For some businesses, the cost of an AI skills gap is already showing up on the bottom line.

In Kaplan's ‘From AI to ROI: Who owns the problem?’ report, 39% of C-suite leaders say their organisation has lost a competitive bid or client opportunity in the past 12 months partly because of concerns around AI capability.

It's a finding that puts the skills gap in a different light. When capability can influence whether a business wins work, achieves the expected return from its technology investment, or keeps AI initiatives moving, it becomes a commercial issue as much as a workforce one.

So what's driving the gap - and what can leaders do to prevent AI investment from becoming a missed opportunity? Here’s what you need to know.

The return on AI isn't guaranteed

Organisations invest in AI with an expectation of what that investment will deliver. But the research suggests that those returns aren't always materialising.

In the past 12 months, 37% of C-suite leaders say their organisation has failed to achieve the expected ROI from an AI tool or deployment.

One factor is how effectively technology is being used. A further 38% say they have found AI tools underutilised, suggesting that simply making technology available doesn't guarantee that organisations will realise its full potential.

This creates a difficult equation for businesses. The investment has been made, but the value expected from it may remain out of reach if the organisation doesn't have the capability to make full use of what it has bought.

Capability can determine how quickly AI delivers

The commercial implications extend beyond whether businesses achieve a return from their existing AI investment.

As AI becomes increasingly embedded in how organisations operate and compete, capability can also influence how businesses respond to new opportunities. A workforce that can use AI effectively can help an organisation move faster, while gaps in capability can create friction when new initiatives need to be delivered.

Kaplan's research found that 26% of C-suite leaders say their organisation has delayed an AI-related project or initiative in the past 12 months.

For businesses, a delay can push back the point at which they expect to see the operational or commercial benefits of an initiative, particularly when AI is being used to support wider transformation.

Retaining and developing AI capability

For businesses, developing AI capability is only part of the challenge. Organisations also need to make sure people with those skills have opportunities to keep developing, put their capabilities to meaningful use and see a future for themselves within the organisation.

The research found that 32% of C-suite leaders have experienced difficulty retaining staff with AI capabilities over the past 12 months. While there can be a range of reasons why people leave, a lack of opportunities to develop and progress could make it harder for organisations to retain people with in-demand skills.

Providing opportunities for continued development can help organisations give people reasons to keep building their skills within the company and progressing within the business, while making the most of the capabilities they have developed.

This could include applying their skills to new projects, expanding their expertise or taking on greater responsibility.

For organisations, the focus should be on creating an environment where people can continue to develop their capabilities, take on new challenges, and make a meaningful contribution as the use of AI evolves.

Workforce capability needs to be part of the investment

If capability gaps can affect everything from technology utilisation to competitiveness, developing those skills needs to be considered alongside AI adoption rather than afterwards.

Yet the balance of investment isn't always there. More than half of C-suite leaders (54%) say their organisation has placed greater emphasis on AI tools and technology than workforce capability development over the past 12 months. Just 20% say the greater emphasis has been on developing employees' skills.

The research also provides an indication of what leaders believe can work. Structured apprenticeship or qualification programmes were rated the most effective approach to building AI capability by 31% of C-suite leaders whose organisations had built AI capability in the past 12 months.

The focus, however, shouldn't simply be on completing training. The goal is to develop capability that employees can apply to the work the organisation is trying to improve through AI.

That means connecting learning to real business needs and giving employees the opportunity to develop skills they can use in practice. This is what makes Kaplan’s apprenticeships so valuable: they develop highly credible, workplace-ready professionals with the practical skills to apply what they learn in their roles.

Through industry-tailored development and immersive learning, employees can build the skills they need to adapt, apply new knowledge, and make an impact within their organisation. They also develop data analytics and AI capabilities, helping them stay equipped to thrive as technology and the workplace continue to evolve.

Protecting the commercial opportunity

The findings from Kaplan's research suggest that AI skills gaps are already affecting competitive opportunities, technology returns, project progress, and workforce retention.

Instead of slowing down AI investment, the answer is to make sure investment in technology is matched by investment in the capability needed to use it.

For business leaders, that means making AI capability a shared organisational responsibility and giving the people responsible for developing it the authority and resources to act. It also means measuring whether those skills are helping the organisation achieve its wider objectives.

Because the real cost of an AI skills gap is the opportunities and investment that can be lost when an organisation isn't equipped to make the most of the technology it has chosen to adopt.

Discover these insights and more in Kaplan's AI to ROI report.

Methodology

The research was conducted by Censuswide, among three samples of:

• 1000 UK employees within transformation-heavy sectors and functions in companies with 50+ employees where AI deployment is active (excludes Business owners and C-Level Execs) between 10.07.2026 - 21.07.2026
• 600 UK HR and L&D decision makers (HR directors, L&D managers, People and Talent leads) with 50+ employees, whose organisation is using AI between 10.07.2026 – 22.07.2026
• 600 (Aged 25+) C-Suite and Director level; in specific sectors; whose organisations use AI; and at companies of 50+ employees between 10.07.2026 – 22.07.2026

Censuswide is a member of the Market Research Society (MRS) and the British Polling Council (BPC), and a signatory of the Global Data Quality Pledge. We adhere to the MRS Code of Conduct and ESOMAR principles