01Why most AI ROI cases are wrong
They count savings without subtracting the platform cost. They ignore migration and change management. They forecast year-three savings on year-one assumptions. CFOs see through this immediately.
AI Business · July 5, 2025
Calculating AI ROI: A CFO-Approved Framework
A finance-grade framework for projecting and tracking the ROI of an AI initiative — from baseline to NPV, with the pitfalls finance leaders catch.
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Binate AI
July 5, 2025
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02The five components of an AI ROI case
- Baseline — the cost of the status quo, including hidden labor
- Benefit stack — labor savings, revenue lift, risk avoidance
- Cost stack — build, license, change management, ongoing ops
- Payback period and NPV — finance-grade, with a discount rate
- Sensitivity — what if benefits are 30% lower or costs 30% higher?
03A worked example
Manual claim review: 8 FTEs at $85k loaded cost = $680k/year. Plus $120k/year in errors caught downstream. Total: $800k baseline.
04Categories of value, ranked by credibility
Defensible
CFO-friendly
- Labor hours saved (measured)
- Throughput increase (measured)
- Direct cost avoidance (e.g. fewer chargebacks)
- Revenue lift in A/B test
Soft
Hard to defend
- "Employee satisfaction"
- "Better decisions"
- "Future flexibility"
- Revenue lift without A/B evidence
05The numbers most teams miss
06Track to the metric you promised
Action Checklist
0/5Tracking checklist
07
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Schedule a working sessionThe takeaway
A credible AI ROI case is a finance document, not a marketing one. Baseline honestly, account fully, sensitize the assumptions — then deliver the metric you promised.
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