Model Drift occurs when an AI model's performance declines because production data changes over time and no longer matches the data used during training. Drift can reduce prediction accuracy and reliability.
Voice AI teams continuously monitor Model Drift to maintain speech recognition accuracy, language understanding, and conversational quality. Detecting drift early helps determine when retraining or model updates are required.