Subvolts take Enterprise AI is moving beyond pilots to production, powered by agents that understand company data. Mar 19, 2026 - Developers
- Learn how to build and deploy AI systems that integrate directly with enterprise data environments.
- Business
- Understand how AI agents can transform decision-making and drive automation, moving from pilots to production.
This interview provides a grounded perspective on enterprise AI implementation from a key industry player.
#327 Baris Gultekin: The Next Phase of AI - Agents That Understand Your Company's Data
Audio streams from Craig S. Smith. Your place is remembered on this device.
From Subvolts
Summary and analysis by Subvolts editorial, AI-assisted.
Eye on AI episode #327 features Baris Gultekin, Head of AI at Snowflake, discussing the practical build, deployment, and scaling of enterprise AI. The conversation covers running AI within data environments, enabling natural language access, and the shift from AI experimentation to real-world impact. Gultekin explains Snowflake's approach of bringing AI to data, the role of data agents in decision-making, and building trustworthy AI with governance and quality retrieval.
This episode explains how companies are building AI systems that work directly with their own data, not just general information. It's like giving AI a deep understanding of a specific business to help make better decisions and automate tasks.
This episode offers a practical look at enterprise AI development, moving beyond theoretical discussions. It's for business leaders and IT professionals seeking to understand how AI is actually implemented and scaled within organizations. The focus on bringing AI to data and using data agents aligns with current trends across frontier labs like Google Gemini and Microsoft Copilot, which are exploring how to make AI more context-aware and useful for specific business needs.
- HostCraig S. Smith
- GuestBaris GultekinHead of AI, Snowflake
- Guest: Baris Gultekin, Head of AI at Snowflake
- Show: Eye on AI
- Episode Number: #327
- Length: 42 minutes
- Sponsor: Modulate
- Automation Savings: Thousands of hours saved by leading companies
This episode is sponsored by Modulate. Most voice AI focuses on transcription. Velma takes it further by actually understanding conversations, analyzing tone, timing, stress, and intent using its Ensemble Listening Model architecture. Explore the live preview: https://preview.modulate.ai/
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
- data agents
- Baris Gultekin
- AI programs that can understand and act on a company's specific data to help with tasks.
- governance
- Baris Gultekin
- Rules and controls to ensure AI systems are used safely and responsibly.
- guardrails
- Baris Gultekin
- Safety measures that keep AI within defined boundaries and prevent unwanted behavior.
- retrieval
- Baris Gultekin
- The process of finding and accessing relevant information, often from a large dataset.
55 min42 min51 min34 minUkraine's Secret Weapon: The Points System Winning the Drone War | Andrii Hrytseniuk
WithAndrii Hrytseniuk
Same guests, other shows
1 h 39Questions people ask
- What is Snowflake's core philosophy for AI?
- Snowflake's core philosophy centers around bringing AI to the data, enabling natural language access across entire organizations.
- What is the benefit of AI-driven automation for companies?
- Leading companies are already saving thousands of hours through AI-driven automation.
Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to Craig S. Smith.