The world moved and the model did not. A model is a snapshot of relationships learned from historical data — when the world underlying those relationships changes, the model's assumptions quietly stop holding, and performance degrades in a way no error message will ever announce.
Models fail silently. They keep returning confident, plausible-looking answers that are simply wrong, with no crash, no error, nothing that would trip a standard software alert — the only way to catch this is to watch the inputs and predictions continuously, because the ground truth needed to know an answer was wrong often arrives late, or never.