Agentic AI is rewriting the rules of enterprise data engineering, turning passive infrastructure into intelligent systems that act, adapt and automate at scale.Gone are the days when platforms simply stored and queried data. Today’s data stacks are being rearchitected to support agentic workflows — systems where metadata, governance and orchestration layers work in concert to guide machine reasoning. Snowflake Inc.’s embrace of open formats such as Apache Iceberg signals a broader shift: Enterprises are building environments where intelligence is embedded into the fabric of data itself

As enterprises race to adopt artificial intelligence and automate decision-making, metadata standardization has become a defining barrier to progress. Without a shared framework for describing, organizing and governing data, organizations risk building AI on a fragmented and unreliable foundation.Despite advances in cloud storage and compute, metadata remains disconnected, inconsistent and often manual. Industry experts argue it’s not about speed or cost anymore — it’s about shared meaning