Inventory Replenishment Planning Agent for Retail Managers

Retail inventory managers will learn how to build and deploy a Copilot Studio AI agent that automates stock replenishment from demand forecasting through order generation. The scenario covers how an agent ingests logistics data from ERP and email systems, uses machine learning to forecast demand at the store and product level adjusted for upcoming campaigns, applies inventory optimization models to eliminate overstock and stockouts, flags slow-moving items for markdowns, generates replenishment orders for manager approval, and pushes confirmed orders directly to the ERP. After this guide, inventory managers can see how AI dramatically reduces the manual effort behind replenishment cycles.