AI Error Risk Cost Calculator (error rate × volume × cost, with and without review)

How it works

Expected errors = outputs × error rate. Without review, expected cost = errors × cost per error. With review, the reviewer looks at the reviewed share and catches a share of the errors there; the rest still reach customers. Cost with review = escaped errors × cost per error + review time (outputs reviewed × seconds ÷ 3,600 × hourly cost). Review breaks even when the cost per error is above review cost ÷ errors caught. This is an expected-value estimate; a single severe error (legal, safety) can cost far more than the average.

⚠ Estimates for information only — not financial advice.

FAQ

How do I measure the error rate?

Take a random sample of a few hundred AI outputs, have experts mark which are wrong, and divide. Repeat after any model or prompt change.

Should I always review everything?

Not always. Where errors are cheap and rare, sampled review may be enough; where one error can be very costly, review everything or keep a human in the loop.

Checked 10 Nov 2026. Expected-value (probability × impact) cost model, as used in risk management (ISO 31000:2018 risk analysis of likelihood and consequence); error and catch rates are your own measurements.