An AI system handles thousands of transactions successfully. Then one unusual case requires human intervention. A specialist reviews the evidence. A decision is made. The exception is resolved. The workflow continues. What happens to what the organization just learned? This is the gap that enterprise AI architectures almost universally leave unaddressed. The system records that an exception occurred. It may record the final disposition and the timestamp. In more mature implementations it records who made the decision and what action was taken. But recording an event is not the same as creating organizational memory, and that distinction matters considerably more than most governance frameworks acknowledge. An exception is rarely just an operational interruption. It is frequently a signal. It may reveal that a business rule needs refinement because the original conditions it was designed for have shifted. It may show that two policies interact in an unexpected way when they are appli...