How to hit profitability and run scenarios with 3 AI Prompts
This edition isn’t theory and this change might feel uncomfortable.
Once, FP&A was the quiet engine room of the business. Crunching numbers. Reconciling budgets. Running static plans that were outdated the moment they shipped.
The playbook was clear:
Finance builds a model.
Leaders guess the future.
Everyone hopes it works.
It was tolerated because it was the best we had. But that world is gone.
Imagine you want to close 2 underperforming stores. Open 2 in growth regions. And model impact on:
Gross margin
Team efficiency
Working capital
Old FP&A playbook:
2 analysts
1 week
5 spreadsheets
3 review loops
New AI FP&A playbook:
5 minutes
One prompt
10 variations
Instant outputs
This edition isn’t theory. It’s a live experiment.
We asked ChatGPT O3 to help model real-world strategic planning scenarios for a bike retail business called Born2Cycle. Our goal is to show CFOs and FP&A how AI can completely reshape planning, fast.
A Broken Process We Accepted for Too Long
Ask any CFO:
How long does it take your team to model the impact of closing 10 stores and opening 5 more?
One week? Two?
And by then, how many decisions have already been made based on gut, not data?
Here’s the uncomfortable truth: The speed of business outpaced finance years ago.
So what did FP&A do?
They chased.
They explained.
They reconciled.
FP&A became historians of what went wrong, not architects of what comes next.
How AI is Making Finance Strategic
AI doesn’t just speed up modeling. It removes the excuse of not modeling at all. With tools like ChatGPT, you can run 20 what-if scenarios in under an hour across:
Pricing
Headcount
Vendor cuts
Store openings
Product launches
Territory planning
I’m showing you a live experiment of how CFOs and FP&A teams can evolve from back office to value center with AI.
We used ChatGPT O3 to simulate how finance teams can handle real-world strategic planning. You’ll use 3 prompts to:
Instantly generate 9 board-level scenarios.
Decide which stores to close, using EBIT, HR reviews, and Google ratings.
Pick the next best locations using demographic, cycling, and competitive data.
This is the future of what’s possible, and it won’t be coming next year.
It’s here… Let’s dive in.
Prompt 1: Scenario Generation
Model: ChatGPT: o3 because it’s creative has advanced reasoning and can do data analysis using Python.
Files to upload: