AI thrives on real-time, high-quality data—but most streaming pipelines are fragile, costly, and overly complex. Messy schemas, dropped records, and late-arriving data wreak havoc on AI models, leaving engineers trapped in endless firefighting. So how do you bridge the gap between cutting-edge AI and the chaos of real-time event streams? In this session, we’ll show you how to build AI-ready, self-healing data streams with Databricks Delta Live Tables (DLT) and Confluent Kafka. Learn how to automate schema evolution, enforce data quality with expectations, and optimize pipelines with serverless compute. We’ll then explore the next evolution—AI-powered streaming—leveraging AI Functions, Foundational Models, and Agentic Frameworks to unlock real-time AI at scale. Whether you’re an engineer, data scientist, or architect, you’ll leave with actionable strategies to fuel AI models with pristine, real-time data. Don’t let bad pipelines hold back great AI—upgrade your streaming game today!