Building an Agent-Ready Data Warehouse: What Traditional Architectures Do Wrong

Traditional data warehouses are not inherently ready for AI agents, as simply providing access does not teach the agent the business context or meaning behind the data. An agent might generate technically correct SQL queries but arrive at wrong conclusions because it lacks an understanding of business rules, data completeness, and metric definitions. To address this, a more robust architecture is needed, featuring a semantic layer to define business entities and relationships for the agent. The proposed solution includes a "decision contract," a machine-readable specification that governs how data can be used for specific decisions, and separating the agent's ability to recommend from its ability to execute actions.