AI Is Coming for Data Catalogs. That Is a Good Thing.

Google’s Knowledge Catalog Enrichment Agent points to a bigger shift in enterprise AI: data catalogs are becoming active, intelligent systems instead of static filing cabinets.

The tool is a command-line AI agent that helps generate Metadata as Code for Dataplex Knowledge Catalog. In plain English, it can read source material like documents, BigQuery schemas, SQL patterns, user feedback, and GitHub repositories, then turn that context into structured descriptions for data assets.

That matters because most companies have a metadata (data about their data) problem. Teams collect huge amounts of data, but the meaning of that data often lives in scattered documents, old queries, tacit knowledge, or code. When metadata is missing or weak, people waste time asking basic questions: What does this table mean? Can I trust this field? Who uses this data? Is this metric still correct?

Google built something to help close that gap using AI

The important part is not just that the agent writes descriptions. It creates reviewable drafts. Humans can inspect, refine, evaluate, and decide when to publish them. That is the right pattern. AI should not silently rewrite your data catalog. It should draft, explain, and prepare work for approval.

Better metadata makes analytics faster. It makes AI systems safer. It helps employees find the right data and avoid misusing the wrong data. As more teams build AI agents on top of internal data, clean context becomes a competitive advantage.

What should you do about it?

1. Audit your most important datasets. Find the tables that people use often but do not fully understand.
2. Gather the context around them. That includes docs, dashboards, SQL examples, business definitions, and feedback from users.
3. Test AI-assisted metadata generation on a small, high-value area before rolling it out broadly.
4. Keep humans in the loop. Treat AI-generated metadata like a strong first draft, not the final truth.

I have always been a fan of data catalogs. They are one of the places where that context will either be organized, or become a bottleneck. Good on Google for building this!