Attendees will gain a practical understanding of how Artificial Intelligence can transform supply chain forecasting from static reporting into a proactive, decision-driven capability. They will learn how machine learning models such as LSTM, ARIMA hybrids, and ensemble methods can improve SKU- and location-level forecast accuracy while reducing inventory imbalance and expedite costs. The session will provide a clear roadmap for operationalizing AI within S&OP and MRP workflows, ensuring models move beyond experimentation into production environments. Participants will also explore scenario-based simulation techniques to manage disruptions such as supplier risk, tariff changes, and demand volatility. Finally, they will leave with actionable strategies to measure ROI, align AI initiatives with executive KPIs, and scale forecasting intelligence across global operations.