CFOs drive AI investment but only one in three succeed at scale
A new study has found that while Chief Financial Officers (CFOs) are increasingly responsible for driving artificial intelligence strategies within their organisations, only one in three report success in deploying these technologies at scale.
OneStream's Finance AI Survey, which compiled responses from over 350 full-time CFOs in the United States, United Kingdom and Australia, points to growing expectations from boards and investors for finance leaders to translate AI's potential into practical results. However, the report highlights ongoing challenges related to return on investment, talent shortages, and the evolving position of the CFO as a primary architect of AI in business.
AI strategy led by CFOs
The survey indicates that finance roles are taking precedence in shaping enterprise AI strategy. According to the findings, 75% of CFOs now claim to lead their organisation's approach to AI, compared with 42% of CTOs or CIOs, 40% of Chief Data or AI Officers, and 27% of CEOs. As AI becomes more central to enterprise operations, 83% of CFOs predict increased AI investment overall, while 80% expect greater spending specifically within the finance function in 2026.
Growth in AI expenditure appears robust, as 78% of respondents foresee up to a 50% budget rise for AI initiatives, and a further 22% expect increases exceeding 50%. Within finance teams specifically, almost four in five CFOs plan for up to a 50% increase in AI investments, with the remainder aiming for still greater backing.
CFOs' confidence in their strategic AI leadership remains strong, with 67% believing their strategies are ahead of the curve. However, only 35% said they had an excellent understanding of AI, and just 33% reported successful deployment of AI at scale.
Involvement across the C-suite
The report suggests that AI is fostering more collaboration within executive teams, particularly between finance leaders and their technology counterparts. Half of CFOs describe their relationship with CTOs or CIOs as more strategic due to AI, while a third highlight increased collaboration overall. Looking forward, 57% of CFOs anticipate closer integration with IT, operations and data science functions as AI adoption accelerates in finance.
Board demand for clear ROI
The survey notes a common theme amongst corporate boards: a desire for measurable returns from AI investment. Almost all CFOs (97%) said their boards expect regular updates detailing progress and investment outcomes, prioritising cost savings, ROI metrics and productivity gains. However, the pressure to demonstrate value is tempered by ongoing concerns among finance leaders themselves.
While 93% of CFOs reported organisational understanding of the ROI on current AI investments, the group remains split on the actual value delivered in practice. Early benefits are being observed, as 56% of CFOs have seen real productivity gains through AI deployments. Still, uncertainty persists, with nearly a third (32%) citing doubts over AI project ROI and more than half (53%) identifying cost optimisation as a future focus area.
"Boards and CEOs are looking to CFOs to lead the enterprise through the AI era," said Tom Shea, CEO and President at OneStream. "Finance sits at the intersection of data and decision-making, positioning CFOs as the natural architects of AI-driven performance. The challenge now is how to break through the AI hype so CFOs can build a trusted, secure AI strategy that solves real pain points across the business."
Implementation challenges remain
Despite rising investment and board-level support, large-scale enterprise deployment of AI remains limited. The survey highlights that most current use is focused on foundational areas-financial close, forecasting and planning, and compliance-rather than broader, end-to-end process transformation. Only a third of CFOs said they have successfully implemented AI at scale, and experimentation with more advanced cognitive or generative AI applications is still in early stages.
Immediate priorities for finance teams over the next two years include automating financial close and consolidation, supporting forecasting and planning, and strengthening risk and compliance. Longer-term ambitions are more strategic: 61% of respondents plan to leverage AI for advanced decision tools such as scenario modelling and enhanced financial forecasting. Nevertheless, a lack of AI talent, inconsistent data quality and integration difficulties are cited as ongoing obstacles to enterprise-wide adoption.
