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Kaplan UK has published research showing that many organisations are spending more on AI tools than on workforce training. The study found that 54% of C-Suite respondents believe investment has favoured technology over employee capability.
The findings point to a gap between AI deployment and day-to-day use in businesses. Kaplan surveyed 1,000 UK employees, 600 HR and learning and development professionals, and 600 company directors and C-Suite leaders.
Only one in five senior leaders said their organisation had prioritised workforce capability over technology investment. At the same time, 44% of C-Suite and director-level respondents said IT or technology teams are primarily responsible for AI capability in their organisation.
The data suggests this approach is leaving many employees without enough support. A third said they had been asked to work with AI without sufficient training, while 26% remain uncertain about how it should be used.
Senior leaders also reported operational consequences linked to these gaps. More than a third said their organisations had experienced problems related to AI capability shortfalls over the past 12 months.
Among the specific issues, 38% said AI tools were being underused and 37% said an AI tool or deployment had failed to deliver the expected return on investment. A further 39% said their organisation had lost a competitive bid or client opportunity partly because of concerns about AI capability.
Confidence gap
The research also highlights a divide between how employees view their own AI readiness and how managers assess it. Four in five employees, or 80%, described themselves as confident using AI productively and responsibly in their day-to-day work.
Leadership did not share that confidence. C-Suite and director-level respondents estimated that fewer than half of employees expected to use AI are genuinely proficient, at 46%, while HR and L&D leaders put the figure at 37%.
The results suggest businesses may be moving quickly to roll out AI systems while lagging in the work needed to help staff use them consistently. They also indicate that responsibility for AI adoption is being concentrated in technology functions, even when the barriers extend into management, training and workplace processes.
Access to formal training appears uneven. Just 35% of employees said their organisation had provided structured AI training to a significant proportion of the workforce.
Where training has been provided, employees generally viewed it positively. Among those who had received AI training, 81% described it as effective.
Shared responsibility
Chiraag Swaly, Head of Data and Technology Curriculum at Kaplan, outlined the shift companies now face.
"The first phase of enterprise AI has focused heavily on access and deployment. The next phase needs to focus on how effectively people are able to apply that technology in their roles. Technology can be deployed across an organisation relatively quickly, but building the judgement, confidence and practical capability needed to use it well requires greater focus and accountability. If employees cannot apply AI effectively in their day-to-day work, technology leaders may face slower adoption and a harder battle to secure investment, as transformation programmes risk failing to deliver the expected results. Technology teams have a critical role, but workforce capability needs to be developed jointly with business leaders and people teams," Swaly said.
The survey comes as companies across the UK continue to fold generative AI and other automated tools into routine work. The results suggest internal preparedness, rather than access alone, is becoming a more prominent issue as organisations try to show returns on those investments.
For employers, the findings raise questions about ownership. Technology teams may lead on system selection and implementation, but the survey points to broader organisational challenges when staff are unclear about use cases, lack training, or do not reach the level of proficiency expected by management.
The picture that emerges is not one of outright resistance to AI, but of uneven adoption. Employees appear willing to engage with the tools, yet many are doing so with limited guidance, while leaders question whether the workforce can use them effectively enough to deliver business value.