Thought Leadership
According to Gartner, chief financial officers must steer their AI investments in a more targeted manner, set realistic expectations, and strengthen AI literacy within their teams.
As the use of AI in finance increasingly moves beyond the pure experimentation phase, chief financial officers (CFOs) must manage their AI portfolios with significantly more discipline in the future, according to market research firm Gartner. Financial leaders are implementing this more disciplined approach by defining realistic expectations regarding time to value, balancing short-term productivity gains against broader business goals, and purposefully strengthening AI literacy within their finance teams.
Varying Time to Value Depending on Use Case
A Gartner survey of 160 senior finance executives, conducted between January and April 2026, revealed that use cases such as data extraction, accounts payable and receivable automation, and report generation typically deliver measurable value after just nine to ten months. In contrast, more complex tasks such as data management, extracting insights from data, and forecasting typically require a significantly longer development period before generating value.
Focus on Fast Productivity Gains as a Risk
Marco Steecker, Senior Director Analyst in the Gartner Finance Practice, explained:
“AI adoption has reached a point where CFOs must adopt more deliberate portfolio management. The goal is not to stifle experimentation, but to know where to invest, when to cut underperforming initiatives, and which foundational capabilities to accelerate, especially as AI technology becomes more user-friendly and barriers to experimentation diminish.”
Marco Steecker, Senior Director Analyst in the Gartner Finance Practice
According to Steecker, AI investments in finance are currently concentrated primarily on use cases with a short time to value that boost productivity, such as report generation and process automation. However, CFOs should not allow the appeal of quick results to crowd out more complex use cases that take longer to mature but can improve decision-making, better manage risks, and support revenue growth.
AI Literacy as the Biggest Hurdle
Attracting suitable talent was previously considered the main obstacle to the success of AI initiatives in finance. However, with the growing availability of agentic coding tools, Gartner assesses that this hurdle has shifted to a lack of AI literacy within existing teams. Steecker elaborated: “Low AI literacy is now the most significant barrier finance leaders must address. CFOs should give employees practical opportunities to use AI through project assignments, sandbox experimentation and short, on-the-job activities. This will help finance teams build the skills and confidence needed to get more value from AI.”
(Editorial Team)
