AI in Finance: The Data-Centric Strategy with Snowflake's Jonathan Regenstein | S2E7

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Dec 16, 2025

In this insightful discussion, Jonathan Regenstein, the AI leader at Snowflake with expertise in data science and financial services, dives into the powerful influence of data sharing in finance. He highlights Snowflake Marketplace's role in simplifying the consumption of alternative data. The conversation shifts to the debate over the AI runtime location—should it be within Snowflake or orchestrated externally? Jonathan also emphasizes the importance of robust evaluation frameworks to ensure AI projects are driven by commercial outcomes rather than just technical wins.

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INSIGHT

Data Sharing Built The AI Foundation

Snowflake's data sharing and OLAP performance created a near-perfect foundation for AI on enterprise data.
That network effect made Snowflake uniquely positioned to unify data, analytics, and AI workflows.

ANECDOTE

Snowflake Accelerated University Research

Jonathan described helping Georgia Tech researchers get data faster via Snowflake shares so their AI work sped up.
He said researchers already had AI skills but valued Snowflake for simplifying data access and collaboration.

INSIGHT

Consumption Pricing Fits Agent-Driven Use

Consumption-based access models for data will matter because agents may query small slices frequently.
Monetization will shift from seat subscriptions to per-request models as agents proliferate across enterprises.

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Welcome back to The Hedgineer Podcast, where host Michael Watson dives into the world of AI, data, and technology within asset management, hedge funds, and financial services. In this episode, Michael sits down with Jonathan Regenstein, who leads AI within Financial Services at Snowflake.

This conversation explores the critical role of data and platform strategy in the successful enterprise deployment of AI, moving beyond purely technical wins to focus on commercial outcomes. Jonathan and Michael dissect the evolution of Snowflake from a powerful SQL engine to a unified platform for AI, and debate where the intelligence layer should reside for maximum effectiveness.

❄️ In This Episode, We Discuss:

The Power of Data Sharing: How Snowflake's seamless data sharing and Marketplace revolutionized the consumption of alternative data on the buy side, drastically simplifying security and licensing workflows.
The AI Layer Debate: A deep dive into whether the AI runtime should live natively within the data platform (Snowflake) using tools like Cortex and Intelligence, or be orchestrated externally by hyperscalers or model providers.
Beyond the Technical Win: The shift from technology-driven AI Proofs-of-Concept (POCs) to projects scoped by commercial outcomes—revenue generation or cost reduction.
Evaluations are the Product: The crucial importance of robust evaluation frameworks (like those provided by TruEra/TruLens) for agentic workflows to avoid "chaos at scale," and how to involve business leaders—not just engineers—in defining what success looks like.
The Semantic Layer's Role: The concept of the semantic model as a first-class citizen in Snowflake, acting as the translator between business language and data, driving accuracy in Text-to-SQL (Cortex Analyst), and building trust with non-technical users.
The Future of BI: How AI is driving the complete rethinking of the Business Intelligence (BI) stack, moving beyond static dashboards to dynamic, generative BI that surfaces insights and visualizations on demand.

👤 About Our Guest

Jonathan Regenstein is a key leader in the AI for Financial Services division at Snowflake, driving the platform's strategy in machine learning and artificial intelligence for banks, asset managers, and insurance companies.

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