Running AI-Driven Inventory in the Real World: Integration and Operations

Even an accurate forecast becomes useless if no one trusts it, exceptions overwhelm the team, or the integration with the rest of the business is fragile. This course steps past the modeling and into the operational discipline that decides whether AI-driven inventory actually delivers in a business. You will work through written scenarios that mirror the rollout, first quarter, and steady-state operation of an AI-driven inventory system. The course also addresses the human roles that remain essential, including category managers, buyers, and warehouse teams. What you'll learn: - Plan rollout in phases that build trust with planners and category managers - Design exception handling for new products, promotions, supplier issues, and unusual demand events - Integrate AI recommendations with ERP, ordering systems, and warehouse management workflows - Build monitoring dashboards that surface model drift and changing demand patterns early - Update human roles so planners focus on judgment calls rather than routine reorders - Plan model retraining, periodic reviews, and the long-horizon evolution of the system The course begins with the rollout phase, moves through exception handling and integration, and finishes with monitoring and long-term evolution. A capstone written exercise asks you to draft a one-year operations plan for an AI-driven inventory system in a real business scenario. This course is designed for supply chain leaders, operations analysts, and technology integrators bringing AI tools into established businesses. No prior AI experience is required. The course respects how real operations teams work and treats trust, exception handling, and human judgment as first-class concerns.