When large language models (LLMs) fail, they do not just glitch; they haunt enterprises with hallucinations and personally identifiable information (PII) leaks. The breakdown of generative AI is a data problem masquerading as a model problem. This session offers a diagnostic roadmap for building a trusted foundation. Lakshmi Nair analyzes a framework in which metadata acts as the bridge to agentic action, transforming “Ghost Data Products” into fully governed contextual assets. Attendees will learn how to stabilize retrieval-augmented generation (RAG) pipelines and turn their data into a primary AI differentiator.