"What's the ROI?" is the question that kills — or funds — most enterprise AI projects. Too many teams answer it with a vibe ("it'll save time!") and lose the budget to someone who brought numbers. ROI on AI isn't mystical; it's value minus cost, honestly counted. Here's a framework you can apply to any AI initiative, and present to a CFO without flinching.
The formula (don't overcomplicate it)
ROI (%) = (Annual value − Annual cost) / Annual cost × 100
Payback (months) = One-time build cost / Monthly net savingsEverything else is just filling in those numbers honestly. The discipline is in not fooling yourself on either side.
Want the math done for you? Plug your numbers into the free AI ROI Calculator — team size, hours, cost, expected savings — and it returns annual net benefit, ROI %, and payback period.
Step 1 — Quantify the value (be conservative)
AI value usually comes from one of three places. Pick the one that's real for your use case and measure it:
- Time saved — people-hours × loaded hourly cost. (Loaded cost = salary + overhead, not just salary.) This is the most common and easiest to defend.
- Revenue lift — more conversions, faster sales cycles, upsell. Harder to attribute; use a conservative estimate and label it as such.
- Quality/risk — fewer errors, faster resolution, avoided incidents. Quantify the cost of the thing you're preventing.
Apply an adoption discount. A tool that saves 5 hours/week only delivers that if people actually use it. Multiply by a realistic adoption rate (50–80%), not 100%.