Building an AI-Ready Knowledge Architecture

The forcing function of AI continues to reshape how organizations think about data architecture. It's no longer enough to simply centralize information in warehouses and lakes. AI systems require context, lineage, relationships, governance, and semantic understanding to deliver trustworthy outcomes at scale. The solution? An AI-ready knowledge architecture. On this episode of DM Radio, we'll examine the nexus of semantic intelligence and metadata management as core components of an enterprise knowledge graph. Eric Kavanagh will host Sebastian Schmidt of Digital Science, who will demonstrate why a solid data foundation and intelligence layer - such as provenance tracking - are crucial for AI trust. They will show how AI Agents, RAG Architectures, and next-generation discovery platforms will only coalesce around trusted, contextualized data. Attendees will learn: Why semantic intelligence is becoming the control plane for enterprise AI How metadata, lineage, and provenance improve trust and reduce hallucinations Why knowledge graphs outperform siloed architectures for AI-driven discovery How AI-ready architectures support RAG, agentic AI, and contextual reasoning at scale