Model Drift Trend 2026

Machine learning models can gradually lose accuracy as real-world data shifts. This phenomenon, known as model drift, occurs when relationships in new data diverge from training patterns. Data scientists and ML engineers monitor drift to trigger retraining, ensuring reliable predictions. Businesses benefit by maintaining model performance, reducing costly errors in finance, healthcare, and e-commerce.