Supply chains shift from decision support to supervised autonomy as multi-agent systems gain real execution authority

For years, enterprise logistics teams have relied on predictive demand models, dashboards, and weekly scheduling runs to translate forecasts into freight and inventory plans. The new inflection point is less about better prediction and more about moving the execution loop—routing, rebalancing, and allocation—closer to the model itself. A growing set of deployments and public trials suggests that multi-agent AI systems are beginning to replace the final