Finance AI adoption in 2025 is consistent with last year, with 59% of finance leaders reporting the use of AI in their finance function, according to Gartner, a business and technology insights company.
According to the 2025 Gartner AI in Finance Survey of 183 chief financial officers (CFOs) and senior finance leaders – taken May through June 2025 – the results show only a slight increase in adoption compared to the 2024 survey, which found 58% of finance functions were using AI.
“The momentum in finance AI adoption has slowed following a sharp increase from 37% in 2023 to 58% adoption last year,” said Marco Steecker, Senior Director, Research in the Gartner Finance practice. “While overall growth in finance function adoption is proceeding more slowly, 67% of those using AI in finance are more optimistic about AI than they were last year. Notably, optimism tends to grow with AI maturity, with 23% of those farther along in AI adoption saying they were “much more optimistic” about AI in 2025 compared to just 7% of those just starting to adopt AI.
“This growing confidence shows that even though the pace of AI adoption in finance has slowed due to complexity, data, and talent challenges, organizations that overcome these barriers are reaping significant rewards. As AI’s performance improves, and the technology evolves to address a wider array of use cases, CFOs should experience a virtuous cycle between AI development in finance and new opportunities to leverage the technology.”
Three use cases stood out as they have been adopted by more than a third of respondents that had implemented AI in their function. Knowledge management – helping organizations organize, retrieve, and leverage information for better decision-making – is the most common AI use case (49%) in finance organizations, followed by accounts payable process automation (37%), and error and anomaly detection (34%).
“Some less-established, high-feasibility use cases also show significant potential. For example, the AI use case ranked highest for impact by finance leaders was code generation, by a significant margin,” said Steecker. “Organizations are finding this use case enables staff to find custom high-leverage opportunities for increased automation and insight generation.”
Challenges Remain for AI in Finance
Two main segments appear to be driving the adoption slowdown: First, a small segment of finance organizations show continued skepticism, with 16% reporting no planned AI implementations for the coming year. Second, there remains uncertainty among a larger share of finance organizations (25%) on how to best make the leap from planning to piloting.
Date literacy/technical skills and inadequate data quality/availability remain the largest obstacles to AI adoption across all organizations. Finance organizations that do not use AI at all tend to struggle with gaining a cultural acceptance of AI and making it an organizational priority.
After overcoming the initial barriers to launching a pilot, it still takes time to realize significant gains, with 91% of respondents reporting low or moderate impact initially. Organizations further along with AI adoption are over two times more likely to experience moderate impact and nearly three times more likely to see high impact from the technology, and are half as likely to report low impact.
“Given that the biggest impacts are achieved once AI is in the production stages, finance leaders should focus on accelerating promising projects through early development,” said Steecker. “AI’s potential in finance remains strong, and organizations that invest in overcoming adoption barriers will be well-positioned to capitalize on future opportunities.”
