Data Lakehouse Open Standards for AI Agents

This article discusses how AI agents, which operate at high speed and volume, expose the weaknesses of closed data architectures. It explains that open standards such as Iceberg table formats, REST catalogs, and federated query engines are essential to avoid data silos, inconsistent governance, and costly data copies. The piece argues that open lakehouse foundations enable agents to access authoritative data reliably, contrasting closed silos with open systems. It emphasizes that the metadata layer is critical for agent success and that cloud providers are converging on open standards like Iceberg to support agentic workloads.