Why UAT collapses on AI systems

UAT for AI systems does not work the way UAT for traditional software works. Two testers running the same query get different model answers; three testers reach three different conclusions about whether the answer was right. The signal collapses.

The right shape: quantitative testing runs first, producing scores against a defined golden dataset. UAT then runs on top — humans test usability, tone, and edge-case judgment, as the human layer on a system already proven to be factually correct.

Without that layer first, you are asking humans to certify quality on a system whose quality varies between runs. That is not a test. That is a hope.