AI ROI, computed honestly.

Most ROI calculators flatter the business case. This one includes run costs, adoption reality, and a 3-year view — the same arithmetic we put in front of CFOs. Adjust the sliders; numbers update live.

ROI/01Model your initiative

People whose work is affected25

headcount touching the automated workflow

Hours saved per person, per week4 hrs

be conservative — measured pilots, not vendor decks

Fully-loaded hourly cost (USD)$45

salary + benefits + overhead, divided by working hours

One-time implementation cost ($k)$120k

build, integration, change management, training

Annual run cost ($k/yr)$40k/yr

inference, infra, licenses, maintenance engineering

Realistic adoption rate70%

the number everyone forgets — start at 60–75%

Gross annual value of hours saved

team × hours × 52 weeks × rate × adoption

Year-1 net (after impl + run)

the number to defend in the budget review

3-year ROI

(3 yrs net benefit − impl) ÷ total 3-yr investment

Payback period

—

months until cumulative net benefit covers implementation

ROI/02How to read the output

If payback exceeds 18 months, narrow the scope before killing the idea — most AI initiatives fail on breadth, not on the core use case. A thinner workflow with 80% adoption beats a platform with 30%.

If the model only works at 100% adoption, it doesn't work. Adoption is an engineering deliverable (latency, UX, trust), not a training-session outcome. Budget for it.

If run costs dwarf savings, the unit economics need design work — model routing, caching, and right-sizing routinely cut inference costs 40–70% (we've published the ledger on our blog).

Want this model built for your numbers?

Bring your workflow to a 30-minute call. We'll pressure-test the business case before anyone writes code.

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