
AI-driven demand planning software replaces single-number forecasts with probability distributions, which lets the algorithm size buffers against realistic upper ranges of demand rather than against historical averages. Modern platforms also update the forecast continuously as new sales data arrives, surface SKUs at risk weeks ahead of the stockout, and recommend the next action, whether that is to reorder, rebalance, or escalate. The shift is from forecasting better to deciding earlier, which is the part of the problem that actually prevents the stockout.