For a long time, AI has been framed as a technology challenge. This meant it lived with innovation teams, IT leaders or – more recently – newly created Chief Data or AI Officer roles. The logic made sense: AI was complex and uncertain, and someone had to make it work. But we’re now moving past the era of AI experimentation and into a phase focused on strategic value and measurable results.

New research from OneStream suggests the power is shifting towards finance. According to the survey of more than 350 CFOs across the UK, US and Australia, three-quarters of finance leaders say they now lead their organisation’s AI strategy.

Rather than a turf war between finance and IT, this represents a strategic evolution. It’s a signal that AI has crossed an important threshold from technical possibility to operational performance and long-term impact. As a result, ownership is moving to those closest to capital allocation and value creation.

Why finance is emerging as the natural owner of AI strategy

Our research confirms what we already know: AI spending is on the up. 83% of CFOs expect overall AI investment to rise across their organisations in the next year, with finance among the fastest-growing areas of spend. Naturally, the pressure is on for this investment to deliver real business impact.

The boardroom conversation has changed, too. When discussing AI, boards are no longer asking broad, open-ended questions about potential; they want to know what value it will create, and how fast. Nearly every CFO surveyed (97%) says their board expects a regular readout on AI investment and progress, with a focus on cost savings, ROI and productivity gains.

In this environment, it makes sense that CFOs are stepping (or being pushed) forward. Not only do they have a bird’s-eye view across the business, but a reputation for balancing ambition with commercial discipline and risk. They’re also used to dealing with uncertainty, trade-offs and imperfect information – all of which are essential to making AI work in practice.

Turning AI ambition into measurable business impact

One of the most telling findings from the research is how candid CFOs are about their current use of AI. While two-thirds (67%) believe their AI strategy is ahead of the curve, only a third say they have successfully deployed AI at scale. And just 35% report an excellent understanding of AI itself.

We found that the current application of AI remains focused on foundational use cases such as financial close and consolidation; forecasting and planning; compliance; and reporting. Longer-term ambitions are more strategic, with many CFOs looking to apply AI to advanced decision-making for scenario modelling and financial forecasting.

This cautious progress might look like a weakness, but I think it reflects a crucially grounded approach. CFO-led AI efforts are starting with specific value levers, whether it’s improving accuracy, streamlining consolidation and close processes, strengthening risk and compliance, or unlocking productivity across finance teams. They’re identifying where AI can make a measurable difference to existing workflows rather than chasing broad transformation narratives.

Starting small sharpens, rather than dampens, ambition. By grounding AI projects in defined KPIs, finance leaders have a far greater chance of delivering early wins, which build confidence and create clear pathways to scale.

Finance and IT as the AI control centre

Crucially, CFO ownership doesn’t mean AI becomes a finance-only project. In fact, our research shows AI is driving closer alignment across the C-suite, with half of CFOs reporting their relationship with the CTO/CIO is becoming more strategic, and a third describing it as more collaborative. That matters because scaling AI depends as much on data quality, integration and security as it does on strong business cases.

In the past, finance and IT were often seen as the guardians of enterprise stability. Today, they face a shared mandate: moving AI projects forward in a way that is ambitious but also responsible. This requires alignment on goals so momentum doesn’t stall.

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Governance is a critical part of this partnership, establishing clear investment thresholds, shared accountability for outcomes, and a disciplined approach to data. Proper governance sets guardrails that actually allow the business to move faster, giving teams the freedom to innovate within a trusted framework.

Implemented well, this kind of governance helps organisations move beyond disconnected pilots. Instead of dozens of isolated use cases, AI becomes embedded into core processes and decision cycles, where it can deliver repeatable value. The result is business-wide trust: in the data, the outputs and the decisions that follow.

The big picture: AI for strategic growth

For years, AI has been discussed in terms of what it could do. Today, the conversation is focused on what businesses actually need.

As AI usage becomes a visible and permanent fixture in the enterprise, the questions surrounding it have become more pointed. Boards are looking for greater rigour around risk and return, and those questions naturally land on the CFO’s desk. This means that AI can no longer exist as a standalone innovation project. To be successful, it has to be integrated into the core decision-making framework; it has to be planned, governed and assessed like any other strategic investment.

Seen through this lens, the real AI power shift isn’t a technological one. It’s all about accountability. The most effective CFO-led AI programmes will bring structure to innovation, delivering outcomes the business can stand behind.