Deloitte has reported a marked rise in optimism among UK chief financial officers over the commercial impact of artificial intelligence, with finance leaders increasingly treating the technology as a performance and investment priority.
The firm’s latest UK CFO Survey found that 73% of finance chiefs are optimistic that AI will materially improve business performance. That compares with 59% at the end of 2025 and 39% two years ago, indicating a significant change in senior finance sentiment as companies expand the use of AI across functions.
The survey also found that 93% of CFOs expect investment in digital technology to rise over the next 12 months. Geopolitics remains the largest external risk facing businesses, but technology spending is still being protected as companies focus on cost control, cash discipline, and productivity.
Finance leaders are being asked to fund AI while proving returns. The early wave of generative AI adoption often sat inside innovation budgets, technology teams, or productivity pilots. Wider deployment requires capital allocation, governance, procurement controls, cyber oversight, data management, skills planning, and measurable effects on margins, customer service, forecasting, or working capital.
That gives CFOs a more active role than simple budget approval. Finance teams are setting the conditions under which AI projects enter operating models, including how investment cases are assessed, what success looks like, and where benefits appear in the P&L. Vague productivity claims are becoming harder to defend as boards ask for evidence that automation, analytics, copilots, and agentic tools are reducing cost or improving decisions.
Recent coverage of AI adoption has already shown the same shift in management discipline. Finance employers have been committing to AI retraining, while directors are placing AI governance on the board agenda. The common thread is that adoption now requires controls, accountability, and workforce planning, not only software access.
Finance teams are likely to be early beneficiaries and early test cases. AI can support forecasting, scenario planning, fraud detection, invoice handling, variance analysis, customer profitability work, procurement review, and management reporting. Those functions are data rich, repetitive, and commercially important, making them attractive for automation.
They are also sensitive. Errors in financial reporting, controls, tax, or regulatory disclosure can create legal, reputational, and operational exposure. A poorly governed tool that produces plausible but inaccurate analysis may create more risk than efficiency. CFOs therefore need assurance processes that can test outputs, protect data, and preserve accountability.
Cost control remains a major concern. Deloitte’s survey points to continuing caution on spending even as digital investment rises. Companies are not entering a broad investment boom; they are redirecting money towards technologies expected to improve efficiency. AI spending therefore competes with hiring, consultancy, software consolidation, cyber resilience, and transformation programmes.
The talent consequences will be felt across finance, operations, HR, legal, and customer functions. Some tasks will be automated, but the premium is likely to rise on employees who can validate outputs, interpret data, understand processes, and connect analysis to commercial decisions. The risk is not only job displacement. Uneven adoption may allow some teams to gain speed and insight while others remain constrained by poor data, legacy systems, and weak governance.
Geopolitical uncertainty complicates investment decisions. Companies are already managing energy risk, trade disruption, currency volatility, supply chain exposure, and higher funding costs. AI investment is being assessed in that environment, so finance chiefs will want evidence that the technology improves resilience as well as efficiency.
Greater CFO optimism does not guarantee smooth implementation. Many businesses still lack clean data, joined up systems, clear ownership, and practical assurance processes. AI tools can create value quickly in narrow workflows, but broader change depends on architecture, controls, culture, and process redesign. Finance leaders will increasingly ask whether AI is reducing complexity or adding another layer of tools that must be governed.
The survey marks a change in boardroom psychology. CFOs are more positive about AI while remaining cautious about the external economy. The next year will show whether that confidence can be converted into audited business value.
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