Gartner: CFO Finance Teams' AI Adoption Growth Slows, Challenges and Optimism Coexist
According to the latest survey released by Gartner on Tuesday, the adoption rate of artificial intelligence among corporate finance teams in 2025 is roughly the same as in 2024, although optimism about the technology has risen. Among 183 surveyed CFOs and senior finance executives, 59% said they use AI within their departments, slightly up from 58% last year. Of those adopters, 67% are more optimistic about AI than they were last year. The research indicates that data literacy, data quality, and skill shortages remain major barriers, while use cases such as knowledge management and accounts payable automation are the most common.
Briefing at a Glance
- Despite rising optimism around artificial intelligence technology, enterprise finance teams' adoption of AI in 2025 remained roughly flat compared with 2024, Gartner said on Tuesday.
- Of the 183 CFOs and senior finance executives surveyed by Gartner, 59% reported that their departments use AI, only slightly above last year's 58%. While the overall pace of adoption has slowed, among finance departments that have already adopted AI, 67% of respondents said they are more optimistic about AI than they were a year ago.
- "This growing confidence suggests that while AI adoption in finance is slowing due to complexity, data, and talent challenges, organizations that overcome these obstacles are reaping significant rewards," said Marco Steecker, senior director of research in the Gartner Finance practice, in a press release. "As AI performance improves and technology evolves to cover a broader range of use cases, CFOs should witness a virtuous cycle between finance AI development and opportunities for new technology applications."
Deep Dive
Gartner forecasts that global AI spending will approach $1.5 trillion in 2025 and exceed $2 trillion by 2026. Large technology companies in particular are investing heavily in AI to strengthen products while experimenting with various use cases internally.
"We like to call it 'drinking our own champagne,'" said Danielle Fontaine, assistant corporate controller at ServiceNow, describing her company's AI journey during an online meeting hosted last week by the Financial Executives International.
Comments from some speakers indicated that while several of the largest U.S. technology companies are using AI to streamline workflows and processes, leaders remain cautious about use cases and guardrails and have not rushed into large-scale projects.
Accounting and finance leaders in particular are "cautious about what it means to bring these types of solutions into our processes and our environment," Fontaine said.
The momentum of finance AI adoption, which jumped from 37% in 2023 to 58% last year, has now slowed, Gartner said.
The report noted two main factors appear to drive the slowdown: first, a small portion of finance departments remain skeptical, with 16% saying they have no plans to implement AI in the coming year; second, a larger proportion of finance organizations (25%) still face uncertainty about how best to transition from planning to piloting.
Insufficient data literacy/technical skills and data quality/availability remain the biggest barriers to AI adoption, the research showed.
According to a report released by McKinsey in early November, corporate efforts to mitigate AI risks in areas such as privacy, compliance, and organizational reputation have increased in recent years. In 2022, respondents managed an average of about two AI-related risks, compared with four today.
Overall, 51% of respondents in the McKinsey study reported at least one negative consequence due to AI adoption, and nearly a third reported issues related to inaccuracy.
Gartner's latest survey found that among AI use cases adopted by finance departments, three stand out. Knowledge management—helping organizations organize, retrieve, and leverage information to optimize decision-making—was the most common use case (49%), followed by accounts payable process automation (37%) and error and anomaly detection (34%).
"Some less mature but highly feasible use cases also show significant potential," Steecker said in the report released Tuesday. "For example, finance leaders rated code generation as the AI use case with the highest impact, and by a significant margin. Organizations find that this use case enables employees to identify customized, high-leverage opportunities to enhance automation and insight generation."
After overcoming the initial hurdles of launching pilots, achieving significant benefits still takes time, with 91% of respondents reporting low or moderate initial impact. Gartner said organizations with more mature AI adoption are more than twice as likely to experience moderate impact and nearly three times as likely to experience high impact.
"Given that the greatest impact is realized after AI enters production, finance leaders should focus on accelerating promising projects through the early development stages," Steecker said.