CFOs Lag Peers on AI Adoption Despite Public Enthusiasm, Gartner Finds
Chief financial officers are talking up artificial intelligence in public while quietly holding back on implementation, creating a widening gap between finance departments and other corporate functions in AI adoption, according to new research from Gartner.
The consulting firm found that 61% of CFOs either have no plans for AI implementation or remain stuck in initial planning phases—the exact inverse of the enthusiasm finance chiefs express in surveys about their AI intentions. The hesitation stands in stark contrast to other administrative functions: only 9% of finance organizations have reached the scaling or active use phases of AI deployment, compared to 20% of HR, legal, IT, procurement, and real estate departments.
The disconnect reveals a classic case of aspiration versus execution in the C-suite. Grant Thornton recently reported that 61% of CFOs plan to invest in AI this year, with 54% of technology CFOs specifically citing plans to use AI for improved decision-making and insights, and 51% targeting automation of routine tasks. Yet when Gartner measured actual progress rather than stated intentions, finance departments emerged as laggards in their own organizations' AI transformations.
"Despite AI's potential, most finance functions' AI implementations have remained limited," said Marco Steecker, senior principal in Gartner's financial practice. He urged CFOs to "partner with their finance leadership teams to compare their current progress against their peers' and identify concrete recommendations from early adopters on how best to accelerate AI use in their function."
The primary culprit, according to Gartner's research, is cost anxiety. Roughly 80% of CFOs believe expenses for purchasing, installing, and training staff on AI tools will increase, with most expecting costs to rise more than 10% by 2026. The irony is hard to miss: the executives most responsible for controlling corporate spending are the ones most spooked by AI's price tag.
The gap grows even more pronounced with generative AI specifically. Just 1% of finance functions have adopted or intend to invest in generative AI technology, compared to 10-20% of customer-facing and IT departments—a tenfold difference that suggests finance leaders view the technology as either too experimental or too expensive for their risk tolerance.
Beyond cost concerns, CFOs cite a familiar litany of obstacles: lack of technology capabilities, poor data quality, and unclear use cases. Steecker noted that these excuses "speak to an important aspect of finance leaders' beliefs about AI, which is that it is a discrete pro[ject]"—though the source material cuts off mid-sentence, the implication is clear that finance chiefs may be treating AI as a standalone initiative rather than an integrated capability.
The research raises uncomfortable questions for an executive cohort that prides itself on data-driven decision-making. If CFOs can't build the business case for AI in their own departments—where automation of routine tasks and improved analytics seem like obvious wins—what does that signal about their ability to evaluate AI investments elsewhere in the organization? And as other functions race ahead, finance risks becoming the bottleneck in enterprise-wide AI strategies rather than the enabler.
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