Most finance organisations have yet to adopt AI, despite optimistic leadership views towards the technology, according to a survey by Gartner.
The survey of 130 finance leaders and 91 associates in administrative support functions in June 2023 revealed that 61% of finance functions either have no plans for AI implementation or are still in the initial planning phase.
Only 9% of finance organisations are in the scaling and using phases, compared to 20% of other administrative support functions, such as HR, legal, real estate, IT, and procurement.
“Despite AI’s potential, most finance functions’ AI implementations have remained limited,” says Marco Steecker, senior principal in the Gartner Finance Practice. “As they begin to chart out a plan for how best to prioritize that additional investment, CFOs should partner with their finance leadership teams to compare their current progress against their peers’ and identify concrete recommendations from early adopters on how best to accelerate AI use in their function.”
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 organisation.
“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,” says 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 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,” says 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 organisations currently using AI (for instance, 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,” says Steecker.