Data Drift

Data Drift is the silent killer of deployed AI models. If a model is trained on pre-pandemic supply chain data, its predictions will fail in a post-pandemic reality. Continuous monitoring and automated retraining pipelines via MLOps are strictly required to detect and correct Data Drift before it impacts operational intelligence.