The safest useful application
A checker reads work a person produced and flags what looks wrong. If it is right, an error is caught. If it is wrong, someone spends ten seconds dismissing a flag.
The downside is bounded and small, which is not true of most AI applications, and the upside compounds because caught errors have real costs.
What checkers do well
- Quotes against the price list and current terms
- Contracts against your standard clauses, flagging deviations
- Job specifications against safety and compliance requirements
- Reports against the source data they cite
- Marketing claims against what you can actually substantiate
- Invoices against the order and the delivery record
The economics are unusually clear
One prevented pricing error on a large quote pays for a year of the system. Unlike most AI business cases, this one does not depend on time savings that are hard to measure.
Ask what your last five expensive errors were and whether a careful reader would have caught them. Usually four of five would.
Tuning the flag rate
Too many flags and people stop reading them; too few and errors pass. Start conservative — flag only high-confidence problems — and widen as trust builds.
Track what proportion of flags are acted on. Below about 30% and you are training people to dismiss without reading.
Where it fits in the process
- The person produces the work as they always have
- The checker runs automatically on submission
- Flags appear before approval, with the reason and the reference
- The person accepts or dismisses, with dismissals logged
- Weekly review of what was caught, which tunes the rules