The adoption of finance artificial intelligence by finance functions has increased significantly in the past year, with 58% using the technology in 2024—a rise of 21% from 2023—according to a survey by Gartner, Inc.
The survey of finance leaders also showed that two-thirds feel more optimistic about AI's impact than they did a year ago, particularly among those who have already made progress leveraging AI solutions. Also, while 42% of finance functions are not currently using AI, half of these are planning implementation.
In this Gartner survey a year before, administrative functions such as HR, legal and procurement were twice as likely to be using or scaling out AI solutions compared to the finance function. This year, the gap is almost nonexistent.
Additionally, by 2026, 90% of finance functions are expected to deploy at least one AI-enabled technology solution, but less than 10% of functions will see headcount reductions, according to Gartner.
Four main use cases stood out among those adopting AI in finance:
Intelligent Process Automation (used by 44% of finance functions): Automation that leverages the AI capabilities of existing automation tools (such as robotic process automation) to enhance information processing.
Anomaly And Error Detection (used by 39% of finance functions): AI-enabled identification and reporting of errors and outliers in large datasets (e.g., internal claims, expenses and invoices).
Analytics (used by 28% of finance functions): The creation of better financial forecasts and results analysis that can lead to improved decision making.
Operational Assistance And Augmentation (used by 27% of finance functions): Emulation of human-judgment-based decisions in operations through AI (often generative AI).
The survey found that finance leaders' top two challenges related to AI adoption were inadequate data quality/availability and low levels of data literacy/technical skills. CFOs are finding it tough to source the talent they need to meet their AI ambitions.
According to Gartner, CFOs will need to address three primary challenges that hinder finance AI talent plans: limited understanding of the necessary roles and skills involved in AI implementation, difficulty attracting and retaining AI talent, and slow progress developing AI skills within existing employees.
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