More than four in five decision makers at UK organisations (83%) report that at least some of their AI spending has delivered no measurable return, or that they do not measure returns at all, according to new research from Air IT Group.

The findings reveal what Air IT Group calls the ‘AI Decision Gap’: the disconnect between investing in AI and having the evidence and clarity to determine whether it is delivering value and where further investment should be made.

The research, based on 504 responses from decision makers at UK organisations, found that 41% had purchased or introduced an AI tool before agreeing what problem it should solve. Among respondents reporting at least one active AI initiative, 74% said not all initiatives had both an agreed business objective and a measure of success.

Businesses are under pressure to move on AI, but the findings suggest many are investing before they have a clear plan for what they want to achieve or which opportunities are worth pursuing.

This raises questions about how far AI investment is translating into the productivity gains the UK Government is seeking to unlock, particularly when businesses are struggling to demonstrate the value of investments already made.

The research found that 83% report at least some AI spending without measurable returns, or do not measure returns at all.

About three quarters (74%) of respondents report at least one active AI initative said not all initatives had both an agreed business objective and a measure of success.

About two in five (41%) have purchased or introduced an AI tool before agreeing the business problem it should solve.

Further, six in ten (62%) of respondents whose organisations formally track AI pilots have abandoned at least one in the previous 12 months.

About half (47%) say Ai has made a task or process take longer than before, once checking, correction, setup and management are factored in.

Only 13% say their organisations consistently convert time saved through AI into measurable higher output or productivity.

The consequences of investing without clear objectives are evident in the number of AI projects failing to progress. Among respondents whose organisations formally track AI pilots, 62% said at least one had been abandoned in the previous 12 months. Integration difficulties and employee adoption were among the barriers identified: 34% selected integration difficulties and 29% selected employee non-adoption as the most common reasons for abandonment.

The research also highlights the importance of how AI is implemented and measured. Almost half of respondents (47%) reported that AI had made a task or process take longer once checking, correction and management were factored in.

Meanwhile, just 13% said time saved through AI was consistently converted into measurable higher output or productivity. The findings reinforce the need to start with clear business outcomes and measures of success.

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“AI has huge potential for businesses, but simply introducing more tools doesn’t guarantee better outcomes,” Lee Johnson, chief technology officer at Air IT Group, said.

“Our research found that 41% of organisations had introduced an AI tool before agreeing what problem it should solve. If the problem and the outcome aren’t clear from the outset, it becomes much harder to know whether AI is actually delivering value.

“Businesses need to start with what they’re trying to achieve, identify where AI can make the biggest difference and agree how success will be measured. That gives leaders the evidence to decide what to scale, what to rethink and where to invest next.”

To help close this AI Decision Gap, Air IT Group launched its AI Accelerator in September 2026, designed to give SMEs a clearer basis for deciding where and how to invest in AI.

The AI Accelerator begins with an in-person AI Envisioning Day, bringing senior leaders together to identify their business priorities and where AI or automation could deliver the greatest value. Air IT Group then assesses the opportunities identified alongside the organisation’s readiness to deliver them, before building a prioritised roadmap setting out what to do now, next and later.