Artificial intelligence is no longer something businesses are “keeping an eye on”. It’s already shaping how work is done, how decisions are made, and how productivity is measured.
New research from CompTIA (AI’s Impact on Productivity and the Workforce), shows that around one in three companies now require employees to complete AI training. That figure alone sends a strong message: organisations are moving beyond experimentation and starting to treat AI skills as essential.
For businesses that haven’t yet invested in structured AI training, the risk is clear. Waiting too long may mean falling behind competitors who are already building AI capability into their workforce.
While CompTIA’s study is based on U.S. organisations, the pressures it highlights are highly relevant to UK employers – particularly those operating in IT, professional services, project management and operational roles where efficiency and accuracy matter most.
The “It’s Too Early” Mindset May Be the Biggest Barrier
One of the most revealing findings in the report is how many organisations believe it’s simply “too soon” to train staff in AI.
Almost 46% of companies said AI training wasn’t needed yet because their AI use is still in the early stages. On the surface, that may sound reasonable. In practice, CompTIA warns it can become a trap. The report describes this as a “chicken or the egg” paradox. Organisations stay in early-stage adoption because employees lack AI skills – yet training is delayed because adoption hasn’t progressed far enough.
In short, progress stalls because people haven’t been equipped to move it forward. This is a familiar challenge for UK organisations that have introduced new technology without fully supporting staff to use it confidently and effectively. AI is no different.
Boardroom Expectations Are Rising – Fast
AI is now firmly on leadership agendas. According to the research, 82% of organisations report growing expectations for AI to deliver tangible productivity gains. But expectations and outcomes don’t always align. Nearly 79% of companies that tried replacing human tasks with AI had to reverse some of those decisions, handing work back to people when systems failed to meet deadlines, quality standards or compliance requirements. Performance issues, difficulties scaling solutions and unexpected costs were common reasons for these setbacks. However, CompTIA is clear that technology alone isn’t the problem.
The report highlights that workflow design and staff skills are just as important as the tools themselves. Without trained people who understand how to apply AI responsibly within real processes, even the best technology can disappoint.
AI Adoption Is Patchy – Skills Make the Difference
On average, 37% of employees are already using AI at work, according to CompTIA. Larger organisations tend to see faster adoption, often driven by CEOs and senior leadership teams. However, adoption does not automatically mean capability. Only 34% of companies currently mandate AI training, while 36% leave training optional. That means many organisations are relying on individual curiosity rather than a consistent skills strategy.
This creates uneven results. Some teams move ahead quickly, while others struggle to keep up. There is, however, a positive signal for training providers and learners alike. Eighty-five percent of organisations say they value industry-recognised certifications to validate AI knowledge and confirm that staff can actually apply what they’ve learned.
For UK employers, this aligns with a growing preference for training that delivers practical outcomes and recognised credentials – not just theory.
Using AI Doesn’t Automatically Mean Gaining Value
Another important finding is how few organisations properly measure the impact of AI. Across five key productivity indicators – including time saved and output increased – only around half of companies measure AI’s effects in a structured way. Many rely on informal judgement rather than data. CompTIA warns that this can lead organisations to overestimate how well AI is performing, particularly when benefits are assessed by “eye-balling” rather than clear metrics.
This reinforces the need for AI training that goes beyond basic tool usage and helps staff understand outcomes, risks and responsible application.
AI and Jobs: Change Is Happening, but Slowly
Despite dramatic headlines, CompTIA’s research shows a more measured reality. Based on a September 2025 survey of 1,133 U.S. companies, 38% have taken some form of staffing action linked to AI. This includes creating new roles, shifting responsibilities and, in some cases, removing posts. However, only 20% reported replacing staff with AI at all, and most of those organisations either redeployed employees or hired new people as roles evolved. The percentage of companies that only reduced staff because of AI is just 9%.
That said, junior roles appear more exposed. Employers cited perceptions of easier replaceability and lower influence on outcomes. This is where early upskilling becomes critical. For both employers and learners, AI skills can help protect roles by increasing value rather than reducing it.
When AI Becomes a Convenient Excuse
One of the more candid findings in the research reveals a credibility issue. Among organisations that reduced staff, 64% admitted that AI was sometimes used as cover for unpopular decisions, such as layoffs or cost-cutting, even when AI was not the sole cause. This highlights why transparent, skills-led AI strategies matter. Organisations that invest openly in training are better positioned to build trust and show that AI is being used to support people – not simply replace them.
AI Skills Are Now a Competitive Necessity
AI is increasingly shaping the job market. CompTIA reports that demand for AI skills in U.S. tech job listings more than doubled year-over-year, with roles requiring AI skills growing far faster than overall tech hiring. Nearly half of organisations say they are reassessing competitiveness because of AI pressures. While these figures are U.S.-based, the same trend is clearly emerging in the UK: employers are looking for professionals who are comfortable working alongside AI, not intimidated by it.
What This Means for UK Businesses and Learners
Although this research focuses on the U.S., the implications for the UK are hard to ignore.
AI is moving quickly from “nice to have” to expected capability. Businesses that delay training risk slower adoption, weaker returns and growing skills gaps. Learners who fail to develop AI literacy risk being left behind as roles evolve.
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