ML Models Face Accuracy Limits in Predicting Delivery Disruptions

A study published on Bioengineer.org reports that machine learning models demonstrate only modest predictive accuracy when forecasting logistics delivery disruptions. This finding suggests that while AI and predictive analytics are increasingly deployed in supply chain operations, their effectiveness in anticipating delivery failures remains limited, potentially affecting how companies approach risk mitigation and contingency planning strategies.