To-date, data management initiatives were designed to support reporting and analytics.  With the rise of generative AI , data strategies must now enable reasoning, decisioning, and autonomous systems at a higher scale and magnitude than ever before. Enterprises have largely focused on cloud, data‑lake modernization and data catalog initiatives, but these requirements were not designed for AI. The lack of "AI-ready data" is proving costly, yielding inaccurate results, or failing in production outright. Enterprises are realizing that without "context" AI cannot meet expectations.AI systems need context to reason over enterprise data. Business definitions, logic, and concepts that often lie in tribal knowledge or unstructured forms are not presenting in AI workflows. Ontologies and "context layers" are rapidly emerging as critical building blocks to successful AI outcomes. This webinar demystifies these semantic concepts and outlines how they transform fragmented data assets into an AI-ready foundation.