300.

The data also showed that certification gainers were more likely to be hired for a more senior role for their next position (38.9% had received one) than non-certification takers (32.5%).

Given the tight job market, employees are looking for anything that can give them an advantage. AI certification can improve their job mobility and help them to stand out from the competition, Faye Ellis, principal training architect at tech skills provider Pluralsight, tells ITPro.

“Certifications demonstrate a commitment to continuous development and validate that skills are up to date and workplace-ready. For many, this can provide a route to new opportunities or higher-paid roles,” says Ellis.

To mandate or not to mandate

The question employers may be asking themselves is whether they should mandate AI certification.

Ellis explains that while every employee “needs a baseline level of AI literacy, mandatory certification will depend on the role and technical depth required.

She cites the example of software developers. Companies should be more inclined to make certification mandatory for them because they’re involved in building and governing AI systems. For employees whose roles are less technical, certification needn’t be mandatory, but they should be encouraged to “support a foundation in responsible AI use, prompt quality and output validation”.

Akhtar agrees, but cautions that certification doesn’t always guarantee future career success.

“Certification can boost a career, but only when it builds the capability an employee can apply in their role,” he says.

“It’s unlikely to support career progression if AI training doesn’t reflect the core business objectives.”

Nearly three-quarters (74%) of companies have reworked security team structures due to the influx of AI tools, and that’s sparking high demand for cyber pros with dedicated skills.

New research from SANS Institute found the rise of dedicated, AI-focused roles in cybersecurity is driving up salaries across the industry.

High-end salaries for AI security roles now top $260,000 (£194,000), with positions such as Post-Quantum Cryptography Migration Specialists and AI governance leads in high demand.

Pointing to a review of UK vacancies on LinkedIn, SANS Institute noted that there are thousands of AI security positions being advertised online, suggesting that hiring for such roles has "moved from prediction to present-day reality".

That suggests that AI isn't taking over cybersecurity jobs, but changing which skills are necessary for the work, the organization said.

"Routine analytical work is increasingly automated, while demand is accelerating for professionals who can secure AI systems, govern AI risk, conduct AI red teaming and orchestrate AI-powered security operations," the institute said.

A new wave of cybersecurity roles

Dedicated AI roles spanning a range of security-related areas are popping up across the industry, SANS noted. AI security engineers, for example, are in hot demand, now commanding salaries of around $185,000 on average.

Roles focused on specific areas and threats are also emerging, the study noted. Ads for AI Identity Deepfake Defense Specialists have been identified. While it’s a wordy job title, the study noted that this shows the impact of trends such as deepfake voice fraud.

Professionals in these roles can command salaries of between $130,000–$175,000 (£97,000–£131,000), the institute noted.

Long-term, the organization expects these new specialist careers will lead to premium salaries due to intensifying demand for skills.

Other new AI-related roles identified by SANS Institute include:

• AI Governance, Risk & Compliance Lead ($240,000 salary)
• AI Red Team Specialist (up to $220,000)
• AI Supply Chain Security Engineer (up to $185,000)

Intriguing new roles include AI Incident Response Orchestrator, AI threat intelligence analyst, and AI SOC Orchestrator were also highlighted by the institute.

Growing quantum focus

It’s not just AI reshaping roles and sparking heightened demand for cyber pros with specific skills, however.

Dedicated quantum-related cybersecurity roles are also growing in frequency, the study found, as organisations ramp up preparations for ‘Q-Day’.

This is the point at which quantum computers can break traditional encryption techniques. While the debate on when this comes still rages, many enterprises are looking ahead to this point - and job ads reflect this.

SANS Institute pointed to roles such as Post-Quantum Cryptography Migration Specialists – a position focused on reacting to looming mass breaking of current encryption by quantum computers – saying it could earn above $260,000.

Reshaping team structures

The study from SANS Institute isn’t the first to highlight the impact AI is having on team structures. As ITPro reported earlier this month, the same shift is occurring in software development due to the influx of AI tools.

Research from Gartner predicts that 60% of enterprises will rework software development units into ‘tiny teams’ by 2030.

While this shift toward ‘smaller’ teams may have alarm bells ringing for developers, the consultancy noted that this won’t necessarily spell bad news.

This transition won’t be a cost-cutting effort or attempt to reduce headcount, but will instead focus on creating more focused, specialized units.

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Palo Alto Networks CEO Nikesh Arora has issued a stark warning to workers reluctant to adapt to generative AI: they face a “Darwinian moment”.

Speaking during a recent appearance on the 20VC podcast, Arora suggested a significant portion of workers globally lack necessary AI skills, which raises questions about how leaders can implement change and build workforces capable of meeting future demands.

“The challenge right now is 90% of enterprise employees are not AI savvy. They’re not,” he said.

“They have to learn. I can’t send them to university. There’s no course you can take in school anywhere. They have to be able to learn on their own. I think we’re back to a Darwinian moment where everybody has to figure out who’s really good.”

In some cases, building an AI savvy workforce has prompted some drastic action by executives. Nikesh pointed to Coinbase CEO Brian Armstrong’s approach of penalizing workers who refused to adapt or embrace the technology.

During a podcast appearance last year, Armstrong admitted to firing workers who refused to engage with the technology after paying for enterprise licenses for GitHub Copilot and Cursor.

Other organizations, such as Jack Dorsey’s Block, reportedly introduced AI mandates for workers. Both companies laid off staff this year amidst claims that the technology is changing how they operate.

“You’ve seen people like Brian Armstrong and Jack Dorsey go out and say, ‘I’m going to decimate my organization, and I’m going to start building from scratch’ and they’ve gone to some version of 30, 40% fewer people because they figured out there is no redemption,” Arora said.

As ITPro reported last year, punitive measures to spur AI adoption in the enterprise is a sure fire way to create workforce pushback.

It’s a similar dynamic to the return to office (RTO) mandates that caused widespread upheaval at a range of big tech firms in recent years. Encourage, but don’t push, or else it could come back to bite you.

Palo Alto Networks’ approach leans toward a gradual shift, Arora noted. The company, which has roughly 20,000 staff, has a “natural attrition of 2% a month. The focus now is on replacing these staff with people who are indeed AI-savvy.

Elsewhere, the company actively seeks out AI talent from events such as hackathons, Arora revealed. These are lucrative talent pools that the company can draw from to acquire staff.

“We hire from hackathons,” he said. “Give me 12 months, I’ll have sort of transformed 20, 25% of my team. Give me three years, I’ll hopefully have enough AI-savvy people working at Palo Alto.”

Top-down encouragement

Building an AI-savvy workforce also requires accountability on the part of leadership, Arora said. Delivering change requires leaders across an array of functions to have ambition and actively engage with the technology.

Arora has regular conversations with leadership figures aimed at establishing their progress with AI, allowing them to showcase potential wins.

“You have to make sure your leaders are ambitious. You have to make sure they're competitive. You have to make sure they want to win. You have to make sure that they have a learning mindset,” he said.

“When they watch their peers around them do cool [stuff], they want to show up and do cool [stuff] the next time. So for me, it's getting 14 people together and saying, ‘Hey, Harry, tell me today, what have you done for AI the last three days since I last talked to you in your organization, and whatever motivates you?”

This gives Arora a clear understanding of the direction some leaders are going in with the technology. Moreover, it appears to act as a springboard for motivating others across the company.

“It creates a little bit of Darwinian competition amongst them. It creates this urge to go embrace this new technology, and I think hopefully I get 14 people fully motivated, and then they go do that with the next set of people because I need to transform from the top down, not from the bottom up on this topic.”

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AI is already transforming the workplace, but does today’s workforce have the necessary skills to use it productively, appropriately, and safely?

The short answer, experts agree, is no. According to Forrester, most employees lack the baseline understanding, skills, and ethics to use AI tools like Microsoft Copilot or Google Gemini in this way. Among information workers in five countries, the analyst firm found that High AIQ only grew from 12% to 16% between 2024 and 2025, and front-line workers are likely further behind still.

“While we don’t have a survey of the AIQ of frontline workers at this point, we assume that they lag further due to gaps in education and immersion into tool usage,” notes J.P. Gownder, vice president and principal analyst on Forrester’s Future of Work team.

While natural language input and multimodal models can lower the operational barrier of AI tools, ease of input isn’t the same as the competence of use. Vendors consistently underplay the human side of AI, says Gownder, which includes the skills, motivation, ethics, and behaviors employers need to cultivate for employees to use AI successfully at work.

“[It’s not] a straight line to success: AI hallucinates, generates coherent nonsense that sounds right but isn’t, can violate privacy standards, and reinforce poor human decisions through its sycophancy.”

Natural language removes one barrier but quietly raises another: that of judgment, says Professor Rose Luckin, founder and CEO of EDUCATE Ventures Research. “The tool will answer almost any question fluently, including those it shouldn’t and when it’s wrong. So the claim that these tools are accessible to anyone confuses producing an output with producing a reliable one.”

What’s the worst that can happen?

Lack of ‘AIQ’ can lead to misuse and mistakes, and so a business opens itself up to a lot of risk if users aren’t properly trained, notes Holly Chate, coo of FutureDotNow – a coalition of UK-based leaders working to close the digital skills gap.

Untrained users might unwittingly share customer or company data: “If you put confidential information into an open source GPT, suddenly that data’s now publicly available,” she points out. They may also pass along incorrect information to customers or prospects, or generate confidently wrong answers about their next best step on the job.

There’s a further risk beyond individual error, Luckin adds, noting that people who don’t understand the tool are the most likely to outsource their judgment to it, accepting what it produces because questioning it feels beyond them. “Over time, that erodes the very capabilities they need to use it safely. The gap isn’t only about access, it’s about who retains the judgment to stay in control of the tool and who gradually hands that control over.”

The four key AI skills employees need to have

In reality, the use of AI tools can widen the digital confidence gap between employees, with the confident getting more capable, while the hesitant fall further behind. The solution to this, and to reducing the other related risks, is to ensure your staff gets the necessary training. But what exactly does this entail?

FutureDotNow developed evidence-based AI skills recommendations to embed into the UK Department for Science, Innovation and Technology’s (DSIT) Essential Digital Skills Framework. Its research found four key AI skills that every worker needs to have. These are AI literacy and understanding, effective communication with AI, critical evaluation of AI outputs, and responsible use of AI.

In the case of effective communication, prompting matters, as this is something that doesn’t come naturally to most people, notes Luckin. “The better the prompt, the larger the pattern you give the model to match, so structured prompts with clear context produce better output.

“My caution is about sequence and proportion,” she continues. “I once sat through a training session that spent 45 minutes on prompt engineering and never once explained what a large language model (LLM) does or why it hallucinates. That’s the wrong way round. Teach it after understanding, not instead of it.”

The ability to critically evaluate AI output is the skill most worth investing in, Luckin says, which has three parts. She recommends starting with the why, as people evaluate output far better once they understand that the model generates plausible text rather than checking facts. Next is to build habits.

“I describe this as the ‘wobble test’: ask for sources, challenge the detail, press on the claims and see whether the answer holds together or collapses,” Luckin says.

“Practical checks help too, such as confirming that cited references actually resolve, since invalid digital object identifiers (DOIs), broken links, and fabricated citations are common signatures of generated text.”

The third part is domain grounding. Critical evaluation depends on knowing enough about the subject to sense when something’s off, so training is most effective when it’s contextual, practiced on real tasks the learner cares about, and uses genuine examples of failure, rather than delivered as abstract drills, Luckin explains.

Getting training right

A 2025 survey from McKinsey found that while 88% of organizations use AI, only 6% are generating meaningful returns. Work by BCG explains why, says Luckin: “Algorithms account for 10% of AI success – people and processes make up roughly 70%.”

This highlights the importance of staff training, but it’s just as critical to get that training right. Gownder notes that too few organizations currently invest in sufficient training: “It’s typically one-and-done.” AI requires iterative training, he says, as it changes all the time, and employees need practice and reinforcement. He adds, however, that social learning and practice are even more important.

Chate recommends designating ‘digital champions’ within teams, as “humans learn from humans. If you identify a handful of people to give extra training to, and incentivize them to support their colleagues, that’s been proven hugely successful.”Another idea is to build AI training into the day-to-day, she notes, such as adding 10 minutes to the end of a weekly meeting where people share their top tips or ask questions. “Having that little bit of support and knowing where to go is really helpful,” she adds.

IT training is a lucrative market, with IDC estimating that the global market will grow to $26.6bn by 2029, up from $21.5bn in 2024.

This is driven by digital transformation, AI adoption, and persistent skills shortages, according to Gina Smith, research director for IDC’s IT Skills for Digital Business practice. Smith adds that 36-40 percent of CIOs globally cite finding skilled professionals as their top talent challenge. It’s understandable, then, that IDC reports 73 percent of businesses plan to increase their training spend this year.

With technology advancing at speed, savvy vendors have positioned themselves to not only provide the latest solutions, but also support businesses’ need for continuous upskilling. Today, major vendors such as AWS, Cisco, Google, IBM, HPE, and Microsoft train millions annually, with the Cisco Networking Academy alone serving more than seven million learners per year.

While first and foremost, vendors cite the digital skills shortage as the main catalyst for developing their own training academies, they don’t deny that there are strategic and commercial drivers, too.

“Vendors have told IDC that they also use academies to accelerate product adoption and ecosystem lock-in, build brand loyalty and influence standards, address regional regulatory or localization requirements, and differentiate via talent pipelines and customer enablement,” says Smith.

The highest uptake is in sectors with rapid digital transformation, such as finance, healthcare, government, and manufacturing, while geographically, North America, Europe, and Asia-Pacific lead in adoption.

“The Middle East and Africa (MEA) and Latin America are seeing rapid growth due to large-scale vendor/government partnerships,” adds Smith, “with AWS, Microsoft, and Google launching initiatives to train millions in AI and digital skills in MEA.”


Vendors vs universities

But what about higher education – are software providers stepping into the roles that were traditionally held by universities? The simple answer is no, according to Ryan Rose, director, skills and certifications product management at Learn with Cisco.

Vendor academies have been designed to sit alongside and complement university education rather than replace it, he says, but adds that the relationship between education and employment is changing quickly.



“In today’s environment, employers are increasingly prioritizing demonstrable skills over formal credentials alone,” he says.

“That doesn’t diminish the value of degrees, but does mean they’re no longer the only signal of workforce readiness. We see it as building a parallel pathway, one that’s more directly connected to industry needs, continuously updated as technology changes and accessible to learners who may not follow a traditional academic route.”

Smith highlights that some universities struggle to keep pace with rapid tech change and employer expectations for job-ready graduates, especially in cloud and AI, which is why many are now partnering with vendors to embed certification and hands-on labs into their curricula.

“Universities will continue to play a critical role in foundational education, but the reality is that learners now need more flexible, continuously updated pathways that reflect how quickly technology is changing and how work is being redefined in real-time,” notes Rose.

The certification calculation

So how should CIOs view vendor-certified talent? Is hiring people with these qualifications a strategic advantage, a pragmatic shortcut, or a dependency risk? 



Smith believes CIOs view it as a pragmatic solution to immediate skill gaps and accelerating technology adoption, but notes that there are risks IT leaders must consider, as overreliance can create dependency, reduce flexibility, and increase switching costs.

“Vendor certifications are widely recognized and can boost employability, but deep specialization can create ecosystem dependency. Organizations are increasingly building workforces aligned to specific vendor stacks, especially in cloud and AI. This can lead to structural dependency, but also ensures up-to-date job-ready skills,” she points out.

The potential risks of doing this can include reduced multicloud flexibility, higher retraining costs, and talent mobility constraints, she adds, advising IT leaders to look towards cross-vendor certifications, third-party training, and focus on transferable skills, such as containerization and data integration in order to reduce vendor lock-in.

Skills without strings attached

Vendors are keen to highlight, however, that many design their certifications to be transferable. “While the certification comes from Cisco, what it teaches applies across a wide range of infrastructure environments and industry roles,” notes Rose.

In the case of FPT, the company launched its own training ecosystem to ensure that its in-house skillset met customer needs. Its foray into education began with its Software Academy’s specialized training program for developers, designed to bridge the gap between academic theory and real-world project delivery. Today, it runs its Vietnam-based FPT University, which provides technical and language training to over 150,000 students, and maintains partnerships with 180 organizations across 40 countries.

“Over time, we see opportunities for FPT to not only support our own workforce, but also the wider ecosystem,” notes Mark Scrivens, chief executive officer of FPT UK.

“The dependency concern is understandable, but it’s not how we design our programs. The ultimate focus is on transferable skills, logical thinking, and problem-solving. Instead of training people on a single technology stack, we design our curriculum based on project demand, business strategy, and market trends. Technology stacks will continue to change. As we service diverse sectors like retail, healthcare, automotive, and finance, our engineers’ ability to learn and adapt is what matters most.”

A hybrid future

IDC believes vendor academies will continue to grow and could even become the dominant model for technical upskilling, especially in fast-moving domains such as AI, cloud, and cybersecurity. However, traditional institutions will remain essential for foundational education, research, and broader skills development.

“Hybrid models are likely to become the norm,” says Smith.

“IDC’s bottom line is that CIOs should use a holistic, skills-first approach, leveraging both certifications and academic credentials as signals, but always validating with practical, role-aligned assessments and a focus on business value. This ensures hiring decisions are resilient to technology shifts and aligned with long-term organizational goals,” she concludes.

Cisco has announced a partnership with the UK's Department for Science, Innovation, and Technology (DSIT) to support digital skills development across the country.

The strategic collaboration with the technology department will support the government's AI Opportunities Action Plan, which aims to provide skills courses to more than 10 million people by 2030.

Cisco noted that the move will also support the government's TechFirst program, which is designed to provide one million secondary school students with access to "technology and AI learning experiences".

Cisco Networking Academy will play a key role in the partnership, with the company committing to contributing over 8,000 hours of employee volunteering for educational schemes over the next four years. And there will also be work experience opportunities for 7,000 students across London, Manchester, Birmingham, and Glasgow.

"We believe a digital society that works for everyone isn't out of reach. Neither is it the responsibility of one group of people or organisations," Sarah Walker, CEO of Cisco UK & Ireland.

"That is why collaboration matters. Today's announcement marks a year of progress towards our commitment to help create a more inclusive, digital UK and Ireland, with a clear path to future impact."

Supporting tech skill development

The move from Cisco comes a year after the networking firm unveiled its UK & Ireland Manifesto to coincide with London Tech Week.

This outlined the company's commitment to "help everyone benefit from a more digitally inclusive society" by providing skills and career opportunities for people from a range of backgrounds.

A year on from the manifesto launch, Cisco said it has made "tangible progress" across three key areas of the pledge:

• Growing its presence in communities
• Developing digital skills
• Activating its people and partners

Cisco has scaled up skills development schemes significantly over the last year, launching a series of partnerships aimed at creating learning pathways for careers in AI, cybersecurity, and networking. The networking firm has worked with more than 100 organizations to support skills development, including through its apprenticeship and levy donation programme with Multiverse.

The company also revealed it has helped 100,000 people build skills and expertise through the Cisco Networking Academy over the last 12 months. Marking a significant step toward its goal of supporting one million learners across the country by 2030.

Organizations that don't have a comprehensive AI people strategy will lose their top talent as soon as this year, according to Gartner.

According to the firm's Global Labor Market Survey, half will see their most talented workers abandon ship for competitors who prioritize workforce enablement over basic adoption.

Only 27% of executives have a comprehensive AI people strategy, the consultancy found, and just 20% believe their workforce is truly AI-ready.

“The survey revealed that in the shift to an AI-powered workforce, most leaders are mistaking basic access or adoption metrics for transformation,” said Swagatam Basu, senior director analyst in the Gartner HR practice.

“This ‘enablement illusion’ is hiding risks and draining ROI.”

Keeping employees happy

Organizations face a host of challenges on this front, according to Gartner. First and foremost, while AI success is often rated in terms of hours saved, 19% of employees said no time was saved at all.

Instead, Gartner said organizations should be focusing on effective and diverse AI use.

Employees who are proficient with AI across multiple use-cases are twice as likely to be highly productive, 2.3 times more likely to deliver high-quality work, and 3.2 times more likely to drive effective process improvements.

Meanwhile, the use of shadow AI needs to be tackled, with a focus on AI governance.

“Eighty-eight percent of employees with enterprise AI access also use personal AI tools for business tasks, often to save time,” said Diana Sanchez, senior director analyst in the Gartner HR practice.

“While hybrid AI users are 1.7 times more likely to report significant time saved over those using only enterprise solutions, this behavior increases corporate data risk and also drives attrition risks with critical talent.”

Focusing on senior staff is also causing problems, Gartner found. While most employees are offered enterprise AI, 73% of highly productive users are managers or executives.

More junior staff – who, after all, are responsible for the majority of automatable tasks – often don't get enough support and guidance.

Nervy staff are causing problems

Notably, Gartner said nervous staff are holding their organizations back, with anxiety over AI-driven job losses undermining productivity and slowing adoption rates.

Employees with a positive outlook on AI are 3.4 times more likely to be highly productive, according to Basu.

“The most effective drivers of positive AI adoption are employee confidence in their current and future roles, and transparent, ongoing communication about how AI will be used and its impact on jobs.”

Looking ahead, leaders need to provide clear communication about how jobs and skills will evolve with AI and set clear norms for human-AI collaboration to reduce anxiety about job preparedness.

They should carry out regular trust pulse surveys to monitor workforce sentiment around AI, and address concerns early and proactively.

Gartner's findings echo research published this week by HR services provider Randstad, which found that the most limiting factor in AI-led transformation is the human factor, rather than the technology.

More than a quarter of technology professionals told the HR consultancy that their organizations are still not doing enough to develop their skills, and 52% said they were seeking training independently – largely because internal programs cannot keep pace with the rate of technological change.

"Upskilling can no longer be treated as an HR program or professional development perk. It’s business-critical infrastructure, part of your technology stack, not separate from it," said Michael Morris, global head of platform and talent at Randstad Digital.

"It needs to be funded, architected, measured, and continuously improved like any other mission-critical system. The organizations that view workforce capability as a layer of their technology stack are the ones that will finally see the AI ROI that has remained so elusive."

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"Breaking point" is a strong term – but one that Gallup doesn't refrain from using when underlining the state of employee engagement today. For many, life feels much harder than it did a few years ago; budgets are being slashed, geopolitical uncertainty is crippling markets, and technology is beginning to pose an existential crisis to many. The list goes on. That's partly why "breaking point" is appropriate.

Last year engagement fell for only the second time since 2009, from 23% to 21%, according to the organization's latest report into the global workforce. The last sustained fall was due to the COVID-19 pandemic in 2020, again a two-point drop from 22% to 20%. This latest dip, the report suggests, has cost businesses a collective $438 billion in productivity losses.

"When employees are engaged, they are more productive at work. They are absent less and produce more. They build better customer relationships and close more sales," the authors of the report write. "So, what engages work teams the most? Their manager. If managers are disengaged, their teams are, too."

What's sparking the engagement fall?

Myriad factors are contributing to a steady decline in engagement, which organizations have "failed to address at their root," says psychotherapist, neuroscience coach and founder of WorkingWell Daily, Farah Harris. For some, a return-to-office mandate has "reintroduced layers of stress around commuting, childcare and managing competing responsibilities with fewer resources". Beyond that, she adds there's a "deeper psychological wound at play".

"Folks are just tired. Tired of the uncertainty. Tired of the layoffs. Tired of being required to do more with less. Tired of the change initiatives that are rolled out with big fanfare then are abandoned or make things more complicated," Harris tells ITPro. She adds that millennials are also dealing with chronic distress in the way of "professional futures that were promised but never delivered".

There's also a "relentless pressure" to do more with less, say many of the experts to whom ITPro spoke. Lisa Sansom, founder of LVS Consulting, says: "We're dealing with a workplace that's burned out and younger generations have seen their parents work hard for no reward, just missing out on family and life. That's not sustainable and employees not only want balance, they also want meaning, purpose, and mattering."

What about the rise in technology, and particularly AI in the engagement fall? It plays a role, experts tell ITPro, but is rarely ever the root cause. "In my work, technology and AI run the risk of diminishing the priority that we place on relationships," says Laurie Cure, the founder and CEO of Innovative Connections. "How often do we start a remote meeting and just get down to business? It’s easy to forget that people are still in the room."

More broadly, leaders need to consider how they deploy new technologies, especially AI. "AI is increasing the speed and complexity of work, but most organizations haven’t evolved their infrastructure and ways of working to help people keep up," Lauren Tropeano, chief people officer at Docebo, tells ITPro. Troeano has 20 years of experience building and scaling teams at organizations like DraftKings, Pivotal Software, and Dell/EMC. "Employees are given new tools without the clarity, skills, or permission to truly change how they work. So instead of feeling empowered, they feel behind and confused."

Diving into management issues

Managers are less engaged than before, according to the research, but the trend is worse among young professionals and women. That's in part because the generational challenges leaders are experiencing are more extreme than in previous years, explains Cure, with many requiring coaching and mentoring, as well as clear frameworks, that simply aren't there. "We’ve handed younger leaders one of the most complex versions of leadership we’ve ever seen and often given them the least support to navigate it."

There's also no moving beyond the way that managers are positioned to be in the middle of the organizational structure – between employees and senior leadership. They are often the ones who must absorb the shock of organizational changes and strategic shifts before thinking fast and ensuring those they manage can adapt and get on board. Meanwhile, they need to juggle such transitions with general performance, hybrid working, employee welfare and resource management. These are demanding tasks that are placing an increased cognitive load on managers, many of whom aren't given the tools to handle the added and often volatile set of responsibilities, experts tell ITPro.

The problem is concentrated among certain quarters. Younger and female managers, in particular, are expected to lead with empathy while navigating the same shifts everyone undergoes without clear guidance and support, Tropeano says. That's not sustainable – and organizations are not investing in manager capability and clarity.

Disengagement among female managers in the workplace is "rooted in a deeper different type of exhaustion," agrees Harris. "It’s 2026 and we are still working on closing that gender equity gap. Not just financially, but in access to opportunities, decision-making power and basic respect. Many women are still trying to navigate the tension between what a successful career is supposed to look like and what a full life requires – especially if raising a family. Women are disengaged because the system wants their labor, not their presence, and it keeps asking them to choose."

Turning the tide

The unfortunate truth is that most workers don't trust their leaders and managers – with less than half (48%) retaining faith in senior management, according to Gartner research. Cure pinpoints a few factors that are further exacerbating the trust deficit, including layoffs, restructures, shifting policies on remote work, and economy uncertainty. All of these place more of a burden on leaders, who are themselves becoming increasingly stretched thin.

To overcome these challenges, Cure recommends building leadership capabilities throughout the organization. "Rarely, if ever, do you hear someone talk about a great leader and list their technical accomplishments. More often, it's about how they motivate and encourage their employees and how much they care."

Angela Rixon is founder and CEO of The Centre for Meaningful Work and tells ITPro that stabilizing the manager experience is as close to a silver bullet as you can get, because "managers are the biggest multiplier of team engagement". This, she adds, involves proper training, practical coaching and ongoing support – not just expecting managers to carry the can on the greater complexity and rely on their instincts purely.

"More broadly, organizations need to bring back coherence. Set fewer, clearer priorities," Rixon argues. "Improve role clarity. Help people see how their work connects to customers, outcomes, and progress. Give teams more local autonomy over how work gets delivered, and create communication rhythms that feel predictable rather than reactive."

The crux of the matter comes down to how well senior leadership can set up their managers for success – and that starts with clarity, says Tropeano. "From there, organizations need to invest in continuous development so employees feel capable of meeting evolving demands. Engagement improves when people feel focused, supported, and able to do meaningful work well and when they bring the right mindsets to the mission at hand.

"It’s not about asking people to give more. It’s about creating the conditions where they can."

While concerns mount over the impact of AI on the global jobs market, Nvidia CEO Jensen Huang insists workers in some professions will benefit greatly from the huge infrastructure build-out required to power the technology.

Speaking during a commencement speech for Carnegie Mellon University’s class of 2026 at the weekend, Huang said economic growth through AI won’t be limited to the technology sector.

Indeed, trade workers will be among the vanguard helping to ramp up infrastructure roll-outs across the US and around the world.

“Electricians, plumbers, iron workers, technicians, builders, this is your time,” he told students. “AI is not just creating a new computing industry, it is creating a new industrial era.”

“AI gives America the opportunity to build again.”

Huang’s prediction of a golden era for tradespeople comes amid huge investment in the underlying infrastructure used to power AI.

Capital expenditures at a host of major tech players, including AWS, Microsoft, Meta, and Google have skyrocketed as providers look to match surging compute capacity demands.

The AI infrastructure will require significant investment over the next five years to keep pace with demand, according to 2025 research from McKinsey.

The consultancy projects data centers will require roughly $6.7 trillion in investment by 2030 to keep pace with demand for compute capacity.

Data centers designed specifically for AI processing will also require a whopping $5.2 trillion in capital expenditure.

Job market threats and opportunities

With AI infrastructure build-outs continuing at pace, research shows that demand for tradespeople is surging. Analysis from Randstad in March this year, for example, found global demand for skilled trades is growing three-times faster than professional roles.

Demand for HVAC engineers and construction workers has surged 67% and 30% respectively, the consultancy found.

Concerns over the impact of AI on “white-collar” work and entry level roles have been rising over the last two years, however.

Last year, Anthropic CEO Dario Amodei suggested that AI could wipe out half of entry-level roles by the end of the decade. A March 2026 report from Anthropic also warned white-collar workers are highly exposed to AI and automation.

The study also uncovered “suggestive evidence” that hiring of younger workers has slowed in exposed occupations. That tracks with SignalFire’s 2025 State of Talent report, which pointed to a marked reduction in tech companies hiring recent college grads across 2024.

During the commencement speech, Huang touted an upbeat outlook in terms of AI’s impact on the jobs market, suggesting that the technology will ultimately deliver broad benefits.

"You are entering the world at an extraordinary moment. A new industry is being born. A new era of science and discovery is beginning. AI will accelerate the expansion of human knowledge and help solve problems once beyond our reach," he told graduates.

"No generation has entered the world with more powerful tools, or greater opportunities, than you. We are all standing at the same starting line. This is your moment to help shape what comes next. So run. Don’t walk."

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When it comes to skills, the outlook for the technology industry can seem contradictory.

On the one hand, employers report continuing skills shortages. On the other, the job market is tightening, especially for early career professionals. New graduates struggle to find their first roles; more experienced workers fear redundancy as companies cut back. Developments in AI only add to the uncertainty.

But these trends are also changing the way the tech industry, and IT professionals, view training. Individuals are taking more responsibility for their development, including paying for training.

Options for training are changing too. Long courses and classroom-based learning have given way to micro credentials, cloud-based labs and what educators call “self-directed” learning. Demand for this can only grow, as both employers and individuals look to bolster their AI and wider digital skills.

Ups and downs

Even so, the picture for training and education in technology is not universally positive. Internationally, spending on workforce training is growing. But UK businesses are spending less.

The corporate training market is projected to grow from $417.53 billion in 2025 to $439.82 billion in 2026, according to The Business Research Company’s Corporate Training Global Market Report 2026.

Pluralsight, a technology training provider, puts the global market for workforce training at a similar value of $400bn today, with annual growth at between 5 and 10%. According to Faye Ellis, principal training architect at Pluralsight, the tech skills market is growing faster at 18-22%. She expects it to triple in size by 2030.

“Organizations are still feeling the effects of skills gaps,” she tells ITPro. “As advances in AI, cloud computing and data analytics accelerate, organizations are going to see the need to continuously retrain their workforces. Estimates suggest that the majority of workers will require significant reskilling by the end of the decade.”

Pluralsight recently launched its AI Academy, to provide modular courses for professionals looking to deepen their understanding of the field. But the optimism of training providers such as Ellis stands in contrast to the actions of many UK businesses.

According to the Learning and Work Institute, an independent policy and research organization, UK employers spend half as much on training as their EU counterparts.

This is part of a longer term trend: the Department for Education found that employer-reported investment in training has declined each year since 2011, according to its Employer Skills Survey. When it comes to technology, only 6% of firms provided formal, digital skills training in the last year.

Some of this is understandable, given economic headwinds. But, as Nimmi Patel, associate director for policy at industry trade body TechUK tells ITPro, this is also a missed opportunity.

“Economic uncertainty doesn’t weaken the case for tech skills, but strengthens it. Companies that continue to upskill and retrain their workforce build resilience,” Patel explains. “Organizations that invest now are better equipped to respond to changing market demands.”

But this is of little comfort to industry professionals whose employers have cut back on training budgets, or struggle to find an early career job in the industry.

“Continued layoffs and hiring slowdowns in the tech industry have created a more competitive job market, particularly for entry-level roles,” concedes Ellis. Hiring at large tech companies is down 50%, she says, and 30% at start ups. “At the same time, organizations are shifting their strategies, reporting that upskilling existing employees is more cost effective than hiring new talent.”

Alexia Peterson, SVP International at publisher and training provider O’Reilly Media, agrees.

“Redundancy pressure is definitely accelerating the shift to skills-first learning in the UK,” she tells ITPro. “People are increasingly aware that employability now depends on keeping pace with fast moving areas like AI, cybersecurity and cloud.”

Sectoral shifts

All of this is shifting both supply and demand for training. According to Ellis, job security (or a lack of it) is a big driver for learning. Pluralsight believes that 65% of workers are considering reskilling, in response to job market conditions.

At the same time, training providers in both the commercial and public sectors are changing their offerings. Vendors, especially in cloud technology and cybersecurity, continue to invest in free to use training. Universities and paid-for providers are moving towards shorter, modular courses and microcredentials professionals can use to build up a qualification over time.

Munster Technological University, for example, started with a cyberskills programme five years ago and is adding courses in AI and cloud computing. As George O’Mahony, head of computer science at the university explains, students often take a short course or microcredential to see if the topic, and course, is right for them.

“Short-form courses are quite good to bridge an initial gap, and see if they like that kind of content,” he tells ITPro. “A lot of them might come back and jump into a part-time bachelor’s or MSc degree programme.”

Vitally, though, the training is both “100% online”, and practical: the university runs live, online lectures but also cloud-based, practical labs and cyber ranges. This ensures students can fit study around their work and home commitments, and ensure they build up experience. O’Mahony says this is essential, particularly if professionals are organizing their own learning.

Long-term skilling trends

And the shift to self-directed, and even self-funded, learning could be a longer-term trend across the technology industry.

The need for continuous professional development (CPD) is not new. But technology professionals are looking to both deepen their technical knowledge, and broaden their skills in areas such as management.

“The main motivation is keeping up with technological advancements, so they remain relevant, differentiate from others, and include proof, in the form of certifications, on their CVs,” Chris Dimitriadis, chief global strategy officer at security body ISACA, tells ITPro. “To be successful, one needs to adapt.”

But it is not just down to individuals to invest.

“The gap between what organizations need and the skills their teams currently have is significant, and growing,” he warns.

And businesses are taking a risk, if they rely on their employees to organise, and potentially fund, their own training. This is all the more so in areas such as security and AI.

Businesses are taking a risk if they rely on their employees to organize, and potentially fund, their own training. This is all the more so in areas such as security and AI.

“One of the biggest risks now is the AI trust paradox. People are using AI confidently, but often without the understanding to question what it’s producing,” warns Greg Hanson, head of EMEA at Informatica from Salesforce, a data analytics vendor.

“A lot of organizations have rolled out AI in low-risk areas, and are now being pushed to do something more transformative,” he tells ITPro. “But they don’t yet have the skills and data foundations in place to move forward with confidence.”

If businesses want to capture the benefits of new technology in a safe and secure way, then they need to invest in their people too. “You can’t outsource judgment to AI,” Hanson warns.

Nine-in-ten women leave the tech sector after ten years, taking vital skills and expertise to other sectors like finance and professional services.

That's according to new research from Akamai, which found that women are leaving tech roles at a pivotal point in their careers, prompting calls to offer better pay, career progression, and flexibility to buck the trend.

The survey of 1,500 women in the UK showed that 55% of women leave tech roles or tech companies after five years of being in the industry, with 87% departing within ten years.

They largely head to finance, education, professional services and healthcare, the report said.

"We lose women from cybersecurity at the exact moment their expertise becomes most valuable," said Zoe Mackenzie, President of Women in CyberSecurity UK. "This isn’t a pipeline problem; it’s a leadership one."

Why women leave tech

According to Akamai, more than a third left by choice and did not want to return to tech, while 31% said they left mostly by choice and now preferred their current situation.

The women polled said they departed the tech sector largely because they didn't feel a sense of belonging, cited by 52% of respondents.

Notably, a lack of gender diversity in company leadership was highlighted by 40% of women polled, suggesting drastic changes to corporate culture are needed to prevent continued attrition.

The poll was split into two sections: women who had left tech, and those who had left but then returned.

Four-in-ten women who had departed the sector said they would come back under the right conditions, notably flexible working arrangements, hybrid working, and improved work-life balance.

That echoes previous research that suggests half of women who left the tech sector did so due to conflicts with caring commitments, though it's worth noting hybrid working and other flexible arrangements are widely popular regardless of roles or gender.

Of those who had come back already, more than half said they were motivated by a higher salary, while four-in-ten said they needed better work-life balance and clear career progression.

"The findings provide a valuable picture of what mid‑career women are looking for in order to return to tech, and it’s encouraging to see that the majority could be persuaded to come back under the right conditions," said Hazel Little, the CEO of Career Returners.

"Progression pathways are crucial for retaining talent, but equally important is ensuring that women who want to return have clear, supported ways to re-enter the sector in the first place. When employers build both return pathways and progression pathways, they create an environment where women can come back, grow and stay."

Tech sector attrition

The Akamai report marks the latest in a string of studies pointing to a concerning trend of female attrition in the tech sector.

According to last year's Lovelace Report, between 40,000 and 60,000 women leave the sector each year. This level of attrition has a direct impact on economic growth, the study noted.

At current rates, the departure of women costs the UK tech sector an estimated £2 billion ($2.7bn) to £3.5 billion ($4.7bn) each year.

Other reports, meanwhile, suggest that women leave the tech sector at twice the rate of their male colleagues.

The gender diversity gap in tech leadership has become a recurring talking point for the sector. Akamai’s study specifically highlighted this issue as a key factor in why women leave the sector, and that tracks with figures on diversity rates in higher-level roles.

Between 20% to a quarter of the UK tech sector is made up of women, yet that isn’t reflected in leadership positions. Official government figures suggest women account for just 5% of leadership positions across the industry.

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

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

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

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

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

Measuring the impact of AI on jobs

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

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

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

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

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

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

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

Tech salaries in the UK

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

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

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

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

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

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

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

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

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

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Unified IT management software provider JumpCloud has announced the appointment of Shianne Sampson as its new chief revenue officer (CRO).

A recognized revenue executive with a people-first approach, she brings more than 20 years of leadership experience alongside expertise in scaling sales and customer teams through phases of rapid transformation.

In her new role, she will oversee the vendor's global revenue growth while helping to expand its mission of intelligent, secure IT.

JumpCloud provides a unified IT management platform that brings together identity, device, and access management to help organizations secure users and systems at scale. The solution is designed to reduce operational complexity while supporting modern IT environments and AI-driven workflows.

In an announcement, JumpCloud CEO Rajat Bhargava said Sampson's appointment will support the firm's growth ambitions, bringing deep operational expertise and a strong focus on leadership development.

"As we define the future of intelligent, secure IT, her ability to build durable, repeatable engines for growth is precisely what JumpCloud needs," he commented. "Shianne doesn't just manage revenue; she builds the systems that make sophisticated security simple and accessible for our customers."

Throughout her career, Sampson has successfully steered high-growth organizations through periods of rapid transformation and developed extensive expertise in scaling complex SaaS platforms.

Most recently, she served as CRO at Eventbrite, where she unified sales and operations to drive significant retention, and has also held leadership positions at New Relic and Zenefits. Earlier in her career, she served as senior sales manager at Yelp, where she founded Yelp University.

Commenting on her appointment, Sampson praised JumpCloud's "high-integrity leadership team" as well as the firm's approach to identity and device management.

"There is a massive opportunity to win the unified platform narrative," she said. "My goal is to help our customers consolidate workflows into a single console for measurable time-to-value, while building a crisp, global playbook that allows us to grow faster without adding unnecessary complexity."

The news follows JumpCloud's recent appointment of Roland Palmer as chief information security officer (CISO). The vendor said both hires will strengthen its leadership bench as it expands at pace in enterprise and global markets.

Communications platform-as-a-service (CPaaS) provider Nebula has announced the appointment of Eric Dodd as its new chief financial officer.

A seasoned industry veteran, Dodd brings more than 15 years of leadership experience across finance, HR, legal, and compliance within growth-stage technology companies.

Prior to joining Nebula, he served as CFO at K3 BTG and Attraqt, where he played a key role in scaling operations and driving financial strategy. He began his career as a chartered accountant with Deloitte in London and holds an MBA from London Business School.

In his new role, he will lead the firm's financial strategy and operations as it looks to sustain growth and expand its platform capabilities.

In an announcement, Nebula CEO Howard Stevens said Dodd's extensive experience will help the company build on its recent momentum and shape the next phase of its expansion.

"Eric's expertise and proven track record make him a fantastic addition to our leadership team," he commented. "His arrival comes at a time of tremendous growth for Nebula, and we are excited to see the impact of his guidance across our financial and operational functions."

Nebula's CPaaS platform is designed to support enterprise communications by enabling organizations to deliver voice, messaging, and customer experience services through a unified, cloud-based environment. The platform underpins the firm's growing ecosystem of more than 700 channel partners and supports over 200,000 active daily users.

Over the past year, Nebula has continued to invest in its proprietary technology and operational capabilities, releasing more than 50 new features and 100 software updates.

The company said its latest appointment will now further strengthen its executive leadership, reinforcing its commitment to strategic growth, operational excellence, and market innovation

Commenting on his new role, Dodd said he is looking forward to contributing to the company's financial and innovation strategy.

"Joining Nebula presents an exciting opportunity to contribute to a business with strong growth momentum and a clear vision for innovation," he said. "I look forward to supporting the company's continued success and delivering value to its customers, partners, and stakeholders."

The government has launched a new multi-million pound scheme to get more women into the tech industry.

The £4 million program, which will kick off later this year, aims to provide 300 women with coaching and support with interview preparation, as well as paid work placements of at least six months at SMBs across the country.

Meanwhile, a new “returnship” pilot scheme aims to help software developers re-enter the workforce via senior tech roles in government after time away.

Piloted with the Home Office and the Ministry of Justice, it will be open to any software developers who have been away from work for 18 months or more – such as women who have been caring for children.

"Women aren’t being given a fair shot in tech – whether that’s getting into the sector, staying in it, or returning after time away bringing up their families," said technology secretary Liz Kendall.

"If we don’t address these issues now, we’ll still be having this conversation in decades’ time, and that isn’t good enough."

Encouraging careers in tech

Meanwhile, a new TechFirst Girls Competition will be rolled out to girls across the country later this year, with the aim of getting more girls to consider a future in tech.

Rolled out in partnership with IBM, the competition will see thousands of 12 and 13 year old girls compete in challenges related to AI and coding.

The projects build on the launch of the Women in Tech Taskforce in December, which brings together leading female tech figures with the aim of getting more women entering, progressing, staying, and leading in tech.

"These aren’t warm words - they’re real jobs, real placements, and real routes back in through a door that has been too hard to open, for too long," said Kendall.

"But we’re not just fixing today’s problem. Through the Women in Tech Taskforce, I want to make sure women aren’t just entering this sector - they’re shaping it. Co-creating the technologies, the culture, and the future of an industry that for too long has been built without them."

New proposals for career support

Separately, Kendall has proposed a new voluntary charter for the research community aimed at making it easier for women to build research careers.

This includes commitments to paid maternity leave for PhD students, more help to return to work, and more flexible working options.

The government will more than double its support for the Daphne Jackson Trust from £1.7 million to £4 million per year, boosting the number of fully-funded fellowships it offers women from 15 to 25.

Similarly, the Trust will launch up to 15 new Research Technical Professional Fellowships per year, a program for retraining and reskilling research technicians who are vital to UK science as they return to R&D.

"Women scientists and researchers are responsible for driving some of the most important breakthroughs that are improving lives for people right across the country. Yet too many see their career ambitions delayed or even halted by vital responsibilities like raising a family or caring for a loved one – trade-offs that should never have to be made," she said.

"The charter will set clear expectations on funders of research – they must act quickly and decisively to give more women the backing they need to resume their studies, whether through greater maternity support or flexible working."

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Positions specializing in AI training are the single-fastest growing role globally, according to new research.

Figures from Deel’s annual State of Global Hiring report show demand for AI training roles surged 283% worldwide in 2025.

The report noted that AI training is a new, expansive profession that barely existed two years ago. Yet there are now more than 70,000 workers training AI systems across more than 600 organizations.

The scope of responsibilities varies wildly, the study noted, ranging from basic data annotation to expert-level feedback in areas such as language translation, economics, and medicine.

“AI needs human touch and the job market has clearly responded,” the report noted. “Tapping into the global talent pool brings in native speakers and subject matter experts.”

Notably, pay rates for these roles vary considerably. While 30% of trainers earn between $15 and $20 per hour for annotation work, 19% earn between $50 and 75 per hour, and 6% earn more than $100 per hour for particular expertise.

Demand for AI trainers is highest in the US, the study noted, where 58% of the world’s total are based. Other key markets include India, accounting for 7.2% of roles, followed by the Philippines (4.6%), Canada (2.1)%, and Kenya (1.7%).

Gender pay gaps are already present in what is an emerging field, according to Deel.

Male AI trainers in the US earn a median of $50 per hour, for example, while their female counterparts earn just $30 per hour.

AI talent flocking to the UK

Deel’s annual report also highlighted the growing appeal of the UK tech sector, which is now among the top hiring markets globally.

The drift of remote workers out of London has reversed, the study showed, and they're now returning.

There was a similar shift seen in France and in the US, where workers are now as close to cities like New York, Los Angeles, Chicago, Houston, and San Francisco as they were in 2021.

“UK talent is gravitating back toward London, and global employers are following. The renewed pull of the capital is a major reason the UK is leading the world in start-up hiring,” said Lauren Thomas, economist at Deel.

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Only four-in-ten UK businesses have given their staff comprehensive AI training, despite rising investment in the technology.

SAP's Value of AI in the UK: Growth, People & Data Report, launched in partnership with Oxford Economics, found businesses are failing to equip employees with the skills to use AI responsibly.

More than two-thirds (68%) said they believed their staff use unapproved AI tools – so-called shadow AI – at least occasionally as part of their day-to-day work. Katie King, CEO of AI in Business, said while these figures raise concern, there are some silver linings.

“Shadow AI isn’t a sign of resistance, but a sign of enthusiasm. Employees are hungry to use these tools, but this eagerness is seeing some move faster than their organizations can support them. This energy is a huge opportunity for UK businesses, if it’s guided in the right way," she said.

"The answer isn’t to dampen this enthusiasm, and the solution is reasonably simple. Give people access to approved tools, clear guardrails, and role-specific training. When staff understand how to use AI responsibly, it becomes a source of innovation and confidence rather than risk.”

While leaders believe AI can deliver returns faster than other technologies, the report found just 7% of organizations have adopted an enterprise-wide AI strategy.

Similarly, seven-in-ten businesses have begun reskilling or upskilling staff to help close the emerging AI skills gap, yet many harbor concerns that progress is falling behind current rates of adoption.

“AI is fast becoming a key driver of growth for UK businesses. When organizations make the technology part of their long-term strategy, they can innovate faster, scale with confidence and compete globally," said Leila Romane, managing director of SAP UK&I.

"It’s essential to get data foundations right, while giving employees the training, tools and space to experiment safely. That’s how businesses create a culture of responsible AI adoption from day one."

AI spending is surging

According to the report, UK businesses are on average spending £15.94 million on AI this year, with companies expected to increase their investments by an average of 40% in the next two years.

They're also expecting strong returns, with ROI forecast to almost double from 17% in 2025 to 32% in 2027. This ROI increase comes as many businesses begin to unlock significant value from the technology.

Firms reported seeing better insights (36%), stronger customer engagement (34%), and faster time-to-value (31%) with AI over the last year.

However, only 7% of UK businesses are investing in AI based on strategic, holistic prioritization, with most relying on ad-hoc pilots or department-led projects.

SAP warned this is creating a fragmented approach to adoption, which is holding back many businesses.

"Too much of today’s spend is fragmented and ad-hoc. Data readiness is inconsistent, particularly in business functions including finance, legal, and HR. Employees are eager to use AI, but training and governance frameworks have not caught up, creating risks around shadow AI," the report concludes.

"UK organizations are committing serious investment to AI, but without a long-term, robust strategy that brings together data, people, governance, and the wider ecosystem of partners, they risk missing out on the full value of the technology."

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The notion of AI replacing human labor is decades old, with academic Herbert A Simon first musing in 1965 on the idea that AI could one day perform "any work a man can do". Since then, this concern has permeated throughout society – and one that’s become more realistic than abstract in the last 10 years.

In 2017, as Google first outlined its transformer architecture, PwC estimated that 30% of jobs could be automated by the middle of the next decade. While that hasn't panned out, AI is progressing at such a pace that we could, for the first time in human history, be on the cusp of seeing this play out in a meaningful way.

Many fear that a permanent reduction in entry-level roles is underway, with IDC research showing that 66% of enterprises expect entry-level hiring to slow. That's in addition to 91% reporting that roles are already changing or vanishing due to AI. The chief reason is clear: short-term cost savings. But at what long-term cost?

Experts tell ITPro they fear a number of unintended consequences, chiefly that today's pullback in entry-level workers risks hollowing out the core of the most dynamic businesses, threatening their long-term survival.

A bleak picture for tech juniors

By any metric, the rise of generative AI has coincided with a significant reduction in entry-level roles and job vacancies more generally. Anecdotally, a long line of companies have announced they're slowing down hiring or taking an AI-first approach to plugging shortfalls, including HP, IBM, Amazon, Salesforce, and Klarna – with the caveat that Salesforce has since rowed back slightly, as has Klarna.

A wealth of research points to a general trend. The UK's Institute of Student Employers (ISE) reported that graduate hiring fell 8% year-on-year between 2024 and 2025 – the first time this has happened since COVID-19.

King's College London (KCL) also found that companies in which workplaces are exposed to AI reduced employment by 4.5% on average, with the effects concentrated on junior positions – which fell by 5.8%. Highly exposed firms became 16.3% less likely to post new vacancies, while technical roles like software engineers and data analysts saw the steepest declines in listings. This represents a fundamental reshaping of the workforce composition.

We can compound this with British Standards Institute (BSI) research that revealed that 41% of business leaders globally said that AI allows for headcount reductions. Nearly a third (31%) also said their organization explores AI solutions before considering hiring a human.

One of the starkest signifiers, however, is a viral infographic that showed the number of US job openings decoupled from the value of the S&P500 when ChatGPT launched in 2022. When you consider that the number of people of working age overall has also increased during this period, it paints a stark picture. But are these trends correlation or causation?

Is AI driving a great workforce recomposition?

Author of the KCL research Bouke Klein Teeselink is a lecturer in philosophy, politics and economics at the university. He tells ITPro that while it's hard to say for certain based on the available evidence, he believes part of the reduction is definitely causal. "Entry-level jobs are more easily automatable than senior jobs, as senior jobs rely much more on tacit knowledge of the firm and production processes (which are not codified, and therefore not part of the training set of AI), and are more relationship-focused," he says.

Others also gravitate toward causation including AI consultant Chris O'Halloran, who tells ITPro: "I'm seeing it at multiple levels. Startups are launching as solo founders powered by AI, and they're growing faster than before. Typical high-growth start-ups would grow 2% week on week. Now they average 10%, with fewer people.

"A core focus of the companies I work with is building AI agents that augment their workforce. Often, these roles won't be replaced through natural attrition, where AI can do the work. The uncomfortable truth is that entry-level work is often basic repetition: doing research, data entry, copying across systems. All things AI does really well. It comes down to economics."

One expert took exception to this thesis, however, offering a different perspective. Josh Bersin, global industry analyst and CEO of The Josh Bersin Company, said that hiring in general has slowed and that entry-level jobs are now extremely valuable, given that younger workers are more likely to be fluent with AI than older workers who didn't grow up using it.

"We have ex-school teachers, young business graduates, and young HR staff in our company who are outperforming many senior people just because of their ambition, open-mindedness, and willingness to learn.

"Companies and teams value young, fresh-thinking employees because they bring new ideas, understand the needs of younger customers, and are eager to learn and contribute. We speak with HR leaders all over the world, and even as overall hiring slows, they’re still hiring – and always will hire – entry-level workers."

Why are businesses turning to AI in force?

To understand what is happening, we must also understand why. The chief driver will be cost savings, naturally, with businesses keen to pursue this after a bitter few years hit by crisis after crisis and an unsettled economic picture. But businesses stand to gain other benefits from aggressively turning to AI in this way.

"Aside from cost, companies can gain consistency, speed, and 24/7 output from AI-driven systems," says Ebenezer Allen, CEO at Westlink Academy, a USDOL-Registered Apprenticeship Program and training provider focused on preparing adult learners and early-career professionals for in-demand roles in cybersecurity, cloud, and IT. "There’s also the ability to scale operations quickly without traditional hiring bottlenecks. For highly regulated sectors, AI also provides an opportunity for built-in compliance or auditability – if implemented well."

Another benefit, O'Halloran says, is the capacity to unlock entirely new revenue streams. "An AI agent works 160 hours a week, not 40. This unlocks work and tasks that were previously non-economical. They now become profitable," he explains.

"One client had a regional product they couldn't sell. It wasn't economical to reach with human sales reps. But the AI sales agent we built, modelled on their top performers, was able to take that 30% of traditionally unsold inventory and work it 24/7. It's now being sold autonomously with AI. That's not a cost saving, that's new revenue."

Teeselink adds that there are tasks at which AI is simply better than humans, and that will render massive productivity gains. In his own work, AI assists him in writing, finding literature, coding, ideating, and many other tasks. None of these are fully automated, he adds, but he performs all of them much faster and potentially better with AI than without.

What are the implications for the future workforce?

With any new profound technological shift, there is the risk that short-term benefits come at the cost of long-term stability and longevity – especially when you reduce today's junior workforce. This is the warning that Liz Eversoll, CEO of Career Highways, an upskilling and recruitment company, is keen to sound.

"The real risk isn’t that AI eliminates human contribution – it’s that companies unintentionally erode their future talent pipeline by removing the very roles where emerging employees typically learn, stretch, and build foundational skills.

"At Career Highways, we see every day that the organizations thriving through this shift are those using AI to augment skill development – not replace it," she says. "They’re moving toward dynamic job architecture and skill intelligence so they can understand which skills are impacted by automation, where human capability is still essential, and how to guide people into higher-value roles with clarity and confidence."

'Erosion' is a notion that frequently comes up in ITPro’s conversations with the experts – especially in the sense of long-term loyalty and the notion of company values being cultivated over many years. Allen, for example, describes entry-level employees as "energetic connectors" across departments – asking naïve questions that lead to innovation and challenging assumptions. Lose them, he says, and you lose part of your feedback loop: "You can’t automate ambition. And if people can’t enter the system, they won’t stick around long enough to lead it."

Kyle Elliot, founder of Tech Career Coach and executive coach at CaffeinatedKyle, said that talent pipelines are certainly at risk of vanishing. "Entry-level positions are about more than completing tasks. They’re crucial for developing future talent," he says. "Early-career employees learn key skills and gain experience that shapes their long-term careers. Without these roles, they miss opportunities to build foundational expertise."

Can we avoid the talent pipeline time bomb?

AI usage will ratchet higher and higher, if the research is to be taken at face value, with AI in today's startups and enterprises increasingly consuming workloads that humans once considered critical to their roles. But the talent pipeline 'time bomb' – in which companies begin to lose their identity due to the increasingly limited stock from which to draw the seniors of tomorrow – need not be set off if AI is approached in a smarter way.

O'Halloran is unsure ultimately where many seniors of tomorrow will come from, but offers two possibilities: the first is that organizations invest in internal AI-accelerated development in which training programs compress years of training into months. The second is that young people may be forced into starting businesses and learning by doing before returning to the corporate world with experience in later life.

"I think credentials will matter less," he says. "It'll be more about demonstrated competence with key skills: strategic thinking, curiosity, creativity, and culture. Higher education needs to evolve. Universities need to bring practical AI into their curriculum."

Teeselink does not feel that this problem will resolve itself, due to a phenomenon that economists call 'poaching externality' – where some companies train and upskill juniors only for another, much larger organization to come along and poach them. There must, therefore, be public policy shifts that incentivize companies towards hiring juniors and helping them develop productive skills in the future.

"Imagine that a firm recognizes that it needs experts in the future. Why does it not simply hire juniors now to train them, even if the traditional junior-level tasks are automated?" he asks. "The reason is that the person cannot commit to staying at the firm once they have received their training. In other words, another company that did not help their juniors develop expertise can simply outbid the company that did the training, and hire this person once they become an expert."

Meanwhile, with AI uptake accelerating, Eversoll says this need not be a cause for panic – rather an opportunity. "If companies let AI shrink early-career hiring without redesigning transparent, skill-based routes into the organization, they will feel the talent shortage most acutely five to seven years from now in leadership, technical depth, and culture-carrying roles," she says, "But there’s an upside – AI also gives us the intelligence to rebuild the pipeline in a healthier way. With the right skills data, employers can map new on-ramps, democratize mobility, and create advancement options for individuals whose roles are changing.

"This is a moment that calls for redesign, not retreat. When organizations invest in skills visibility and internal mobility, AI becomes an engine for growing talent — not a barrier to entry."

The UK government wants to train 10 million people in AI by 2030 in an ambitious expansion of a nationwide upskilling program.

Under the plans, every adult in the UK will be eligible to take free courses to gain practical AI skills.

The announcement builds on a previous pledge made in June 2025, in which the government teamed up with industry giants to launch the AI Skills Boost scheme.

Initially, the aim was to train 7.5 million people across the UK to capitalize on the generative AI boom.

Courses run through the expanded program have been curated by industry stakeholders and align with Skills England’s AI foundation skills for work benchmark.

"We want AI to work for Britain, and that means ensuring Britons can work with AI," said Liz Kendall, secretary of state for science, innovation, and technology.

"Change is inevitable, but the consequences of change are not. We will protect people from the risks of AI while ensuring everyone can share in its benefits,” she added.

"That starts with giving people the skills and confidence they need to seize the opportunities AI brings, putting the power and control into their hands."

Inaugural partners on the AI skills Boost program included a range of tech giants, such as Amazon, Google, IBM, Microsoft, Salesforce, and SAS.

They will now be joined by Multiverse, Pax8, TechUK, Cisco, Cognizant, and more.

Sarah Walker, CEO for Cisco UK&I, said the networking giant is “ pleased to support the government’s expansion of its AI upskilling mission”.

“We are proud to help ensure that communities in every corner of the country can benefit from technology and innovation. AI presents an enormous opportunity to unlock human potential, but only if we improve basic digital literacy and support people with AI skills across the UK,” she said.

“The AI Skills Boost is core to raising living standards and generating economic growth opportunities for the nation."

How to get involved in the skills push

The nationwide training scheme will be open to all adults online, the government noted, with some courses taking as little as 20 minutes.

Participants enrolled in these courses will be taught how to use basic AI tools in the workplace, such as using AI for drafting text, creating content, or completing administrative tasks.

“This training will give both workers and employers confidence in their new skills, and set standards for what good AI upskilling looks like,” the Department for Science, Innovation and Technology (DSIT) said in a statement.

Local government and NHS employees will be among those first to benefit from the expanded training scheme, the government said.

Addressing future challenges

Alongside the expansion of the AI skills program, Kendall announced the launch of the new AI and the Future of Work Unit to help the country remain “front-footed” in addressing future skills challenges.

The new unit will be led by a panel of experts from businesses and trade unions to examine the potential impact of AI on the economy and labor market.

Long-term, the hope here is that the unit will help guide policymakers in adapting to technological changes.

“It will ensure the AI transition boosts economic growth, supports workers to adapt, protects communities from the mistakes of past industrial change, and delivers a fair, dignified future of work for everyone, where people are supported into better jobs in a more productive economy,” the DSIT said.

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Lloyds Banking Group has announced plans to train every employee in AI skills in a bid to streamline adoption of the technology across operations.

The bank’s new AI Academy, launched this week, aims to provide “practical AI skills” for 67,000 staff “no matter their role or level”.

As part of the scheme, employees will gain access to interactive modules, podcasts, articles, short courses, and additional opportunities for community-based learning.

“Learning is tailored to the different ways colleagues use AI from AI Users to AI Leaders, Builders and Enablers,” Lloyds said in a statement.

“To begin, all 67,000 colleagues will complete a short module on Working with AI Responsibly, ensuring safe and ethical use aligned with Group standards.”

Ron van Kemenade, chief operating officer at Lloyds Banking Group, said the skills program will help prepare staff for AI adoption across the organization, ultimately streamlining the roll-out of the technology.

“Scaling AI is about getting real use-cases into production so we can simplify processes for colleagues and deliver more personalized services for customers,” he said.

“By investing in the skills of our people, we can do this responsibly and at pace, improving service today and building the foundations to scale new innovations in the future.”

Lloyds targets complete skills overhaul

Lloyds anticipates a wholesale transformation of skills across the organization in the coming years, noting that by 2030 “most of the skills used today will have evolved”.

The financial services giant said it projects around 60% of the workforce will need to reskill as a result of AI integration, yet literacy in this area is lacking.

Lloyds said it aims to upskill 100% of colleagues by the end of 2026 alone – a bold target, but one which it said will help deliver marked benefits both for customers and employees alike.

“Upskilling our colleagues is central to how we transform. The AI Academy gives every colleague practical, hands-on tools to use AI responsibly in their day-to-day work,” said Sharon Doherty, chief people and places officer.

“By investing in our people, we’re strengthening the skills that matter most, so our teams can deliver for customers with confidence in a workplace already supported by AI.”

Lloyds has long-running experience with machine learning and AI innovation, having first implemented an ML-powered savings tool for customers in 2021.

Last year, the company put 50 generative AI use-cases into full production, ramping up adoption of the technology across core operations, while unveiling plans to deploy an agentic AI-based financial assistant for over 20 million customers.

Responsible AI

A key focus for the bank lies in responsible and ethical development. In 2022, it became the first in the UK to hire a dedicated responsible AI lead, for example, and its Responsible AI programme helps guide internal development of the technology.

All told, the bank has seven core AI ethics principles. These are implemented through a range of overlapping schemes, frameworks, and teams, including:

• The Lloyds AI Assurance Framework
• A dedicated Data & AI Ethics Committee (DAIEC)
• The Lloyds Risk Mitigation Template
• A “central repository” of AI risk guardrails that staff must adhere to

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It’s been 15 years since the term “gig economy” was coined by then editor of the New Yorker, Tina Brown, to describe a new style of flexible workforce behavior – taking on short-term or casual roles as contractors and freelancers.

At the time, the world was in the midst of the 2009 financial crisis, which caused a global recession and put immense pressure on leading economies. Redundancies from full-time roles soared, leaving many former employees looking for new ways to make a living.

Interestingly, some people date the term “gig economy” to the 1910s when it was used by jazz musicians to explain how they moved from job to job. But since Brown’s usage, the term has evolved to cover everything from food deliveries and store shifts to IT support and creative skills.

One major industry change ushered in by the gig economy was the emergence of door-to-door travel, especially in big cities, with the likes of Uber and Lyft redefining the industry practically overnight. Daniil Petin, vice president of mobility at ridesharing and urban services platform inDrive, which now operates across 46 countries, praises the concept for bringing new freedoms and choices to so many everyday people.

“The gig economy has provided new and flexible work opportunities to those who previously struggled to find and hold down a traditional ‘9 to 5’ job due to their personal circumstances or location,” says Petin.

“By giving flexible options, it has brought many people into the formal economy, who might have been previously excluded. This influx of new workers has also indirectly supported innovation across many industries.”

Incoming growth worldwide

Even now, the gig economy continues to expand at pace. Tracy Stanton, senior vice president of client services EMEA at integrated workforce platform Magnit, believes this should come as no surprise given the turbulent times we currently live in.

“As the global economic outlook continues to look shaky, the use of contingent workers could be on the cusp of significant growth,” explains Stanton.

“Businesses are having to find a delicate balance between keeping costs under control, while focusing on long-term growth. As a result, two-thirds (65%) of businesses are set to increase their use of contingent workers to compete.”

According to Stanton, the UK’s IT and technology sectors are seeing a surge in demand for professionals with skills in AI and machine learning (ML). This aligns with the government’s ambition to position the nation as a global leader in AI’s potential.

“The ongoing talent shortage seen across industries has given workers new career advantages and flexibility,” Stanton adds.

“Rather than just being job seekers, they’re job choosers, with more control over their career paths than ever before. The sought-after skills of software sales, cloud services, and managed security reflect companies’ strategic priorities in navigating today’s technology-centric marketplace."

Some of these vacancies could be filled by tapping into markets across Europe. For example, Magnit’s own research shows Poland has an excess supply of more than 60,000 IT workers who could be hired to work remotely.

Magnit’s figures chime with what they are seeing at Harnham Group, the global leader in data and AI recruitment.

Kirsty Garshong, its UK contract director, says: “We’ve experienced a surge in demand for contractors over the last two years, with an approximate 50% increase in contract roles year-on-year; 12% of UK data teams are now contractors.

“This is largely due to businesses facing stretched budgets, but also because of a shift towards hiring for project-based work as AI projects proliferate.”

Finding the right fit

Garshong admits using contractors is not appropriate for all tech positions. “In a project such as building a data platform,” she adds, “it can take several months just to understand the inner workings of a business and to complete all of the scoping work required to begin data processes. Therefore, a short contract hire will be unlikely to be able to deliver the outcomes needed in that timeframe.”

There’s also the sticky issue of IR35 in the UK, which requires gig workers to prove they are not simply acting like normal full-time employees. But Harnham Group’s own survey of 3,500 data professionals globally revealed that 67% of UK respondents were contracted outside of IR35, up from 42% in 2023.

“Hiring someone on a short-term basis means that businesses do not have to budget for all of the costs that come with a permanent employee, such as benefits,” Garshong explains.

“If a company only has £60K available and there are 20 working days in a month, over a six-month period they would be able to hire someone at £500 per day and couldwork exactly to that budget without exceeding it.”

The gig economy also allows leaders to take on workers in a ‘try before you buy’ scenario, she says, especially important when many specific roles in AI are not cheap to hire.

“Due to the time-limited nature of contract work, individuals must feel confident in joining new teams, asking plenty of questions, and hitting the ground running,” advises Garshong.

“They must liaise across numerous teams in order to get to the root of any issues and identify where support is most needed. It can be challenging to build rapport with colleagues quickly, but doing so is critical in gaining the trust of team members and boosting workplace morale.”

Financing the future

Despite the celebrated flexibility, the gig economy has also been mired in controversy. Concerns over low pay and poor conditions, plus a lack of transparency and oversight, have been raised, while governments have faced issues collecting the right amount of tax from both workers and companies.

To make matters worse, a majority of gig economy workers report having issues accessing financial services, simply due to the nature of their work.

Recent research has found that financial institutions often lack access to the right data to ensure gig workers in the UK can utilize a wide variety of products, such as mortgages and loans.

The study by fintech startup Rollee found that two-thirds of gig workers (66%) had been denied a loan despite knowing they had a good credit score. It also found that 34% of financial institutions are more likely to approve an application from a PAYE worker compared to gig worker counterparts because they have greater transparency of their income and employment data.

Overall, 70% of UK gig economy workers struggled to get approved access to financial products in 2023, an improvement of just six percentage points over 2022 figures.

“This is having critical repercussions on the lives of many self-employed workers, causing them to face high levels of financial exclusion and being denied financial products despite having the necessary levels of affordability,” warns Ali Hamriti, co-founder of Rollee.

Darren Upson is vice president of global demand generation at Tipalti, which works with companies like Amazon, Twitch, Spotify, and Duolingo to help finance teams streamline payments to contractors, freelancers, and self-employed creators.

He agrees there is a problem and says: “There are many reasons why people choose gig economy work. However, a failure of the business model that remains prevalent is workers getting paid the right amount, and on time. Not doing so is a huge risk to the business model and puts retention of those workers in jeopardy.”

Upson argues this leads to poor payee satisfaction and the risk of workers moving to a competitor.

He adds: “The complexity associated with paying workers different amounts every month, based on the amount of work completed, is often where we businesses stumble – with late payments and errors being common when finance teams are processing manually at scale.”

“The future of the gig economy hangs on businesses making it a reliable money-earner for workers,” adds Upson. “Until we see more adoption of payment automation, wage woes will continue, and businesses will begin to see a smaller pool of gig workers.”

Managed security service providers (MSSPs) are a vital part of the cybersecurity ecosystem, often serving as the first, and sometimes the only, line of defense across multiple clients. Their role is also growing in importance, largely due to the persistent global skills shortage. However, new benchmarking data reveals blind spots that could limit their strategic value.

Hack The Box’s Global Cyber Skills Benchmark 2025 analyzed nearly 800 teams and more than 4,500 participants worldwide. While MSSP teams performed strongly in OSINT (64.5%) and forensics (62.8%), they lagged in preventive and offensive disciplines such as secure coding (18.7%), web security (21.1%), and adversary emulation.

The results, which were mapped to the MITRE ATT&CK framework, show a clear imbalance. Although MSSPs are great at detection and response, they are falling short in prevention and protection. Detection is obviously an essential skill, but it’s reactive only. As adversaries exploit AI automation, supply-chain vulnerabilities, and custom exploits, MSSPs risk the need to be more than reactive responders; they need to become active defenders of an organization’s resilience.

Scale vs depth

The MSSP operating model generally includes standardised tooling, multitenant platforms, and is built for speed and efficiency, but it lacks depth. The problem is that detection scales easily, while prevention needs context-specific expertise and secure engineering fluency. When it comes to prevention tools, they alone can’t compensate for missing skills. And that’s why capability, not tooling, is now the main differentiator for an MSSP.

Continuous Threat Exposure Management (CTEM), a concept introduced by Gartner, is a useful framework for proving resilience. CTEM reframes the narrative from “How fast can we detect?” to “How much risk did we actually remove?” It scopes attack surfaces, simulates threats, validates controls, and measures improvement.

For MSSPs, embedding CTEM helps to turn technical skills into business value. It will provide proof that cybersecurity investments are actually reducing risk exposure and by how much.

Skills as a differentiator

To close the gap between detection and prevention, MSSPs should start with data-driven workforce benchmarking. This will help ensure money spent on professional skills development delivers genuine operational impact.

Generic training won’t help. MSSPs need role-based learning paths aligned to core functions, such as SOC analyst, threat hunter, red team operator, and secure developer. Short, verifiable micro-credentials are also important to support continuous improvement.

The focus isn’t just about training. It is about implementing carefully planned upskilling and having the ability to prove capability to clients and boards alike.

MSSPs should also consider building industry-aligned capability pods, where there are specialised teams focused on vertical threat landscapes. A finance pod might prioritize blockchain and application security; energy and manufacturing pods could focus on ICS and OT defence; retail pods might tackle supply chain and web application threats.

These pods deepen contextual understanding of threats and help to strengthen protection. To avoid siloing skills, pod governance should include a process to ensure structured knowledge transfer and continuous feedback loops.

Offensive emulation and AI risk

Offensive emulation is one of the weakest areas for many MSSPs, with the benchmarking figures showing Pwn/exploitation solve rates averaging just 9.8%. Regular red teaming exercises and adversary emulation training will help improve and validate defences under real-world conditions and feed directly into CTEM metrics, turning simulations into proactive indicators of resilience.

MSSPs are early adopters of AI-assisted tooling, with solve rates in the benchmarking averaging 38.3%, which is above the global mean. But AI without a secure engineering discipline is a double-edged sword because it has the potential to accelerate vulnerabilities faster than they can be fixed.

To mitigate this, MSSPs must reinforce secure-by-design skills and integrate AI governance checklists into development and automation pipelines.

Speaking the boardroom language

Traditional SOC metrics like MTTD (Mean Time to Detect) or MTTR (Mean Time to Respond) do not accurately reflect investment value. Executives want to see measures of exposure reduction, such as fewer exploitable weaknesses, faster patching, and tangible improvements in secure coding proficiency.

By combining skills benchmarking with CTEM, MSSPs get the ability to communicate actual progress. For example: “Secure coding proficiency up 20%, with a 25% reduction in client-side web vulnerabilities.” That’s the kind of language that needs to be used in the boardroom to translate technical performance upskilling into trust in the MSSP’s business.

With the UK facing significant AI skills shortages, new research suggests a sharper focus on boosting workforce diversity will be required to meet government AI training plans.

A new study from BCS, the Chartered Institute for IT found the proportion of women working in tech has risen to 22%. While the marks a welcomed - albeit small - increase of 1%, the institute noted there’s still a lot of work to be done.

At present, 441,000 women work in specialist IT roles across the country, but BCS said this means roughly half a million women are still “missing” from the workforce if an equal gender split were present.

BCS said the report comes at a critical time for the UK tech sector, with enterprises ramping up AI adoption and the government pushing for a rapid roll-out of tools across the public sector.

Skills shortages have been a long-running challenge for the tech sector, and AI is now exacerbating the issue. In a report earlier this year, IT leaders said finding talent with AI-related skills was one of their leading challenges.

BCS is urging leaders from the tech industry and government to sharpen their focus on closing the gender diversity gap and accelerate upskilling plans laid out in the AI Action Plan.

Part of the government’s AI strategy centers around boosting skills to compensate for growing demand for AI talent. All told, the government aims to retrain or upskill around 7.5 million workers in AI with support from big tech companies.

With women still underrepresented in the sector, BCS said there is a “significant opportunity to ‘supercharge’ the AI capacity of the UK” by boosting diversity and recruiting from other minority groups in tech. This includes workers with disabilities and those over the age of 50.

Recommendations outlined in the BCS report include ensuring that digital literacy and computing skills are “embedded across the curriculum and support girls to stay engaged beyond the age of 14”.

Higher investment in programs aimed at supporting and promoting women to pursue tech careers, or return to the industry, is another key recommendation.

"Accelerating the numbers of women in tech roles is both a challenge, and an opportunity for every organization building Britain’s digital future,” said BCS chief executive Sharron Gunn.

“We cannot create high-trust, high-integrity AI systems if the profession behind them is missing out on the talents and perspective of half the population. Diversity is not a cosy add on but a prerequisite for safe, fair and innovative technology, especially in AI.”

Diverse teams build responsible AI

Aside from boosting broader tech sector diversity, research shows diverse teams will be crucial in AI development moving forward.

Analysis from IBM earlier this year, for example, found a lack of senior female leadership figures in business could hamper responsible development strategies.

69% of respondents told IBM they believe it’s important that female leaders are involved in AI decision-making, while 73% said improving female representation will help tackle AI-related gender bias issues.

Crucially, gender diversity in senior leadership has a tangible impact on economic performance, the study found.

Nearly three-quarters (74%) of respondents said increasing female leadership roles will be vital to ensure all corners of society will experience benefits from the technology.

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CompTIA has unveiled a new training program designed to help non-technical employees master generative artificial intelligence (AI) tools, citing a critical lack of formal training in the enterprise as a barrier to return on investment.

The computing association announced the release of CompTIA AI Essentials, an interactive learning resource aimed at knowledge workers and desk-based employees. The course focuses on practical, day-to-day applications of major AI platforms, including OpenAI’s ChatGPT, Microsoft Copilot, and Google Gemini.

The AI skills gap

The launch comes amid growing concern that while businesses are rapidly adopting AI tools, workforce proficiency is lagging behind. According to CompTIA’s own research, titled "AI's Impact on Productivity and the Workforce" (November 2025), just 34% of companies currently require AI skills training for their employees.

Simply purchasing licenses for AI tools is insufficient for driving business transformation, warns Katie Hoenicke, CompTIA’s chief product officer.

"Companies are in various stages of evaluation and experimentation with AI, but to truly glean the value and return on investment desired, it is important that they invest in staff training and consider the change management aspects of AI on staffing and job roles," she said.

"Simply providing employees with access to AI tools does not guarantee success. The emphasis needs to be on fluency and the acquisition of skills."

Course structure and security

The AI Essentials curriculum is designed to be concise, taking less than three hours to complete. It moves away from passive video watching and uses a "scenario-based approach" that forces learners to engage with realistic workplace challenges.

Key modules cover practical prompting techniques, which are cited as the primary hurdle for new users, as well as the critical ability to identify appropriate AI use cases in daily workflows.

Crucially, the course also addresses security and data privacy fundamentals, a major pain point for IT leaders worried about sensitive corporate data leaking into public LLMs (Large Language Models).

"The focus is on exactly what matters: foundational understanding of AI in workplace settings," said Henry Mann, senior director of product development at CompTIA, emphasizing the focus on immediate application.

"Our highly interactive, scenario-based approach ensures employees don't just passively watch. They gain real, job-ready competency in under three hours."

Verifying competency

To assist organizations in auditing their current skill base, the program includes a 15-minute competency assessment. This feature allows businesses to verify whether staff possess the necessary foundational skills.

It also offers a "test out" option for employees with significant experience with AI tools, ensuring that training time is not wasted on those who are already proficient.

The association stated that the ideal learner is "any employee in a knowledge or desk-based role," signaling a shift from CompTIA’s traditional focus on IT professionals toward the broader business workforce.

The release of CompTIA AI Essentials (V2) is available immediately for organizations looking to standardize their approach to AI adoption.

Academia finds itself in an odd spot when it comes to developing tech industry talent. On one hand, despite appearances to the contrary, universities are leaning further and further towards a business model that prioritizes profit over their original ideals.

On the other hand, there are a number of technology leaders who seemingly pine for the presumed comfort of academia, where theoretical thinking – rather than spreadsheets, budget burn rate, and headcount management – can be prioritized.

The tech industry isn’t unique in this regard; historians love becoming professors, journalists like to give guest lectures, and plenty of journeyman tradespeople find themselves teaching the next generation of carpenters, plumbers, and the like. This is nothing new, except the IT sector is seeing more and more people jump to a different ship.

But the most value can be found in academics bringing their unique perspectives to the enterprise, rather than the other way around.

As always with these sorts of things, the landscape is muddy. There are tech-focused academics like Georgetown University’s Cal Newport, who are leading professors as well as industry entrepreneurs. Newport runs a YouTube channel focused on productivity, but much of his work is underpinned by his background in theoretical computer science. Similarly, we’ve seen a number of tech-academics find audiences of various sizes. Some, like Lex Friedman, have established widespread podcast audiences interviewing the likes of Demis Hassabis.

In June, I wrote a piece that looked at why the sector can benefit from academic labor, what those academics need to know when making the shift, and what trends there are in terms of the need for academic expertise in the sector. In the last few months, those needs have come even further into focus. There are universities where the heads of educational development are AI evangelists. We now have a world, especially in North America, where academic budgets are under increasing pressure and no university in the world will turn down millions in research dollars. Well, wouldn’t you know it: tech companies love to be associated and integrated into the academic sector.

I think academic and theoretical thinking, at a time where projects and companies like Google DeepMind and OpenAI are in need of this sort of labor, are also a possible antidote to the extremes of the bootstrapped startup methodology.

While these self-starter views won’t suddenly disappear, and might even proliferate further in the short and medium term, the injection of talent that is rooted in research and a slower working methodology is vital.

However, as with any industry trend, there is a danger here. Just because an academic is at the proverbial decision making table doesn’t mean they will be listened to and it also doesn’t mean they won’t rally around a problematic premise. I’m sometimes uncomfortable with AI cheerleaders in academic settings because, thanks to being a specialist, they’re less likely to look beyond their own profession and look at downstream effects. For example, AI evangelists teaching educators how to use AI to create lesson plans – a hypothetical but all too realistic example – feel counterintuitive. If the same evangelist instead turned to teaching educators the difference between generative and traditional AI, or helping them find AI tools used for accessibility and inclusion, then I’m all for it. To rephrase an old real estate slogan: it’s all about context, context, context.

It’s here that academic thinking, rooted in the humanities as well as concepts such as ethical AI, can play a role.

What I find interesting is that the headlines are less and less about the students graduating university and becoming tech leaders, and more about long-time academics shifting over to entrepreneurship.

With the Gates and Zuckerbergs of the world, we were talking about drop outs – about how the academic environment just wasn’t the right space for these ‘visionaries’. Now, we’re seeing academic spaces, as they become more business development focused, building grounds for new technological talent. Yes, the plucky upstarts are still there, but so are middle-aged academics creating health-tech startups and business incubators. We have reached a stage where it’s incredibly attractive to tech companies for your resume to have an advanced degree and more academics could embrace this with a willingness to get out of the academic tower and muck about in the moat.

Amid increased return to office mandates, the pressures of turning a profit on tech companies both young and old, and the shifting dynamics of the IT industry, I foresee a far simpler problem that may arise: academics don’t tend to like meetings.

This might seem odd and reductionist – but there’s never been a more obvious boredom than the one that exists in a faculty meeting. Tech companies, and their leaders, are at their best and their worst when they have their hands on all parts of the business. Academics, on the whole, are also against meddlers. Most, even the incredibly practical ones, tend to want to be left alone to do their research and teach.

Whether academics succeed in the industry depends on whether they are actually allowed to do their work, whether they can adapt to a different schedule, and whether they can translate theoretical underpinnings into actionable paths for enterprises.

We need academics in the tech sector, just the same as we need industry leaders contributing to academic environments. To achieve this, however, we need an IT environment that is welcoming to this shift. Expecting a square peg to fit in a round hole is not going to work, but neither is egotistical pandering. Part of the success of the sector is when there is compromise.

Academics are there to provide a foundation and at a time of seismic change, it’s about time we saw a little bit more of their expertise. It’s often historians who sound the alarm when something is going awry. Here’s hoping that it can be those steeped in historical knowledge who can help the industry avoid some of the worst pitfalls the future has to offer.

Infosys co-founder NR Narayana Murthy called for Indian workers to adopt a 70-hour week last year, but he thinks that’s still not enough and wants to take things further.

Speaking during a recent interview, Murthy called for an increase in working hours from 70 to 72. That number represents the total hours worked by those on the infamous '996' schedule, which involves working from 9am to 9pm, six days a week.

This approach, Murthy noted, appears to be the ideal format for enterprises to drive innovation, maximize employee productivity, and essentially represents real “hard work”.

“No individual, no community, no country, has ever come up without hard work,” he said. “When I say hard work, not going to the office and sleeping there. When I say hard work it means hard and smart work.”

While Murthy is keen on the 996 approach, it’s not quite all it’s cut out to be in terms of workforce productivity. The practice was widely employed by businesses in China, but was banned by lawmakers in August 2021.

Research from the World Health Organization found longer work schedules have a serious negative impact on both physical and mental wellbeing for employees.

Those working more than 55 hours a week were linked with higher health risks compared to those working a standard 35-40 hour week, for example.

Not Murthy’s first rodeo

This isn’t the first time Murthy has advocated for longer working hours, or courted controversy on working practices. When he called for younger workers to up their hours to 70 last year, his comments sparked a national debate over working conditions and the potential long-term effects of this approach.

Those comments came hot on the heels of an interview with CNBC in which he criticized the concept of work-life balance and slammed the country’s shift to a five-day work week in 1986 as bad for the economy.

Despite Murthy’s views on the matter, a string of studies in recent years have found shorter working weeks actually make employees more productive.

A trial scheme of a four-day work week in Iceland, for example, was found to have marked benefits for employees, including higher mental and emotional wellbeing, with researchers hailing the pilot as a “real success story”.

Moreover, productivity and economic output actually increased at companies adhering to this schedule. A similar scheme at Microsoft Japan resulted in a 40% increase in output off the back of a four-day work week.

Long hours in tech are becoming a trend

While the 996 trend was outlawed in China, in big tech it’s become somewhat of a trend in recent months. A recent investigation by the New York Times showed this working practice has been gaining traction among some “hustle culture” entrepreneurs in Silicon Valley.

While the publication noted that entrepreneurs boasting about their own 9-9-6 approach on social media highlights anecdotal evidence of the trend gaining traction, separate reports from Axios found that some companies in the tech industry have begun actively promoting “7 day weeks” in job postings.

The industry’s scramble to drive AI adoption certainly hasn’t helped things, either, with big tech providers and enterprises alike pushing workers harder to deliver returns on investment with the technology.

Earlier this year, Google co-founder Sergey Brin suggested working 60 hours was the 'sweet spot of productivity' for developers.

In a leaked memo, Brin noted that those who “put in the bare minimum to get by” during their working week were “not only unproductive but also can be highly demoralizing to everyone else”.

For developers, the concept might not have such appeal given the profession has been contending with surging levels of burnout and mental health issues over the last five years.

JetBrains' 2024 State of the Developer Ecosystem report, for example, found nearly three-quarters of developers have dealt with burnout at some point in their career.

Aside from the obvious personal impact of burnout on individual employees, the issue has long-term implications for broader workforce efficiency and financial returns.

Analysis from Harness in late 2024 found the issue costs enterprises globally as much as $1 trillion each year.

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Up to three million UK jobs could be lost to AI over the next ten years, according to the National Foundation For Educational Research (NFER), prompting calls for widespread reskilling programs.

In a new report, the foundation said that roles in at-risk occupations such as administration, secretarial services, customer service, and machine operations are declining at a much faster rate than previously predicted.

While the number of jobs in the labor market as a whole is actually expected to grow by 2035, the study found most growth will be in occupations such as science, engineering, and legal roles.

These jobs require what the NFER sees as “essential” employment skills centered around communication, collaboration, problem-solving, organizing, planning & prioritizing, creative thinking, and information literacy.

“The report’s focus is on what are now widely recognized as the essential employment skills that underpin employability and are increasingly sought after in the evolving world of work. It makes a major contribution to our understanding of how to better value, develop, and support these skills," said Josh Hillman, director of education at the Nuffield Foundation.

“Crucially, it also provides the education system, employers, and policymakers with evidence to help ensure the workforce can continue to build and use them effectively in a dynamic labor market.”

The UK workforce needs to be retrained

Notably, the study revealed that around 3.7 million workers have 'substantial' shortfalls in the six vital employment skills, with the number projected to increase to around seven million by 2035 unless action is taken. 

While 45% of UK adults said they currently feel supported by employers to develop new skills, 43% did not. Only 24% said they feel the government supports them to develop new skills, with 66% feeling they aren't currently supported.

To combat this looming shortfall, the foundation called on the government to ramp up support for the adult skills system. This includes increased funding to break down barriers for adults retraining and transitioning from declining occupations into growth sectors.

It should also ensure that HR and management practices help employers and line managers to accurately assess, utilize, and develop their workers’ existing skills. 

Meanwhile, researchers said schools should foster essential skills, building them into the Initial Teaching Training and Early Career Framework.  

“The time has come to tackle this critical challenge head on, and we all have a role to play. Meeting projected skills shortages means a collective response from government, employers and across the education and skills systems," said Jude Hillary, principal investigator and NFER’s co-head of UK policy and practice.

“We need to strengthen support in the early years, tackle inequalities in schools, strengthen pathways into growing jobs, and rebuild the adult skills system to deliver growth that benefits everyone.”

Jobs will disappear, but more will be created

The NFER study comes hot on the heels of Gartner research that warned of huge labor market changes in the next decade, largely due to widespread AI adoption.

A study from the consultancy found that a range of professions will be hit hard by AI adoption as businesses look to reduce headcount and automate aspects of their operations.

All told, roughly 32 million jobs will be “reconfigured, redesigned, or fused” each year from 2028 onwards. However, while the outlook may appear gloomy for workers, this period of flux is expected to create more jobs, rather than result in a sharp decline.

Upskilling and reskilling will be crucial to ensure this transition period is smooth, according to Gartner, with around 150,000 people each day expected to begin retraining.

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Anthropic’s Claude AI assistant is among the most popular options out there on the market in 2025, but are you struggling to get the most out of it?

If you think you need to scrub up on your skills, the AI company has teamed up with skills development firm Coursera to launch a new course and specialization aimed at giving developers key tips and tricks when using the assistant.

According to Coursera, the new content from Anthropic is designed to give learners “direct, hands-on experience with Claude and help them build the confidence and skills to collaborate effectively with AI”.

Through the Building with Claude API course, learners will gain access to interactive sessions guided by AI-generated content, as well as personalized feedback on their progress.

The course spans several modules, from the basics to more advanced topics such as Retrieval Augmented Generation (RAG) and Model Context Protocol (MCP) tips.

If you’re just learning the ropes, modules on simply getting started with the AI assistant are available, allowing users to learn API fundamentals, model selection best practices, and how to make your first API call to Claude.

Elsewhere, prompt engineering modules aim to help developers “master the art of designing, refining, and testing high-quality prompts” while a dedicated course on Claude Code, the company’s AI coding assistant, are also available.

Maggie Vo, Anthropic’s head of education, said the modules aim to ease learns into using the AI assistant in their daily workflows.

“Claude can transform your workday, acting as a brainstorm partner, a researcher, and a coder,” she said.

“But we know many people are still learning how to collaborate with AI safely and effectively. These courses address that gap by giving learners the skills and confidence to get the most out of Claude, from the fundamentals of getting started up to building agents.”

More Claude courses are coming

In addition to the developer-focused content, Anthropic’s collaboration with Advancing Women in Technology (AWIT) will also see a new course launched.

The Real-World AI for Everyone course is a triple module specialization that aims to help learners “of all experience levels to build practical fluency for using AI in their daily work”.

This will include a dedicated module, dubbed AI Fundamentals with Claude, aimed at giving users an insight into structuring prompts to get more high-quality responses from the assistant.

Meanwhile, the AI Automation with Claude module will guide users through the process of automating repetitive tasks with the tool.

Nancy Wang, founder and CEO of AWIT and SVP of engineering at 1Password, said the course will help broaden access to the tool.

“AI use remains uneven across different groups,” she said. “And anyone, at any level, can benefit from deliberate, hands-on practice. That’s why we partnered with Anthropic to give Coursera learners worldwide access to real-world, curated AI learning experiences.”

“Learners receive hours of experience with Anthropic’s AI assistant, Claude, guided by former Anthropic engineering manager Dan Mellott. Learners build fluency, confidence, and joy as they use AI to innovate, lead, and create lasting impact across every field and community.”

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Enterprises are cutting back on entry-level hires at an alarming rate, which experts warn could create significant long-term skills shortages.

In a survey conducted by IDC on behalf of Deel, 66% of enterprises revealed they expect to slow entry-level hiring while 91% reported that roles are already changing or disappearing due to AI.

Media, retail, healthcare, professional services and logistics are the industries most affected, the survey found.

“AI is no longer emerging, it’s fully here. It’s reshaping how we work and how businesses operate,” said Nick Catino, global head of policy at Deel.

“Entry-level jobs are changing, and the skills companies look for are too. Both workers and businesses need to adapt quickly. This isn’t about staying competitive, it’s about staying viable.”

Virtually all of the organizations surveyed have at least started exploring and implementing AI, despite the fact they’re reporting significant problems with talent pipelines.

With AI taking over repetitive and knowledge-based tasks, this means there's a shortage of candidates with the necessary skills for higher steps on the ladder.

Just under seven-in-ten survey respondents said there are now fewer on-the-job development opportunities for junior employees, while 71% reported increasing difficulty in recruiting and training future leaders because of the loss of entry-level learning pathways.

Similarly, nearly half (43%) cite a shortage of skilled AI talent as a big problem. Half of all employers are now willing to pay AI specialists 25% to 100% more than comparable tech roles.

They're also offering extra incentives, with half offering access to cutting-edge tools and 43% promising well-defined career paths.

Enterprises are evolving to compensate

Meanwhile, organizations are restructuring to try and improve matters, with nine-in-ten saying they've experienced role changes or displacement and 34% undergoing significant workforce restructuring to integrate AI.

Two-thirds of respondents are already investing in AI training programs to upskill workers and future-proof their teams.

However, 57% are finding limited employee engagement in training, 51% face budget constraints, and 45% struggle to find expert trainers.

Notably, respondents said it’s unclear who holds responsibility for AI reskilling in many companies, with only 3% having established cross-functional teams to coordinate initiatives, and 29% admitting they don’t know who owns the process.

A grim outlook for entry-level workers

The survey results mark the latest in a series of gloomy future predictions for graduates this year, and with enterprises changing recruitment practices things could get worse.

Just 5% of organizations now view a degree as essential for entry-level roles, for example. Instead, the top three requirements for entry-level talent are technical certifications in AI tools or coding bootcamps, problem-solving and critical thinking abilities, and strong communication and collaboration skills at 51%.

"Artificial intelligence is reshaping the global workforce at an unprecedented pace, outstripping any recent technological shift,” said Chris Marshall, vice president for AI in Asia Pacific, IDC.

“Organizations that will thrive are those that unite automation with a human-centered vision – investing in upskilling, redefining entry-level opportunities, and ensuring that governance and ethics evolve in step with innovation.”

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American workers are the least confident they’ve ever been in the job market. Official monthly data released in early September by the US Federal Reserve showed that the perceived probability of finding a new job fell to 44.9% in August. This is the lowest reading since the central bank started surveying job-finding expectations in June 2013.

Faced with uncertainty, workers are staying in their jobs even if they would prefer to hand in their notices tomorrow. This isn’t a new trend, as the job market has always ebbed and flowed, but “a sense of global events as unpredictable and unprecedented, combined with looming AI disruption, is making workers increasingly unsure,” according to Korn Ferry.

As a result, workers are holding on tight to their jobs and the security of their pay packet – or ‘job-hugging’, as the management consulting firm puts it.

Recent data from Randstad Digital backs this up, with almost half of all Gen Z tech workers concerned about the impact of AI on job security.

It’s a reversal of the Great Resignation that occurred in 2021 and 2022 when employee turnover rose sharply as workers quit en masse and were confident about quickly securing new jobs, says Emma Collingwood, chief people officer at real-time payments platform Volt. “We are now beginning to see the opposite happen, largely due to macroeconomic factors,” Collingwood says. “It’s harder to move roles.”

Job-hugging in itself isn’t “inherently problematic”, Collingwood points out. After all, if employees are hopping from job to job instead then this increases hiring and training costs. However, if job-hugging means workers are mentally checked out, as with quiet cracking, then this could hamper productivity.

Gauge engagement levels

The challenge, then, is to keep job-hugging employees engaged. Leaders need to start by understanding how they’re feeling and what might be driving any disengagement. Collingwood suggests conducting pulse surveys to gauge levels of employee fatigue.

One-to-one meetings can also be incredibly helpful as they can allow employees to open up about any concerns they might have. Leaders should use these meetings as a chance to discuss career development goals.

Collingwood explains that ”it’s often a lack of growth opportunities, unclear expectations, or feeling undervalued that’s driving disengagement”. Elaine Laird, head of people and culture at Logitech, echoes this sentiment and argues that regardless of job market conditions, “when opportunities for growth and development in current roles aren’t available, most, if not all, employees will switch off.”

Debbie Mitchell, director at HR consulting firm LACE Partners, agrees and tells ITPro that businesses must do more to provide tangible opportunities within the workplace. “Leaders often make the mistake of treating job-hugging as an employee problem, when in reality it’s often a problem with the organization,” she says. “If your best people are clinging to the safety of a role, it usually means they don’t see clear, supported pathways to grow elsewhere.”

Let employees rise to the challenge

As for practical steps leaders should take, they need to find new ways to “reignite employees’ motivations”, says Laird. This can be done through “engaging them on the potential opportunities, new challenges and different responsibilities or other roles they could be fit for elsewhere in the business.”

She recommends that leaders give their employees stretch assignments. These are tasks that require skills and knowledge beyond their current development and responsibilities. However, they’re a chance for employees to demonstrate to employers that they are capable of rising to a challenge.

Once employees complete stretch assignments successfully, leaders need to give them feedback – and praise where due. Recognition matters and can give employees a sense of belonging, says Ronni Zehavi, CEO and co-founder of HR tech firm HiBob. “Small, timely acknowledgements boost morale and reinforce a sense of belonging far more than annual rewards.”

If employees can see that their input is valued and that their employers trust them to take risks, then they’re more likely to take risks in the future. It’s a virtuous circle that can benefit performance and productivity. Employees may also come to realize that there’s room for them to grow with their current employers. As Mitchell puts it, “job-hugging quickly can quickly turn into career building”.

Turn caution into commitment

There are a number of other steps leaders can take to keep employees engaged. These include training and mentoring to boost skills and internal mobility programmes that promote the movement of employees to take on new roles.

It’s clear that businesses have an opportunity here to improve retention and fill skills gaps at the same time. Tech leaders in particular can look to meet the growing demand for AI skills through internal reskilling and seek to stem potential staff turnover down the line through this targeted training and investment in high-value staff.

Mitchell warns that “chaining” employees to their current roles can make them more of a flight risk. But, “by creating transparent pathways, encouraging lateral and cross-functional moves, and making it clear that ambition is welcome,” leaders can increase the likelihood of employees wanting to stay put.

At the end of the day, even the most loyal of employees will want to leave if they don’t see a future at their current employers, notes Zehavi. “With the right approach, however, leaders can turn caution into commitment and build loyalty that lasts beyond the downturn.”

Nora works in Uganda in business process outsourcing (BPO) at a call center. She's cautiously optimistic about AI adoption – after all, she's been able to reduce wait times from ten minutes to just two. But she's also worried about whether she'll have a job in the future.

This anecdote was shared by Elise Montano, director for measurement and impact at Caribou, while speaking about the tension between AI and work at the Mozilla Festival in Barcelona, Spain.

"Nora is an example of living at the cutting edge of this tension," Montano told attendees.

As part of a wider research project, Caribou interviewed 20 BPO workers in the region. Every one of them reported using AI everyday, Montano noted, and they are worried about its impact on their jobs.

And they should be: younger people will be the hardest hit by AI, as entry-level jobs continue disappearing. Montano noted that BPO tasks are 68% filled by young people, and 50% of the tasks in entry-level positions are ripe for automation versus 4% in more senior roles.

"AI is starting to remove the first rung of the career ladder," she said. But at the same time, she added, AI is also raising expectations of what skills workers will have. "The second rung of the ladder has moved up for many people."

Aside from younger people, Montano said Caribou's research suggested that women were the next cohort of people at high risk of automation, followed by rural jobs.

Those findings align closely with a study from the UN’s International Labour Organization (ILO) earlier this year, which found generative AI is three-times more likely to impact women in the workplace than their male counterparts.

On the job training

Montano noted that the BPO workers her team spoke to were largely teaching themselves on the job, rather than being offered formal training, an issue which enterprises are now grappling with globally as staff turn to ‘shadow AI’ tools and non-approved training materials.

"Most learning is on the job," she said, adding they learned how to do it themselves — despite being required to use the technology on the job.

Indeed, she shared an anecdote about another worker who was mandated by managers to use Microsoft Copilot in his work, and even monitored to ensure he did – but not given any training at all.

"There's a whole ethics issue of people being forced to learn this on their own time," Montano added.

Notably, that sort of "experiential training" seems to work well when it comes to AI.

Caribou set up an online training effort in an attempt to reach five million small businesses — which they achieved. However, she noticed there was little impact noticeable in terms of profits, jobs or efficiency for the businesses.

In the organization's next attempt, it offered specific tools to benefit SMBs and training how to use them — sparking a much more positive response.

Of course, context matters, and Lindsey Gottschalk, vice president of strategy and partnerships at Data.org, noted that formal learning does seem to help in her work with charities and social impact organizations.

"We do still see the value of formal learning, but only when paired with experiential learning," she added.

Sometimes less is more

But the question remains on how much training is necessary to upskill workers for the AI era – and naturally it depends on industry and role. But reaching a basic level of digital skills at a wide scale is a good start, Gottschalk said, though she added that “one course on ChatGPT is not going to get a worker ready for AI”.

She also warned that providing AI tools without the right level of digital or data maturity brings risks, as workers will have a "false sense of understanding of what comes beneath it."

For example, rather than hiring a graphic designer, a company may hand generative AI tools to an employee and ask them to sort out marketing content. Although they might know how to use AI, a lack graphic design abilities will ultimately lead to AI slop.

Gottschalk pointed to no-code tools letting companies create a product without understanding the outputs, biases or other challenges of such engineering.

"That's a real danger," she said. "We really care about that baseline of data maturity."

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AI is continuing to make life harder for entry-level workers, with a new study revealing that new grads are facing a radically changed job market.

According to research from St. Thomas University, nearly half (42%) of employers believe that AI may eliminate most entry-level white-collar roles in the next five years – although a similar number think these roles will recover after the initial AI boom.

The study noted that the application process is getting more disheartening for those entering the workforce. One-in-five graduates said they'd applied to more than 50 jobs before landing their first role, with just 21% of applications resulting in a real human interview.

Nearly three-quarters of job seekers (73%) believed AI resume filters prevented their applications from being seen – and they're right, with almost half of employers using AI to screen resumes.

Meanwhile, 28% said AI helped schedule interviews or assess candidates through tests. Other applications include chatbots for communication, ranking candidates after recruiter reviews, and even analyzing video interviews.

Nearly eight-in-ten job seekers said they’ve run into 'ghost jobs' that appear outdated or fake, and 42% or employers admitted that this was the case.

There’s light on the horizon for entry-level workers

Despite a challenging jobs market, researchers said there is room for “cautious optimism” ahead.

Nearly two-in-five hiring professionals said they expect to increase entry-level hiring in the year ahead. Over the past year, 38% said entry-level hiring stayed the same, and 29% reported growth.

More than half of companies (53%) said they hadn't changed minimum experience requirements, and only 18% required AI-specific skills for most postings.

"Early-career tech workers are facing a challenging but not insurmountable path into the industry. Graduates are applying to numerous jobs, often encountering ghost listings, yet many still see value in their degrees and believe in the long-term potential of tech careers," researchers said.

"On the employer side, cautious optimism about entry-level hiring suggests opportunities remain, even as AI-driven processes change recruitment tactics.

“These findings illustrate a complex but evolving hiring environment that future graduates must be prepared to navigate."

The report is just the latest to highlight the difficulties facing new graduates in the age of AI.

Earlier this summer, for example, SignalFire’s 2025 State of Talent report found that tech companies were hiring significantly fewer college graduates than in the year before.

The unemployment rate for new college graduates had surged 30% since September 2022, researchers said.

Meanwhile, tech leaders confirmed the trend, with LinkedIn’s chief economic opportunity officer, Aneesh Raman, comparing the situation with the sharp decline in manufacturing jobs that took place in the US during the 1980s.

Notably, Anthropic CEO Dario Amodei said that both the industry and government needed to be more honest about the situation, telling Axios "I don’t think this is on people’s radar."

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Gen Z tech workers are reassessing their career paths and future plans – and key factors behind the shift lie in the rise of AI and a demand for more flexible working patterns.

That's according to a global survey by Randstad Digital, which found that two-thirds of Gen Z tech workers are excited about the role AI will play at work and are already using it in their roles. However, nearly half (43%) remain concerned about the impact of AI on their job security.

"Our research illustrates that tech jobs remain highly attractive to Gen Z – yet their expectations are shaping how companies now think about culture, flexibility, career growth, and even the use of AI," said Graig Paglieri, chief executive of Randstad Digital.

That said, the split isn't large between generations. Millennials working in the technology sector are slightly more likely to describe themselves as excited about AI at 77% versus 75% for Gen Z, and only a couple of points less likely to say they are concerned about their jobs at 41%.

Gen X is even less concerned, but still in the same range at 38%.

Gen X is even less concerned, but still in the same range at 38%.

Gen Z entered the workforce at a weird time

Gen Z spans people up to 28 years old at this point, and many have entered the workforce amidst the explosion of the generative AI ‘boom’ and a period of mass layoffs across the tech sector.

Research shows they’re experiencing acute difficulties at present, with a recent study from Stanford University suggesting that entry-level technology jobs have been among the hardest hit in the early stages of the AI boom.

Paglieri warned that means they're often left without early-career training or job progression — and that could be bad news for companies in the longer term as talent pipelines dry up.

"While it’s tempting to focus automation efforts on entry-level jobs, employers should design these roles as stepping stones to build stronger, more resilient organizations for the future," Paglieri said.

"Tech leaders should also focus on competitive compensation and clear career paths, while encouraging AI exploration and building a culture of innovation within their organization."

Get ready for churn

Notably, the Randstad report found loyalty to a single company was diminishing among Gen Z workers. Only 3% of respondents in this age group said they expect to last a decade at their current employer, versus 10% of millennials and 11% of Gen X staff.

Instead, a quarter of Gen Z workers said they planned to stay at their current company for three to five years, with three-in-ten saying they'd stay up to two years and 18% for less than a year.

Many younger workers said they have no fear of quitting. Half of Gen Z employees have quit a role after less than a year, pinning the blame on poor workplace culture (41%), low pay (36%), and a lack of career progression (19%).

To avoid churn and keep younger workers longer, Randstad said companies need to offer better pay, show a clear career path, and flexible working hours.

Blended income models

Given concerns about job security – and the continual failure of pay to keep up with cost of living – it's perhaps no surprise that a quarter of Gen Z workers are looking to add a so-called "side hustle" to their main full-time role, versus 23% who prefer to work just one job.

"These insights indicate a strong trend towards blended income models," Randstad said in a statement.

Gen Z workers also continue to favour flexible working hours, with 49% ranking it first, over 45% choosing pay as a priority and 41% saying location.

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Databricks has announced plans to train 100,000 people across the UK and Ireland in AI and data skills.

The skills development scheme will target a range of areas, including generative AI, data engineering, machine learning, and analytics. The initiative will be delivered through the company’s global education program, Databricks Free Edition, and underpinned by $10 million in funding.

Databricks Free Edition offers participants access to self-paced training and AI tools, and is designed to help close what the company claims is a growing AI talent gap.

“The need for highly skilled AI talent, coupled with a robust AI strategy, has never been more crucial for business success,” the company said in a statement.

“According to World Economic Forum data, workers can expect that almost 40% of their existing skill sets will become outdated in the next 5 years, with AI becoming one of the fastest-growing skills needed for today’s workforce.”

Databricks is teaming up with universities

As part of the scheme, Databricks said it plans to work closely with government and academia across the UK and Ireland.

This includes a partnership with the UK Government’s Department for Science, Innovation and Technology (DSIT) through the ‘Get Tech Certified this Autumn’ program.

The program is a three-month scheme which aims to provide free AI and machine learning training for public sector employees across the country, running in tandem with the government’s Blueprint for a Modern Digital Government.

Elsewhere, Databricks is expanding its University Alliance Program, which sees the company work with more than 40 universities across the UK and Ireland. This includes partnerships with the London School of Economics (LSE), University College Dublin, and the University of Sheffield.

The program is helping to equip students at a slew of universities with data and AI-related skills.

Dr Marcos Barreto, Associate Professor of Data Science and Lead on AI for the Department of Statistics at LSE, said the program is enabling students to transition into the workforce with vital skills.

“Providing our data science students with the latest data and AI skills is something we take great pride in. By being part of the Databricks University Alliance program, our students can learn the latest in big data programming and analytics, which is essential to flourish in the fast-paced AI sector,” Dr Barreto said.

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It can be hard to be proud of being disabled. It’s an identity that has been steeped in vitriol and discrimination for centuries.

And yet, much like for other marginalized groups, there are efforts to celebrate. July marked Disability Pride Month, an initiative with formal origins that can be traced back to early 1990’s Boston.

The month has a flag – that has been designed multiple times due to changing access requirements – it has an origin story deeply connected with intersectional advocacy, and it has a growing number of supporters inside and out of the tech sector.

Understanding yourself as disabled, let alone prideful of an identity so often connected with discrimination, is a process. Amy Lomellini, director of accessibility at Anthology, has had to process what it means to connect with disability later in life.

“Knowing what I know now, I was disabled, I just didn't identify with the label,” she tells ITPro. “I didn't know what it was, and I didn't understand disability culture, and I didn't understand disability pride, and it wasn't until I got a neuromuscular disease that paralyzed me from the waist down that I started to recognize that there's more people out there who have shared experiences. And it doesn't have to be a bad thing.”

Lomellini came to tech from the academic world. Disabled people in academia face a whole host of access issues from toxic productivity cultures, to hush hush handshake agreements when it comes to accessibility accommodations, to assumptions about who can and who can’t do intellectual labor.

For Lomellini, it was the access created by digital learning platforms during time abroad. She completed her undergraduate degree thanks to these sorts of spaces, which ultimately got her interested in working in the sector. This came at a time when her disability ended her chosen career path of being a sign language interpreter.

“I was kind of running away to find myself, if we're being honest, it was a very hard hit that I could no longer do the job that I loved, and I had to accept that that was a limitation of my body and that wasn't going to change…and when I realized that there was this whole online learning realm of education that could let me be me… I knew that that's the field that I wanted to be in.”

For some in disability communities, Disability Pride Month – and similar declarations like October’s National Disability Employment Awareness Month, or the myriad of disability-specific ones – is little more than performative activism that give companies an excuse to say they’ve done something that hints at inclusion.

Some also feel as if the types of disability activists who tend to be given the proverbial microphone online put undue pressure on disabled people to be out and proud when it may be safer to be closeted.

Lomellini doesn’t feel that pressure, and says that Disability Pride Month can be an opportunity for every company as they come to understand where they are in terms of creating access for clients and staff – from those who are early on in their understanding to those who integrate accessibility at every step.“

I see them as a springboard for continuous learning. So I think there's organizations and institutions that are at different points in their journey. If you've never heard of disability, if you're not doing a single thing, a disability awareness month can be a catalyst for something like that.”

Surprised I can lead

Shea Belsky is technology lead at a software engineering company and former CTO at Mentra, a platform dedicated to creating employment opportunities for neurodivergent candidates. He says he sometimes bumps into people who are taken aback by his career trajectory.

To him, that’s an opportunity for knowledge sharing and perception shifting. It also begs a question:“Why do people think that autistic people can't be leaders or shouldn't be leaders, and what can we be doing to educate them? And I think it really resonates with people when I talk about these experiences as openly as I do.”

Belsky, who is autistic, says that his relationship to how he thinks about his disability at work has changed over time as he was often in spaces with colleagues who had very little real-world experience with autistic people.

“Coming into my time as a software engineer, I had to become confident talking to people about it, and really become more confident figuring out what does it mean for me to self advocate and what does it mean for me to really figure out how other people can work with me in a way that aligns with not just my brain, but my way of working, my style of working.”

In one junior role, Belsky went through five managers in one year, an experience that let him use his skills to "iterate rapidly” when it came to figuring out his own work processes and how he connected with his own identity on the job. This led him to ask himself a few questions.

“How am I going to get my elevator pitch about autism down? What do I need to say? What does a manager need to know? What does my team need to know? And that really altered my thought process as far as what I felt a manager needed to know, and, most importantly, what I needed from them to be able to do my job.”

A common point of conflict between disability pride and staying safe at work is disclosure, whereby someone chooses to share that they have a disability. The most common time for this concern to appear is at the interview stage, but this challenge, often known within the community as “access friction”, can occur when roles change, when someone gets new symptoms, or they face a micro or macro aggression at work.

Belsky, who now takes on the role of a mentor, says that confronting what you need – and what your employer is or isn’t willing to provide – leaves disabled candidates, even those of us with a strong understanding of our needs, with a difficult choice.

“I think that's a big distinction that I've made when I talk to people: It’s like, you need these things, you need accommodation. Maybe it's headphones, maybe it's an executive functioning coach, maybe it's some sort of medical adjustment,” he says.

“Whatever it is, there are things that you know that you know that you need in the workplace, and you need to be able to ask for them. If your employer can't provide those to you, it is not the company for you, and that's a tough pill to swallow.”

The Role of COVID

Disability, and disability pride, saw a renaissance of sorts during the pandemic. In all sectors of the workforce, time at home led more people to consider if they were neurodivergent, remote work became a key framework for access that became better understood, and more disabled people started to become open and honest about their identities at work.

Suddenly, working from home, the playing field was just a little more level. At the same time, the onset of the COVID-19 pandemic signaled the beginning of a mass-disabling event as a large swathes of the population suddenly had to reckon with a body and/or mind that was different to the one they’d to which they had grown accustomed.

For Catherine Hicks, the founder and principal product designer at A Focused Design Studio, it was COVID-19 that showed some spaces in the tech industry needed to do more to create baseline understandings of what disability and access mean. For her, one of the only ways to do that was to speak up and create space for herself and her work.

“I got a lot of really dismissive comments during the pandemic. Everything from I'm not going to get it [the vaccine] because it's not going to affect me…to people literally telling me this is to clean the gene pool out of people like you during the pandemic, and I think that shifted my narrative to being more in your face. I am a disabled person. I am here. You have to deal with me.”

But that wasn’t how Hicks, who started as a programmer, shared her disability as she began her career in the early 2000s. Back then, she had the double whammy of being both disabled and a woman in tech. As her disabilities aren’t considered visible by most people, she was able to not talk about it.

She believes she “bought into the fear” of what could happen if her colleagues – in an already fast paced environment – knew about her identity. For a long time that information was only shared with human resources and bosses who needed to know.

However, slowly, Hicks decided that she could share a little more, such as telling her colleagues that an upcoming day off was for an infusion for her rheumatoid arthritis. That conversational approach allowed Hicks to share more without having to be set apart in her office dynamic. With the pandemic, Hicks felt there was more of an onus on her to speak up.

“A lot of times when I was talking to people during the pandemic in my life, they didn't realize I was disabled and that their decisions were affecting me personally. And I realized…that my voice, as a disabled person who is n an industry where we're not normally extremely present, had more of an impact if I was more vocal.”

Now Hicks’ work is focused on accessibility in a way she doesn’t think would have happened were it not for COVID-19.

Oh, I’m Blind

For many blind people, including Kamille Richardson, the founder of iSee Technologies, technology and accessibility are two peas in a pod. Kamille works to support those with vision disabilities when it comes to using accessible tools like Windows’ JAWS or Apple’ Voiceover. To her, and many in her community, technology is the main pathway to independence.

“[Without technology] you’ve got to have other people check your mail for you and slide into your DM’s and read your text message, but just be all kind of up in your business. This allows them to be able to do these things, of course, for themselves.”

Richardson, who supports people to find gainful employment and helps companies understand and implement accessible technologies, says there were – and are – days when disability pride is hard to find, just the same as there are days where owning her disability feels empowering. That path, from conflict to comfort, like for many disabled people, has been a lifelong one.

“I really felt like sometimes my blindness was a burden. But then, as I grew and I evolved, and I began to just really spread my wings and get out there and start using my voice and speak up and really use my voice for change and really make a difference in the community. That pride came back,,And I really realized that I am rocking it out in a world that was not designed for me, and I'm making it look good while I'm doing it.”

Her current concern when it comes to how the sector treats disabled people is how she’s finding applications that previously worked with screen readers getting updated and having that vital accessibility fall away. One app that helps her book transportation, immediately came to mind.

“People will say, but Kamille, ‘Well, then you can always call them…” And that's not convenient for me either, because that's a long wait time. I shouldn't have to depend on somebody else to book something for me that I've been able to do all these years by myself.

“When everyday tasks become inaccessible it can be hard to grasp onto disability pride that can take such a long time to find. “I can name a couple of them right now that I can tell I'm getting a little nervous, and these are apps I use a lot, that they might not be accessible then the next update because I'm having a harder and harder time being able to use them.”

Disability Pride: A Precious Commodity

For many, especially those who work in the tech and IT sector, there are a multitude of reasons why pride in a marginalized identity like disability can be difficult to both find and keep.

To be in that position of power within yourself often means having support, having confidence, and knowing what you can and cannot say.

Disability pride might be relatively new on the scale of awareness months, but its own particular version of change is being felt on the tech landscape and within the workforce.

Today is Ada Lovelace Day. A day dedicated to highlighting and celebrating all that has been achieved by women in science, technology, engineering, and mathematics (STEM).

It’s as fitting a day as any to share my recent experience with the F1 Academy, which aims to champion female talent - both on and off the track - in what has traditionally been a male-dominated industry. It hopes to get to a point where Motorsport is “ more diverse, inclusive, and accessible.”

The F1 Academy was created in November 2022 to help young, female drivers progress to higher stages of competitive racing in F1. Susie Wolff - a very prominent and well-respected industry figure - was appointed CEO in March 2023.

At the end of August, at the Dutch Grand Prix in Zandvoort, I spoke with F1 Academy’s head of commercial operations, Karin Fink, about the racing series' hopes for the future and how far it has already come.

“When I started, they'd done a first season. They didn’t have the connection with the F1 teams yet, but it was all building up to that. We’re still in the building phase, but we’ve gone from essentially a racing series that, in 2023, raced at tracks that were not related to F1, [almost] behind closed doors, [with] some that were done with other sports events,” Fink says.

“The commitment from F1 is really clearly shown in giving us that time on the track, allowing us to host our guests here in the Paddock Club, utilizing the incredible broadcast facilities, and access to the fans.

“So, as opposed to all the women’s sports leagues like WSL, WNBA, I don’t have to build my own stadium. The advantage is enormous, and that’s something we really try and capitalize on. We work with the race promoters to add value to the overall event itself and to really convert more of the existing F1 fans to F1 Academy fans.”

Different routes to your destination

Fink started her now extensive motorsports career as a waitress at the F1’s VIP hospitality service, the Paddock Club. She spends a fair bit of time sharing her story of that route into the industry and highlighting the fact that it will be different for everyone.

Indeed, F1 Academy runs a program during races called ‘Discover your drive’ which, in partnership with race promoters, hosts local female students to find out more about what a career in motorsports looks like.

“The reality is, there is no straight path. I'm pretty sure, for a lot of the roles in technology, there isn’t,” Fink adds.

“We want to show them that it's actually possible. If you really want it, you just say ‘yes’ at any opportunity, and then put your hand up.”

Fink talked about how important awareness and visibility are in encouraging other females into STEM roles in traditionally male-dominated industries.

F1 Academy’s recent Netflix series has definitely helped, according to Fink, who adds, “Visibility has risen, and we're really happy with that. For us, it's really about showing girls that our drivers are what they could be.. If you can see it, you can be it.”

Trusted partnerships helping to get the message out there

Amplification of what F1 Academy is trying to do is incredibly important, and there’s definitely strength in numbers. In addition to the support it already gets from F1, partnerships are key.

Back in March, the F1 Academy partnered with TeamViewer, its first technology partner.

“TeamViewer was so passionate about coming into this and into the sport with the view of really opening it up to females. We've been super happy to work together,” Fink says.

“For a company like TeamViewer, a very well-established company that has been in the sport [for a while], with the Mercedes partnership. to take a leap of faith… for them to essentially invest in F1 Academy, I think it really shows that we have something here that is worth consideration and that creates real value and relevance.”

The partnership has many elements to it, but one particularly poignant to this piece on Ada Lovelace Day is TeamViewer’s support of the Wild Card entry at Zandvoort.

Driven by 20-year-old Esmee Kosterman, wearing a TeamViewer-labelled racing suit, the Wild Card car featured TeamViewer livery in support of its ‘Visibility drives change campaign. The car was adorned with images of more than 200 women who are working in STEM and serving as an inspiration to others.

The car’s number was 86, a nod to TeamViewer’s ‘Women in sport tech’ report, created in partnership with Loughborough University. That research found that the majority (86%) of women believe that the way to really achieve gender equality in the workplace is to ensure organizations have visible female leaders.

Racing alongside Kosterman was 18-year-old Chloe Chong. She was racing in the Charlotte Tilbury car, which featured a giant pair of lips and lipstick.

Chong makes use of TeamViewer for remote troubleshooting if she encounters issues with her race simulator. She is also a big believer in the determination to chase your dreams.

“Whatever you want to do, whatever you dream of, you should be able to achieve it. Of course, you've got to put in the work. But I think, now's the time, if you dream it, go and get it, go and get that dream,” she says.

“Even though you will face setbacks. Everyone faces setbacks. There have been times when I thought I'd never race again, but you've just got to hang in there. You've got to keep pushing for what you want.”

I couldn’t have put it better myself!

With the tech skills gap showing no signs of closing, very few IT and business professionals believe they're getting enough support for tech learning.

A survey of 1,500 tech executives, IT professionals, and business professionals in the US, UK, and India from tech workforce development firm Pluralsight has revealed that while 95% say building a culture of learning is a priority at their organization, the same number believe they need more support to learn tech skills.

The biggest problem is lack of time, with only 46% of organizations giving employees dedicated time for learning on the job.

"Organizations understand that a culture of continuous learning is essential to staying competitive," said Chris Herbert, chief content officer at Pluralsight.

"However, translating that intention into action with the right strategies, resources, and the time needed to upskill effectively remains a significant challenge for many."

And the problem isn't getting any smaller. While 67% of organizations said they'd made progress in reducing the IT skills gap, that figure is down 11% year-over-year.

And it's having a big effect on business as a whole, with 48% of IT professionals and 58% of business professionals saying they've had to abandon projects in the past year due to technical skill shortages. This problem showed up most in cybersecurity, cloud infrastructure, AI and machine learning (ML), and DevOps.

"Finding ways to course-correct towards more effective tech learning programs will be mission-critical as rapid cloud and AI innovations further pressure workforces," said Herbert.

Upskilling is seen as being faster and more cost-effective than hiring, with 89% of organizations saying that hiring IT talent is more expensive than upskilling their current workforce.

Nearly three-quarters of organizations spend less than $5,000 per employee to upskill, while 46% spend over $5,000 to hire a single tech employee. In the US, the contrast is even more stark, with an average upskilling cost of $5,770, compared with $14,170 for hiring.

Meanwhile, 43% of organizations say upskilling is faster than hiring, allowing teams to quickly contribute to critical projects and accelerate time-to-impact.

There are big advantages for workers who do upskill, with the research revealing that certifications are currently the number one factor in job progression for tech professionals – 46% of IT employees who earned certifications reported salary increases or promotions as a direct result.

Meanwhile, 47% of non-technical employees said tech skill 'microcredentials' or digital badges played the biggest role in getting them a raise or helping them get into a new role. They also reckoned that company upskilling programs, bootcamps, and immersive training are just as impactful as employer-funded degrees when it comes to promotions.

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