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Baris Gultekin, Head of AI at Snowflake, breaks down how enterprise AI is actually being built, deployed, and scaled today. From running AI directly inside governed data environments to enabling natural language access across entire organizations, this conversation explores the shift from experimentation to real-world impact.
You'll learn why Snowflake's core philosophy centers around bringing AI to the data, how data agents are transforming decision-making across teams, and what it takes to build trustworthy AI systems with governance, guardrails, and high-quality retrieval at the core.
Baris also shares how leading companies are already saving thousands of hours through AI-driven automation, why culture and leadership determine AI success, and what the future looks like as agents move from pilots to full-scale production.
If you want to understand where enterprise AI is actually headed and what separates hype from real execution, this episode breaks it down.
(00:00) The Evolution of Snowflake AI
(01:40) Baris Gultekin: Background & AI Mission
(02:59) Why AI Must Run Next to Data
(04:29) Inside Snowflake's AI Infrastructure
(09:08) Model Choice vs Product Layer Strategy
(12:16) Building Trust: Governance, Guardrails & Quality
(16:01) How Enterprise Agents Are Built & Orchestrated
(20:10) AI Adoption Across the Entire Organization
(24:39) Reasoning vs Retrieval: What Matters More
(27:43) Real Use Case: Faster Decision-Making with AI
(31:44) AI as a Co-Pilot for Leaders
(36:52) Preparing Data for AI at Scale
(38:46) What the AI Data Cloud Really Means
