How does AI amplify a reputation crisis?

Two mechanics make AI crisis amplification distinctive. First, synthesis: an AI engine reading ten articles about an event does not produce ten different summaries; it produces one consolidated narrative that reads as confident fact, and that narrative is what users see. Second, source-set persistence: once the engines have absorbed a story into their training corpus or their retrieval index, the narrative tends to persist even after fresh contradicting information emerges, because the engines weight breadth of citation over recency. The practical effect on a crisis is that the AI version of events can be both worse and more durable than the press version. Daily AIQ monitoring during a crisis catches the formation, identifies the sources the engines are weighting, and points to where source-level intervention will actually move the picture.