Most finance teams are racing to put AI on top of their data. Almost no one is asking the more dangerous question: what happens when the AI is confidently wrong?
In this live session, I'll pull up a real-world FP&A dashboard reporting a $255M revenue "variance" — a number alarming enough to trigger a board-level demand crisis. Then, live, we'll take it apart and find out it was never a real business problem at all. It was bad data, dressed up by a confident system.
You'll watch the exact thought process a senior finance professional uses to catch this before it reaches leadership — and learn the framework you can apply to any number that lands on your desk.
What you'll walk away with:
The 3 checks that come before trusting any variance — completeness, allocation logic, and underlying assumptions (FX, mappings) — and how to run them in minutes.
How to spot a "data artifact" vs. a real business problem — including the tell-tale patterns (like uniform misses across markets) that scream bad data, not bad performance.
A repeatable governance mindset for the AI era — why AI and dashboards don't remove the need for judgment; they raise the stakes on it, and where to look first when something feels off.
Who this is for: FP&A and finance professionals, controllers, analysts, and anyone whose name goes on the numbers — especially if your team is starting to lean on AI tooling.
Bring a number you don't fully trust. You'll leave knowing exactly where to look.
