
AI does not predict events but models uncertainty to prepare for multiple scenarios. The distinction matters because expecting AI to forecast specific disruptions sets unrealistic standards and obscures the real value. A probabilistic model quantifies the range of outcomes around each forecast and translates that uncertainty into buffer sizes, replenishment proposals and exception alerts. When a disruption occurs, the operation is already positioned to absorb a wider range of outcomes than a single point estimate would allow. Scenario simulation extends this further by showing how the plan would behave under specific stresses, which is what lets teams compare responses before committing to one.