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Gartner Says Most Finance Organizations Lag Other Functions in AI Implementation


Gartner research shows that four out of five finance leaders anticipate the cost and effort they allocate to deploying AI within finance will increase over the next two years, with 52% of finance leaders expecting cost and effort to increase by more than 10%. However, finance is currently well behind most other business functions when it comes to investments in AI by the organization.

“This lag is even bigger if with generative AI with just 1% of finance functions having adopted or an intention to invest in the technology,” said Steecker. “This is compared to customer facing and IT functions where approximately 10-20% have adopted or intend to invest in generative AI.”

Finance Leaders Cite Other Priorities as Top Reason Preventing AI Investment
Finance leaders whose functions are not yet using AI cited four primary reasons: other priorities, lack of technical capabilities, low-quality data, and insufficient use cases. Three of these commonly cited reasons (lack of technical skills, suboptimal data quality, and insufficient use cases) are related to workflow- and capability-based limitations.

However, the most frequently cited reason for not using AI is that finance leaders have other priorities. “This speaks to an important aspect of finance leaders’ beliefs about AI, which is that it is a discrete project that would need to be added separately to their function’s transformation roadmap,” said Steecker. “What this perspective underappreciates is that AI can be a critical enabler of finance leaders’ ‘other priorities,’ such as more dynamic financial planning or close and consolidation efficiency.”

Finance Organizations’ AI Use So Far Is Highly Variable but Largely Impactful
Finance organizations currently using AI (i.e., developing pilots, using AI in production, and scaling AI solutions) are doing so in a diverse set of areas within finance. No one area of AI use in finance is disproportionately represented among early AI adopters. The three most common areas of AI use within finance include accounting support, anomaly/error detection, and financial analysis.

“Despite varied uses of AI within finance, the experience has been largely positive. This should be encouraging news for CFOs and other finance leaders who are contemplating whether they should invest and, if so, where they should direct that initial investment,” added Steecker.

Additional information is available to Gartner clients in the report The Current State of AI Use Within Finance: 2023 Insights. Nonclients can watch a short video Gartner Experts on AI in Finance: The Next Industrial Revolution or the webinar Move Towards an AI-Forward, Autonomous Finance Future.

About the Gartner Finance Practice
The Gartner Finance practice helps senior finance executives meet their top priorities. Gartner offers a unique breadth and depth of content to support clients’ individual success and deliver on key initiatives that cut across finance functions to drive business impact. Learn more at https://www.gartner.com/en/finance/finance-leaders. Follow Gartner for Finance on LinkedIn and X using #GartnerFinance to stay ahead of the latest expert insights and key trends shaping the Finance function. Visit the Gartner Finance Newsroom for more information and insights.





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Leah Sirama
Leah Sirama
Leah Sirama, a lifelong enthusiast of Artificial Intelligence, has been exploring technology and the digital realm since childhood. Known for his creative thinking, he's dedicated to improving AI experiences for all, making him a respected figure in the field. His passion, curiosity, and creativity drive advancements in the AI world.
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