Finance leaders are embedding AI into forecasting and planning at a rapid clip, but most still can't prove the technology is paying off. Protiviti's 2026 Global Finance Trends Survey, released Aug. 26, found that 77% of finance organizations now use AI, up from 58% last year for financial forecasting specifically. Only 35% say they are highly or moderately effective at measuring AI's return on investment.
The survey, based on responses from CFOs and finance executives, shows AI adoption has moved from experimentation to core operations. Financial forecasting is the leading use case, followed by risk assessment and management (67%) and process automation (56%). But the report, titled Synchronize, warns that most finance teams are deploying AI without a defined strategy - just 14% are doing so - which limits their ability to scale the technology or tie it to measurable business outcomes.
Data security remains the top priority
For the third consecutive year, finance leaders ranked security and privacy of data as their top priority, ahead of financial planning, analytics and AI. The finding reflects the growing dependence on internal and third-party data as AI becomes more embedded in finance workflows.
"Organizations cannot scale AI without confidence in the quality, security and governance of their data," said Christopher Wright, global leader of Protiviti's CFO Solutions and Business Performance Improvement practice. "That is the major reason why cybersecurity and data governance remain finance's top priorities."
The survey also found that 83% of CFOs rank cash management among their top three areas requiring attention, as economic, monetary and trade policy shifts create pressure on liquidity. Finance teams are strengthening cash flow forecasting, working capital dashboards and liquidity reporting to give leaders real-time visibility into cash positions rather than waiting for month-end reports. Industries placing the greatest emphasis on cash management include financial services (61%), manufacturing and distribution (55%), healthcare (45%) and consumer products (41%).
AI's next opportunity: scenario planning
Protiviti identifies AI-enabled scenario planning as an underdeveloped opportunity that could connect forecasting, risk assessment and cash management. Finance teams that build this capability would be better positioned to model multiple economic outcomes and adjust plans quickly.
For finance professionals, the survey's message is that AI adoption without governance and measurement creates risk, not advantage. The teams that will lead are those pairing AI tools with clear objectives, strong data controls and defined metrics for value - the same disciplines that make forecasting and cash management reliable. That combination is what separates AI experiments from AI-enabled finance transformation.
Why this matters for finance executives
CFOs and finance leaders should treat the 35% AI ROI measurement figure as a competitive signal. The gap between adoption and measurable value is where finance teams can differentiate - by defining success metrics before deploying AI, not after. The survey suggests that AI for CFOs is no longer a question of whether to invest, but how to govern, measure and scale those investments. Similarly, AI for Finance teams is moving from isolated use cases to integrated workflows spanning forecasting, risk and liquidity - and the organizations that build that integration with disciplined data governance will be the ones that turn AI spend into performance.
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