While three-quarters of UK businesses now use AI tools, the material benefits of the expensive technology remain underwhelming at best. So far, only 31% of companies using AI have seen a positive ROI of any kind, while less than half can even define what ‘success’ would look like when implementing AI – casting doubt on the sustainability of current investment rates.
Having been swept up in the AI-ferver of the last three years, many investors are suddenly looking at substantial spends in the cold light of day, and wondering when the returns advertised will start to materialise.
Around the world and across all industries, executives remain excited around AI. Publicly, at least, they issue statements declaring they hope to realise huge productivity boosts and efficiency savings by plumbing the technology into every facet of their operations. But more than three years since ChatGPT and generative AI entered the public conscious, material impacts seem thin on the ground.
Late in 2025, for example, one now infamous MIT study found that fewer than one-in-ten firms had seen positive financial impacts from implementing AI. Meanwhile, when IBM polled an international cohort of CEOs, talk of the technology’s untapped possibilities remained rife, but the researchers found that progress to realise that was slow. In 2024, two-thirds of leaders said they expected to move beyond the piloting phase of AI changes, but a year later, 60% were still stuck in the nascent period of experimenting.
Now, another study has suggested that little has changed at the start of 2026. Digital product studio Studio Graphene commissioned Censuswide to survey 500 senior decision-makers within UK-based businesses, ranging from managers and directors to C-level executives and owners. And the data returned shows that while over three-quarters of UK businesses are now using AI tools, the vast majority are yet to see any return on their AI investments.
Wheel-kicking
With widespread excitement around the technology having gripped firms of all sizes, the fact 78% of businesses polled said they were using AI in some capacity – rising to 85% for mid-sized organisations, the highest of any group – may not come as a surprise. But while a further 14% are exploring their options or plan to implement AI in 2026, they may want to look before they leap into the space at a time of rising scepticism.
A sparse 31% of the businesses using AI said they had seen any positive ROI from their investment in the technology. And while 16% said it was still too early to tell, 18% said their AI projects had never delivered the benefits they expected.
Commenting on the findings, Ritam Gandhi, director and founder of Studio Graphene, said, “Many organisations are at a critical point in their AI journey. There has been a rush to adopt AI amidst huge hype and a proliferation of new tools – this is certainly true of private equity-backed mid-sized companies looking to AI for automation, scalability and competitive edge. The problem, however, comes when AI is deployed without first defining where it sits within workflow, the decisions it’ll inform, the processes it’ll support, and the criteria for measuring success – often teams haven’t agreed whether AI is meant to save time, improve decision quality, reduce risk, support growth or all of the above.”
This brings up another recurring theme on AI. While many companies are still all too willing to believe the hype, few have any idea how they would even begin to define whether the technology was living up to it.
Late in 2025, a Wavestone survey found that even as the vast majority of organisations said they thought the technology is now saving them time at work, more than two-in-five had no ROI mechanisms in place to actually measure the benefits of AI tools. And in this case, Studio Graphene found that – worse – only 41% of AI users had “a clear idea of what ‘success’ looks like” when implementing AI solutions. And while this rose among the biggest AI-dependents of mid-sized businesses, 46% is still a minority.
As these companies continue to burn through funds, investors are beginning to participate in a growing amount of wheel-kicking – testing to see which areas they are actually seeing value for money in. If leaders expect to continue on this track, then they will need to put more extensive plans in place than they have managed to date.
Gandhi added, “It’s a really important issue that threatens progress. Without defining these things, building a long-term business case for AI and realising its value will be difficult. At board level, frustration will grow without a clear picture of how and why AI is being used, and to what effect. It underlines the need for rigorous planning for any AI transformation project, not just in selecting the right tools, but in defining the broader strategy, implementation and criteria for success.”
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