AI confidence gap opens between senior & junior staff

TrustedTech has published research showing a gap in AI confidence and training between senior leaders and junior employees. The survey covered 2,000 employees in the UK and US.

The findings point to a mismatch between corporate investment in AI tools and the support many workers receive to use them. In the UK, 73% of decision-makers said they felt confident using AI at work, compared with 44% of junior employees.

Training appears to be a central issue. More than a third of employees, 38%, said they were largely self-taught in AI, making it the most common way to learn the technology. By contrast, 23% said they had received AI training from their employer.

Many respondents also described weak guardrails around workplace use. Some 41% said their organisation did not provide enough training on using AI safely and securely, while 38% said they had received little or no clear guidance on acceptable AI use at work.

That combination of patchy training and limited policy direction raises concerns for employers trying to widen AI use across their organisations. Staff expected to work with the technology may instead rely on informal experimentation, creating security, compliance and privacy risks if unsanctioned tools or practices spread.

Workplace divide

The survey suggests access to AI knowledge is developing unevenly inside businesses. Senior staff appear more likely to build confidence quickly, while junior workers, who may face bigger changes to day-to-day tasks, are getting less structured support.

Almost half of respondents, 47%, said employers should take primary responsibility for helping staff develop AI skills. Yet the figures suggest many workers believe they are being left to figure it out on their own.

There are also signs that reluctance to use AI is linked as much to uncertainty as to resistance. Among those uncomfortable with AI tools, 24% said a lack of knowledge or understanding was the main reason they had not adopted them, while 22% said fears of being replaced by AI were holding them back.

The picture that emerges is not simply one of uneven enthusiasm for new software. It is a broader workforce issue in which confidence, access to training and clarity over acceptable use may determine who benefits from AI at work and who falls behind.

Julian Hamood outlined that concern in comments accompanying the research. "Employees are being told AI will transform the way they work, yet many have received little training on how to use it effectively, securely or confidently. In many organisations, workers are learning through trial and error while leaders stay ahead. The people who are most confident with AI will continue to build skills and productivity, while others risk being left behind through no fault of their own - and there's a huge risk of an AI skills divide emerging as a result. Organisations need to treat AI readiness as a people issue, not simply a tech deployment issue. Clear governance, practical training and a structured understanding of where employees are today are critical if businesses want AI adoption to be both effective and responsible," said Julian Hamood, Founder and Chief Visionary Officer, TrustedTech.

Adoption risks

The data arrives as companies continue to push AI into routine office work, often through writing assistants, search tools and software features embedded in wider workplace platforms. But the survey suggests rollout alone does not guarantee broad or consistent adoption.

For employers, that can mean weaker returns on technology spending if workers do not know when and how to use the tools. It can also increase the likelihood of so-called shadow AI, where staff turn to unauthorised applications because approved systems, training or policies are unclear.

The results underline a practical challenge for management teams. If AI use is left to self-teaching, early adopters may gain a sharper productivity edge, while other employees remain hesitant or exposed to mistakes that better training might have prevented.

The research highlights the need for structured assessments of AI readiness, including clearer governance and a better understanding of current skills levels before organisations expand AI use. The figures suggest many businesses still need to address those basics before AI can become a consistent part of everyday work.