How is AI-driven raw material planning different from MRP?

AI-driven raw material planning forecasts consumption directly at the component level and calculates dynamic buffers based on probabilistic scenarios, while MRP derives requirements top-down from finished goods forecasts using deterministic logic. Each MRP calculation step inherits the errors of the previous one, amplifying variability upstream, the bullwhip effect. Where MRP tells planners what to order based on a single-point demand assumption, AI-driven planning tells them how much buffer they need given the realistic range of outcomes that could occur.