Baris Gultekin, VP of AI at Snowflake, explains how “bringing AI to the data” is reshaping enterprise AI deployment under strict security and governance requirements. PSA for AI builders: Interested in alignment, governance, or AI safety? Learn more about the MATS Summer 2026 Fellowship and submit your name to be notified when applications open: https://matsprogram.org/s26-tcr. He shares the importance of bringing AI directly to governed enterprise data, advances in text-to-SQL and semantic modeling, and why high-quality retrieval is foundational for trustworthy AI agents. Baris also dives into Snowflake’s approach to agentic AI, including Snowflake Intelligence, model choice and cost tradeoffs, and why governance, security, and open standards are essential as AI becomes accessible to every business user.

LINKS:

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Sponsors:

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MATS:

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CHAPTERS:

(00:00) About the Episode

(03:02) Snowflake 101 and AI

(09:25) Text-to-SQL and semantics

(19:10) RAG, embeddings and models (Part 1)

(19:17) Sponsors: MongoDB | Serval

(21:02) RAG, embeddings and models (Part 2)

(32:23) Bringing models to data (Part 1)

(32:29) Sponsors: MATS | Tasklet

(35:29) Bringing models to data (Part 2)

(51:14) Designing enterprise AI agents

(58:35) Trust, governance and guardrails

(01:07:14) Agents and future work

(01:15:33) Platforms, competition and value

(01:26:04) Enterprise models and outlook

(01:40:00) Outro

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