Explores how AI transforms CDN performance by predicting demand, prepositioning content, and dynamically routing traffic across edges. It covers real-time anomaly detection, adaptive caching, and ML-driven load balancing that cut latency and cost. The post weighs privacy and observability trade-offs, outlines A/B methods for tuning models, and shares practical wins from congestion-aware routing and origin offload.