More than half of Finance functions have been using artificial intelligence in 2024, with 58% using the technological advancement, according to a survey by Gartner, Inc.
The Gartner survey, which polled 121 finance leaders, also found that half of the 42% of Finance functions that are not currently using AI are planning implementation.
"AI adoption in the finance function is advancing quickly," says Marco Steecker, senior director, research in the Gartner finance practice.
He adds that it is also encouraging to note that two-thirds of finance leaders feel more optimistic about AI’s impact than they did a year ago, particularly among those who have already made progress leveraging AI solutions.
"In this survey last year, other 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," Steecker notes.
Gartner says there are four main use cases that stood out amongst those adopting AI in finance:
1. Intelligent process automation (used by 44% of finance functions) — Automation that leverages the AI capabilities of existing automation tools (such as RPA) to enhance information processing.
2. 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).
3. Analytics (used by 28% of finance functions) — The creation of better financial forecasts and results analysis that can lead to improved decision making.
4. Operational assistance and augmentation (used by 27% of finance functions) — Emulation of human-judgment-based decisions in operations through AI (often generative AI).
Data and talent shortages present challenges
Gartner named that the top two challenges finance leaders face in relation to AI adoption were inadequate data quality/availability and low levels of data literacy/technical skills.
"Because interest in AI is rising across the board both inside and outside their organisations, CFOs are finding it tough to source the talent they need to meet their AI ambitions, and this problem is likely to get worse," says Steecker.
He notes that it is therefore essential that CFOs have an overarching functional strategy to identify, acquire and develop AI skills.
CFOs will need to address three primary challenges that hinder finance AI talent plans: a limited understanding of the necessary roles and skills involved in AI implementation; a difficulty attracting and retaining AI talent; and slow progress developing AI skills within existing employees.
In terms of data quality, Gartner experts recommend considering leaving behind a "single version of the truth" data management philosophy because it is almost impossible to attain this kind of perfection given the volume and volatility of data in modern companies.
Gartner says the alternative is a "sufficient versions of the truth" approach that balances data quality with ensuring it is useful in decision making.
