Half of UK chief executives surveyed by EY-Parthenon identified artificial intelligence among their three largest contributors to productivity gains during the past year, although only 14% said they had comprehensive, real-time visibility of the technology’s costs.
The findings come from the October 2026 CEO Outlook Survey, which included 100 UK chief executives. They suggest that AI is becoming an important operational investment while many companies continue to face difficulties measuring the financial returns.
AI-enabled tools and applications were cited among the leading productivity contributors by 50% of respondents, ahead of business process redesign and simplification at 40% and workforce reskilling at 38%. These results represent executives’ assessments of their companies rather than independently measured increases in productivity across the wider UK economy.
Nearly one-third of the UK sample, 32%, reported significant gaps in their ability to evaluate AI return on investment. The problem extends beyond identifying whether an application saves time, since financial assessment also requires businesses to understand how much the technology costs to operate and whether improvements translate into additional output, lower expenditure or better commercial results.
An AI application may reduce the time required to process customer enquiries, prepare documentation or analyse recurring information. Calculating its financial contribution, however, also involves software licensing, system integration, infrastructure, employee training and the supervision required to operate it effectively.
Some benefits appear as additional capacity rather than immediate reductions in expenditure. A business may complete more work with the same number of employees, allowing staff to address demand that previously exceeded available resources without producing a directly identifiable saving on its payroll.
Among the chief executives surveyed, 34% selected greater output without additional headcount or capital as the leading productivity benefit. Faster delivery was identified by 19%, while 15% cited more time for higher-value work.
Each outcome requires a different method of assessment. Transaction volumes and processing times may provide relatively straightforward operational measures, while better decision-making, customer experience or employee capacity can require longer observation before the financial effects become apparent.
EY-Parthenon found that 34% of UK respondents considered legacy technology and operating models the largest obstacle to turning productivity improvements into measurable business value. Another 29% identified organisational complexity, regulation or increased risk management as their principal constraint.
These findings indicate that introducing AI into an established process may provide limited benefit where underlying systems remain fragmented or information is inconsistent. Organisations can improve individual tasks while continuing to encounter delays elsewhere in the same operation.
More than two-fifths of the UK executives, 44%, reported reinvesting productivity gains in growth, innovation or transformation. That approach can support future expansion, but also complicates financial measurement where efficiencies are used to undertake additional activity instead of reducing existing costs.
The research also examined AI’s role in corporate transactions. Some 54% of UK CEOs said their organisations were piloting the technology in selected transaction-evaluation activities, while 28% reported using it across multiple activities.
Potential applications include organising due diligence information, assisting document review and identifying subjects requiring further examination. Such systems can improve access to information, but responsibility for assessing a transaction and making investment decisions remains with the organisations concerned.
Workforce capability is another concern. Nearly three-quarters of the respondents, 74%, expected skills shortages to become a greater constraint on growth than access to capital over the next three years. That finding reflects executive expectations rather than a prediction of the number of vacancies that will remain unfilled.
The UK survey forms part of a wider EY-Parthenon study of 1,200 chief executives across 21 countries. The national sample of 100 executives is therefore distinct from the global results, and its findings should not be presented as representative measurements covering every British business.
Reported productivity improvements provide evidence that executives are recognising benefits from AI, but those assessments do not establish the return earned on individual investments. As companies extend the technology into more operations, the ability to account for implementation costs and measure sustained financial performance will influence where further expenditure is directed.
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