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FP&A pros anticipate AI-driven headcount reductions

August 27, 2025
in Accounting
Reading Time: 4 mins read
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FP&A pros anticipate AI-driven headcount reductions
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The mass adoption of AI in the financial planning and analysis world has led to predictions that headcount will likely shrink over time because fewer people will be needed in the future. 

This is according to a survey of 258 FP&A professionals conducted by business planning platform Drivetrain. The survey found, among other things, that many believe AI will lead to smaller, more efficient teams: 65.5% think that junior and entry-level roles are at most risk of automation, and 50% believe that AI will reduce the headcount required for the FP&A function. 

“This paints a picture of transformation, not just through tools, but through talent,” said the report. “Tasks once handled by entry-level analysts, data prep, reconciliations, basic modeling are increasingly being absorbed by AI.”

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The people who will be on these smaller teams are expected to come from different backgrounds and have different skill sets. The report said there is already a new wave of FP&A talent emerging from outside traditional finance backgrounds as many finance leaders recognize a growing need for hybrid roles that blend finance fluency with technical expertise. 

This is likely because the skills FP&A providers are looking for in their staff are also changing: survey respondents anticipate that the most valuable skill in the future will be “data storytelling/communication,” with an overwhelming 87% expecting such capacities to be critical within the next three years. Following this will be constructing the basis for such stories, as 65% said financial modeling and analytics will also be critical. Not quite as important, at 39%, was finance business partnering. 

This fits with the primary use cases of AI so far among FP&A professionals. The most common use of AI in this realm is report writing/commentary generation, at 57%, followed by Excel automation at 48%, and presentation and deck creation at 37%. Ranked last were the actual analytical parts of FP&A: 30% use it for variance analysis and 28% use it for forecasting and planning. 

“It’s clear that the most valued skills blend domain expertise with technological fluency and business acumen. Finance teams are no longer expected to simply run the numbers they must explain them, act on them, and increasingly, guide cross functional teams through uncertainty,” said the report. 

The actual tools they’re using are generally not very sophisticated. Public chatbots like ChatGPT are the most used solutions by a mile, with 93% of respondents having incorporated it into their work. In contrast, only 22% use Microsoft Copilot, 20% use BI tools, and only 17% use specialized FP&A programs made specifically for their profession. Despite this, only 4% said AI has not given them any time savings at all, while 54% say it has saved them between one to five hours per month. 

One might wonder whether it is wise to use public AI models for financial work involving sensitive data, as doing so tends to send the data to third parties (namely, the companies running the public models.) While 47% of the respondents said they were concerned about data breaches due to AI, only 22% have a detailed AI policy with clear guardrails that might possibly mitigate such risks. In contrast, 34% either have no policies or guidance at all, or aren’t sure yet. 

“As AI tools become integral to planning/ reporting, the absence of governance policies creates risk. The gap between adoption and policy is wide,” said the report. 

Considering the survey findings, Drivetrain recommended treating AI as a team capacity versus a personal individual skill; and formalizing approaches to AI governance. Leaders should be proactive and lead the narrative versus reacting to someone else’s; match hiring patterns to the current moment; and experiment with real world use cases. 

“AI won’t make FP&A obsolete. But it will change what great FP&A looks like. The leaders who act now, by building skills, setting policies, and testing use cases, will be the ones who shape what comes next,” said the report. 

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