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Finance leaders expect to see the biggest impact of generative AI in forecast and budget variance explanations, according to a new Gartner survey.
Gartner surveyed 100 finance professionals in November to identify the top anticipated use cases for GenAI in finance. Roughly two-thirds (66%) of respondents put forecast and budget variance explanation in their top three, and and for 26%, it was their first choice.
Respondents’ top choice “reflects the availability of embedded GenAI interfaces within business intelligence tools,” Clement Christensen, senior director analyst of research in Gartner’s finance practice, said in a news release. “This enables users to perform natural language queries to quickly assess known common causes of variance.”
Other popular use cases for GenAI in finance include:
- Classifying revenue/spend data: 44% of respondents put it in their top three, and 10% made it their first choice
- Drafting management reports (34%, 7%)
- Creating financial/regulatory reporting drafts (30%, 7%)
- Reviewing contracts and documents (29%, 13%)
Finance leaders also identified expected challenges around GenAI. According to Gartner, respondents “expect to contend with issues around talent, data accuracy and governance, technical compatibility, budgeting, and change management.” They’re slightly more worried about data accuracy and talent limitations, Gartner found.
Experts agree that organizations need buy-in from employees in order to succeed with their AI implementation, CFO Brew recently reported.
“Finance leaders see potential in the accessibility of GenAI in finance, but valid questions on reliability, accuracy, auditability, and cost, as well as data privacy and security, still remain,” Christensen said.