From Data Governance to Semantic Intelligence

As AI adoption accelerates, many enterprises are hitting the same wall: traditional approaches to data governance, metadata management, and cataloging were not designed to support AI and AI agents operating at scale. Fragmented tools, siloed semantics, and inconsistent definitions make it difficult for both people and AI systems to trust and act on data.

In this webinar, industry expert Mike Ferguson and Collate co-founder and CEO Suresh Srinivas explore how leading organizations are evolving from tool-centric data catalogs and governance toward semantic intelligence, a unified approach that brings governance, context, and meaning together to support analytics, automation, and AI at scale.

Collate co-founder and CTO Harsha Chintalapani will also provide a brief demonstration showing how semantic intelligence is applied in practice, including how data teams design and build AI agents on governed enterprise data.

What You'll Learn:

1️⃣ Why data discovery, governance, lineage, and data quality and observability must work together to support AI-driven use cases

2️⃣ How fragmented semantic layers and tool-specific context limit trust, scale, and reuse across analytics and AI

3️⃣What semantic intelligence means in practice and how it extends beyond traditional data catalogs

4️⃣How shared meaning enables secure, governed access to data for both people and AI agents

5️⃣How semantic intelligence supports the delivery of trusted, consumable data products with meaning, quality signals, and governance that are ready for analytics and AI agents

6️⃣What it takes to make data truly AI-ready without sacrificing control, compliance, or consistency

Designed for data leaders, enterprise architects, and governance teams, this session explains why existing catalogs and governance tools remain useful—but are no longer sufficient on their own—and how enterprises can operationalize shared meaning to support analytics, data engineering, and AI initiatives at scale.

Register here