All terms
Evaluation
Concept Drift
When the data a model sees in production changes over time, eroding its accuracy.
Definition
Concept drift is when the relationship between inputs and the right outputs shifts after a model is deployed, so its predictions slowly get worse. Real-world patterns change — tastes, prices, behavior — and detecting and adapting to that drift is a core challenge of keeping production AI accurate.