Karthik Gopalakrishnan

How does Snowflake manage its own cloud spend across a rapidly growing platform? In this session, we share how we built an internal, AI-powered FinOps system on Snowflake to unify cost visibility, detect anomalies and drive real-time decisions. See how Snowflake CoWork, semantic models and AI agents enable conversational cost analysis and proactive optimization. We’ll break down the architecture and design patterns behind our internal solution — and how you can replicate them to modernize cloud cost management.

AI is moving from experimentation to enterprisewide adoption, with CIO and CDO teams at the center of driving it forward. In this executive panel, Snowflake leaders share how we’ve evolved our own Data & Analytics and Enterprise Engineering teams to keep pace with the speed of AI — shifting from dashboards and reports to enabling agentic AI across the business. Hear how we’re aligning teams, redefining deliverables, and balancing speed, governance and trust. Walk away with a clear framework for how your data team should evolve and what to prioritize in the next 90 days. This session is being conducted under Chatham House Rules. To foster an open and candid discussion, participants are expected to treat all information shared during the session as confidential. Information, comments, viewpoints, and materials discussed may not be referenced, disclosed, attributed, distributed, or shared outside of this session without the express permission of the organizers and participants.

Whether you’re evaluating migration paths for your Db2 databases or are interested in efficiently operating your already migrated Db2 databases on Amazon RDS, we’ve got you covered.