Generative artificial intelligence, or GenAI, will have the most effect on forecast/budget variance explanations (66%), the survey’s respondents believe.

“Forecast and budget variance explanation as the top choice reflects the availability of embedded GenAI interfaces within business intelligence tools,” explained Clement Christensen, senior director analyst, research, in Gartner’s finance practice.

“This enables users to perform natural language queries to quickly assess known common causes of variance.”

Respondents then anticipate revenue/spend data classification (44%) and management reports (34%) as the next most impactful use cases.

These are then followed by financial/regulatory reporting draft creation (30%); contract and document review (29%); competitor research and analysis (25%); coding assistance (25%); finance support staff response augmentation (17%); translation of policies (15%); and generation and interpretation of policies (15%).

When it comes to potential challenges around implementing GenAI, finance leaders expect to contend with issues around talent, data accuracy and governance, technical compatibility, budgeting and change management, in particular.

Data accuracy and talent limitations cause slightly more concern, the technological research and consulting firm noted, although the fairly even distribution of other potential barriers reiterates financial leaders’ relatively limited experience with GenAI.

“GenAI is all about large language models, but the core of finance’s work isn’t in natural language, it’s in numbers, so many finance leaders are still waiting to see a GenAI application that can reliably handle complex calculations,” said Christensen.

“For most finance teams, GenAI will likely be an interface to interact with other AI models based on machine learning, or other non-generative models for the next few years.”

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Gartner advised that finance leaders seeking to adopt GenAI in their function should keep an open mind and involve key stakeholders, including the finance leadership and IT teams, to discuss priorities and expectations.

Further, they should also identify when to approach vendors to determine which GenAI offerings are worth acquiring for the organisation’s needs.

Finally, CFOs should audit critical data with respective owners before implementation, to decide what modifications must be implemented for use by a GenAI model.