How Should FP&A Be Using AI?
Key takeaways
AI gives FP&A teams more time to think, not just calculate
Small wins like faster variance analysis build confidence without major disruption
FP&A shouldn’t fear AI—like Excel before it, it’s a tool to amplify expertise
Augmentation, not automation, is the right entry point for AI in finance
Adoption starts with time savings, not transformation
Why FP&A Is Naturally Cautious About AI
FP&A teams are often the most trusted thinkers in any organization. They’ve built their credibility on precision, self-reliance, and a deep command of financial models. And they’ve done it largely with Excel, ERP exports, and old-school logic.
So when AI shows up and suggests doing the thinking for them, there’s bound to be hesitation.
Unlike calculators or spreadsheets—where every formula can be inspected—AI can feel like handing over the wheel. Even if the destination is the same, not knowing exactly how you got there can be unsettling.
Start Small, Prove Value Early
AI adoption in finance shouldn’t start with a vision of mass automation. Instead, it should start like Excel once did: as a productivity tool. The best AI deployments begin with narrow, measurable wins that make an analyst’s life easier.
Examples:
- Auto-clean ERP data to eliminate rework
- Suggest variance drivers without digging through a dozen pivot tables
- Generate base-case forecast scenarios with one click
- Allow CFOs to ask questions like “What’s driving margin compression?” and get answers in seconds
These aren’t revolutionary. But they’re time-saving, trust-building, and momentum-generating.
A Practical Path for FP&A Teams
- Pick a visible pain point—think recurring manual work like monthly forecast updates
- Implement a narrow AI tool that complements your workflow (not overhauls it)
- Compare results side by side with the old method
- Measure time saved, not just accuracy improved
- Share wins across the team to shift the mindset from threat to value
The goal isn’t to turn finance into data scientists. It’s to free up time so smart people can do smarter work.
What Changes – and What Doesn’t
AI doesn’t change the fundamental value of FP&A: being trusted advisors to leadership. What it changes is how quickly and confidently they can deliver insight. The best analysts won’t be the ones who write the best macros. They’ll be the ones who can explain the story the AI is telling—and challenge it when necessary.
In short, AI isn’t the driver. It’s cruise control. FP&A is still at the wheel.
FAQs
Q1: Will AI replace FP&A roles?
No. It replaces repetitive tasks—data prep, reforecasting, reconciliations—not the thinking, interpretation, or business judgment.
Q2: What’s the first thing we should automate?
Look for low-risk, high-friction tasks: data cleanup, variance flagging, or baseline forecast generation.
Q3: Do we have to change platforms or workflows?
Not at all. Good AI tools integrate directly into your current environment—Excel, Power BI, or ERP dashboards.