Has your CEO been asking how AI can help make your forecasting process simpler lately?
A new Datarails survey of 389 finance leaders shows CEOs are now the ones directing AI deployment in finance. Over four in ten finance leaders (44%) say the CEO is the primary driver of AI adoption in finance. Less than a third (28%) say the CFO is leading it. When it comes to major tech overhauls in finance now, the research suggests some CFOs are playing second fiddle.
Leaders of finance’s AI agenda
This pattern shows how the CFO role is increasingly being viewed not just as a cost center, but as a revenue driver. However, though many CEOs want to lead finance’s technology initiatives, the research data shows CFOs are some of the most well-rounded executives when it comes to AI use.
More than eight in ten CFOs (84%) say they personally use generative AI and more than three in four (77%) say they are using it in an authorized AI program. This has led to a varying but rapidly accelerating rate of implementation at an organizational level. Nearly two thirds say their companies adopted AI in finance within the past 12 months with only 11% saying they have more than 24 months of usage.
So, when a CEO asks how AI could impact the forecasting planning variance narrative or close cycle compression, many CFOs can respond with firsthand usage rather than hypothetical language or technology rhetoric. The data indicates many CFOs have already built familiarity through daily interaction. If they have CEO buy-in on driving new tech into finance, the next challenge is articulating which area of that CFO’s finance function is first up.
Areas where AI is taking hold inside finance
Nearly three quarters of companies (74%) that have a financial operations function say that team is already using AI and two thirds (66%) say the same for accounting. Respondents working in FP&A reported the highest adoption inside analysis work, with 88% of workers there using AI for data analysis. Two thirds (66%) of FP&A respondents also said they’re using it for narrative reporting and 63% say they are using it for planning and modeling. Eight in ten (80%) of treasury respondents identified risk management as their top AI use case, while 70% of audit respondents identified risk and anomaly detection as theirs.
Larger organizations are also integrating AI inside platforms that already act as the system of record. Eighty-two percent of companies with more than $250 million in revenue report using embedded ERP AI features compared with only 50% of smaller companies.
How CFOs can lock-in and lead
The pressure is on now for finance as expectations for productivity improvement are high. Almost four in ten (38%) expect 11% to 25% productivity gains and over one in three (36%) expect 26% to 50% gains. Nearly all finance leaders (92%) expect at least 11% improvement. Yet only 43% expect headcount to decline by more than 11%. This shows a belief that AI will increase the volume and pace of finance’s processing power without requiring large layoffs or elimination of future roles en masse.
Tooling preferences also reveal finance’s intent. Nearly three in four (74%) say their preferred approach is building internal AI tools on general purpose models. More than half (54%) say they also buy AI native tools. Only 31% say they prefer using new AI features from existing vendors.
For those who are using vendors, the largest players are unsurprisingly dominating. OpenAI is used by 89% of companies and Google Gemini is used by 70%. For some CFOs, this points to a shift in software strategy. Finance is positioning itself to assemble its own AI capability rather than relying entirely on vendor modules. But, as leaders like KPMG’s Deputy Chair Atif Zaim told CFO.com in August, many organizations of all sizes, including KPMG, are sticking to their core functions, using vendors and not building large AI tools.
The remaining gap in the CFO-CEO dynamic is measurement language and a bit of ego shelving for both sides. CEOs are green-lighting AI programs because they see the financial advantage. CFOs, many of whom will own the risk and responsibility for these rollouts, have been experimenting, implementing and operationalizing for some time. The next stage of AI in finance, according to the research done by Datarails, will be defined by how quickly CFOs can attach metrics to those gains and then explain those metrics to their CEO and boards in ways they can extract value from.
If they define the ROI model early, CFOs may be able to retain control of finance’s technology rollout and how value is communicated. If they wait, other leaders and functions may start to define the benefit narrative on their behalf. The survey signals a moment where CFOs now need to treat AI measurement like capital allocation. The technology is already being used. The strategic next step is nothing new for the CFO, explaining to stakeholders the math behind the initiative while managing big ideas of the CEO.
