Executive Summary:
AI Adoption vs. Value: While finance functions are rapidly moving AI from pilot stages into production, CFOs are struggling to convert these deployments into significant business value.
Activity vs. Impact: Gartner warns leaders not to mistake high deployment volumes for actual impact, as boards now expect proven outcomes in decision-making and execution.
Efficiency vs. Analytics: Though 66% of organizations report improved productivity, 63% faced slower-than-expected implementation. High-impact areas like financial forecasting and insight generation remain difficult to optimize.
Gartner’s Recommendations: CFOs should shift focus from deployment metrics to realized value. They must address cost and mindset barriers, target material business problems, and strengthen data foundations for future AI integration.
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Finance functions are rapidly moving AI from experimentation into production, but many CFOs are still struggling to convert AI deployment into significant business value, according to Gartner, Inc., a business and technology insights company.
Speaking at the Gartner Finance Symposium/Xpo 2026 in National Harbor today, Marco Steecker, Director Analyst, Research in the Gartner Finance practice, said finance’s 2026 AI “report card” shows that AI adoption is advancing, but realized value is not keeping pace with CFO expectations (see Figure 1).
“Finance teams have certainly made AI use more common, but CFOs now need to prove that AI is improving decisions, accelerating execution and helping finance shape enterprise outcomes,” said Steecker. “They must not mistake activity for impact. Counts of pilots, tools rolled out or use cases in production show that finance is moving, but they do not prove that AI is delivering the value boards now expect.”
Figure 1. Realized Vs Expected Value from AI Tools
Source: Gartner (May 2026)
The chart, derived from a March 2026 survey of 204 finance leaders, shows why CFOs must shift their focus from AI deployment to AI value creation. Steecker said the question for finance leaders is no longer whether AI tools are being used, but whether they are improving decisions, accelerating execution and strengthening finance’s influence on enterprise outcomes.
Report Card Shows Progress and Value Gaps
The clearest outcome so far has been efficiency. Among finance organizations that have adopted AI, 66% reported greater efficiency and productivity as a top benefit. Steecker urged CFOs to now look beyond productivity-led AI use cases and focus more directly on value creation.
Finance’s lower grades are concentrated in implementation speed and analytics impact. Gartner found that 63% of finance organizations said AI implementation was slower than expected in 2025. Analytics-related use cases also remain difficult to convert into high impact, with financial forecasting and insight generation among the lowest-rated use cases.
“Finance leaders see the potential of AI analytics, but too many initiatives are still aimed at incremental improvements rather than material business problems,” said Steecker. “The best opportunities are in areas that matter to the business and are difficult to diagnose using traditional methods.”
To improve finance’s AI grade, Gartner recommends CFOs measure AI portfolio progress by realized value rather than deployment volume, rebalance investments beyond productivity-led use cases, address stall points such as cost overruns and rigid team mindsets, and prepare for embedded AI assistants and AI-enabled simulation by strengthening data, talent, process and governance foundations.
“Finance does not need to prove that it can use AI anymore,” said Steecker. “It needs to prove that AI can change how finance supports better business decisions.”
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