When concept drift is detected in the pipeline, it means that the model performance has degraded over time due to changes in the underlying data generating process. This requires retraining the model with new data that reflects the current situation and updating the model parameters accordingly. Reference:Use pipeline parameters to retrain models in the designer - Azure Machine Learning | Microsoft Learn,Retraining Model During Deployment: Continuous Training and Continuous Testing