AI Quality Tiers: When 85% Accuracy Is Fine

Accuracy targets make sense only after we price the failure mode and the quality layer that catches it. A human review queue, spot check, deterministic gate, or no-automation decision changes how much model accuracy is worth. That tiering prevents wasted tuning on cheap errors and premature automation where one miss causes real harm.