How do you implement agentic AI for automated retail demand forecasting?
Retail demand forecasting agents predict product demand at granular levels to optimize inventory and staffing. Configure agents with access to POS data, inventory systems, weather services, and promotional calendars. The agent models demand using historical sales patterns, seasonal trends, promotional effects, and external factors like weather and local events. Implement SKU-level forecasting with store-level granularity. Support new product demand estimation using similar product analogy. Generate automated replenishment orders based on demand forecasts and current inventory levels. Track forecast accuracy using WMAPE and bias metrics per product category and store. Implement promotional uplift modeling that predicts incremental demand from planned promotions. Generate demand planning reports with scenario analysis for different planning assumptions.