AI in Retail: Personalization, Demand Forecasting, and Supply Chain Optimization

AI is transforming retail operations across the entire value chain. Recommendation engines: collaborative filtering for "customers also bought" (Netflix-style matrix factorization), content-based for similar products, and hybrid approaches. Amazon attributes 35% of revenue to recommendations. Dynamic pricing: use ML models trained on competitor prices, inventory levels, demand elasticity, and seasonality to adjust prices in real-time. Demand forecasting: Facebook Prophet handles seasonality and holidays well for weekly/monthly forecasts; LSTM neural networks capture complex temporal patterns for SKU-level daily forecasting. Supply chain: AI-powered vendor selection using multi-criteria optimization, automated reorder point calculation based on lead times and demand variability, logistics route optimization with OR-Tools or Google OR. Computer vision applications: checkout-free stores (Amazon Go), shelf audit automation, visual search for products. Implementation roadmap: start with demand forecasting (fastest ROI), add recommendations, then pricing optimization.