How Sanofi Scales AI Across 80 Countries with Dataiku and Snowflake

How do you scale AI across 80 countries in a highly regulated industry? Join Snehal Patel (Head of Data and AI Engineering (Commercial US), Sanofi) and Conor Jensen (Field CDO, Dataiku) for a candid look at turning AI ambition into global enterprise execution.

No slides, just a casual conversation — podcast style — of how Sanofi uses Snowflake as its global data foundation and Dataiku to connect business and IT, operationalize governance and accelerate the shift from pilots to production. Learn practical lessons on data quality, platform strategy and operating model decisions for scaling AI in a complex, regulated organization. 

• Democratizing Enterprise AI: Sanofi implemented a global data mesh strategy to federate and democratize data and AI for a wide range of non-engineering personas, rather than just relying on traditional data engineers.
• Business & IT Collaboration: To successfully scale capabilities globally, the company established Centers of Excellence for core technologies, including Dataiku and Snowflake.
• Streamlined Platform Strategy: Because Dataiku runs in place on Snowflake, Sanofi operates more efficiently and does not need to dedicate team members solely to managing the integration between the tools.
• Governed AI Execution: Operating in a highly regulated industry requires strict oversight. Building on a governed foundation, Sanofi is now safely deploying high-value AI agents, including a central agent hub that prevents different teams from developing the same agent twice.

This conversation is a recorded session from Snowflake Summit 2026.