As AI and autonomous agents redefine how systems interact with data, modern data architectures must pivot from traditional analytical models to intelligent, AI-first designs. This session explores how to evolve your architecture to support AI-native use cases by embracing machine-oriented data models, metadata-rich data layers, and unified AI-driven observability. We’ll dive into why data quality and consistency are foundational for accurate RAG (Retrieval-Augmented Generation) and LLM fine-tuning, and how a well-architected, compressed data layer can accelerate low-latency responses. Learn how this intelligent layer becomes the bedrock for building knowledge graphs and enabling reliable contextual grounding for LLMs. In an agentic world, data is no longer just analytical—it’s operational.