Finance teams are adopting AI faster than they can measure its value. Protiviti's 2026 Global Finance Trends Survey found that AI use for financial forecasting jumped from 58% to 76% in a year, yet only 35% of finance organizations say they're effective at measuring AI ROI.
Financial forecasting is the biggest use case among the 77% of finance organizations employing AI, ahead of risk assessment and management and process automation. Teams are using AI on larger data sets, more scenario planning, and faster insights for leadership.
Adoption outpaces governance
Only 14% of finance groups are deploying AI against a defined strategy. Nearly everyone is adopting the technology, but far fewer have a governance model or a way to show the board what the money bought.
Security and privacy of data ranked as finance's top priority for the third year running, ahead of financial planning, analytics, and AI itself. It stays on top because AI pulls in data from both inside and outside the organization. The more data feeding the AI, the more exposure risk that comes with it.
"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."
For finance professionals looking to close the governance gap, resources like the AI Learning Path for CFOs can help build the skills needed to manage AI initiatives. The broader AI for Finance coverage tracks how these tools are reshaping financial operations.
Cash management rises in importance
Economic and trade volatility is pulling finance's attention, reshaping priorities. The survey found 83% of CFOs rank cash management among their top three priorities, with financial services (61%) and manufacturing and distribution (55%) placing the greatest emphasis on it.
The survey is global, but the bind is the same everywhere. Finance is leaning into AI, but can't yet prove what it's worth.
"Today's challenge is to use AI to make more informed business decisions and prove that it is delivering measurable value," Wright said. "Organizations that pair strong data governance with clear business objectives are better positioned to navigate economic uncertainty, shifting market conditions and rising expectations for finance transformation."
The numbers at a glance
Adoption keeps outrunning control. Seventy-seven percent of finance teams use AI, 35% can measure its return, and just 14% run it against a defined strategy.
Data security has outranked AI itself on finance's priority list three years running, even as AI spread through forecasting and planning. Finance reached for the practical use first, putting AI into forecasting at 76% adoption, ahead of risk assessment at 67% and process automation at 56%.
Why this matters for finance professionals
The gap between adoption and measurement is a career risk. If you're deploying AI tools without a defined strategy or ROI tracking, you're exposed when leadership asks what the investment delivered. The practical move is to pair every AI initiative with a measurement plan and clear governance, so you can show results instead of defending spending.
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