What AI Can and Can’t Do in Cost and Profitability Analysis
Sponsored by the Profitability Analytics Center of Excellence
Commodity prices swinging. Tariffs shifting. Margins under pressure from every direction. And now AI showing up in every tool you touch, promising to make the analysis faster, if not always clearer. Cost and profitability teams are being asked to move quicker and explain more, at the exact moment the ground underneath their numbers keeps moving.
This session walks through the judgment behind allocations, variance analysis, cost-to-serve, and scenario modeling, and the decisions a spreadsheet or dashboard never shows you. As more processes run through AI, those decisions get easier to miss and harder to trace.
No hype, no vague AI predictions. A specific look at where AI genuinely helps with this work, where it fails, and what stays entirely on you no matter what’s doing the calculating, or how fast the market is moving underneath it.
At the end of the webinar, you will be able to:
- Separate what the model computes, what AI adds, and what still needs a person.
- Spot when AI speeds up real analysis, and when it just answers with confidence.
- Apply four questions, what, why, who, what if, to any number before acting on it.
- Know what a cost model needs before AI can be trusted with it.