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Typically, we don’t like to make predictions about hype cycles. Will Taylor Swift always dominate the pop charts? When will teenage boys stop doing their hair like that?
These are the questions we can’t answer.
But when it comes to the hype cycle of generative AI in finance, we have some expert insight, for once. On Tuesday, Gartner released its latest hype cycle report, a research series that measures the maturity, commercial viability, and opportunity presented by emerging technologies. This time around they looked at finance AI, or the deployment of generative AI and other related analytics in the finance function.
The takeaway: Don't believe the hype. Or, rather, understand and listen to the hype.
Out of the AI-related technologies Gartner measured, including prompt engineering and cloud analytics, generative AI is “at the very peak of inflated expectations,” an early stage of a technology’s life cycle when initial publicity and hype are tempered by “scores of failures,” per Gartner.
“A range of publicly available generative AI tools have generated enormous publicity for the technology in the last two years, but as finance functions adopt this technology, they may not find it as transformative as expected,” Mark McDonald, senior director analyst in Gartner’s finance practice, said in a statement.
Given its current hype cycle placement, “Gartner experts forecast disillusionment with GenAI tools in finance in the future.”
Still, ask anyone: There are useful applications of generative AI in finance, but those experts warn that “they just might not be as transformative as many finance leaders think right now.”
“Finance functions could also use GenAI to do things they currently don’t,” McDonald said. “For example, comparing an inbound vendor invoice with the negotiated pricing to make sure charges align with the agreed prices.” Also, other tasks that require textual analysis, like evaluating contracts, are a good fit.
“The main strengths of GenAI in finance are its ease of access and simplicity of use,” he continued. “With many vendors offering private in-house GenAI solutions, harnessing such tools is largely a case of teaching employees how to use it and under what circumstances it is a reliable solution.”