Event Overview

‍The explosion of AI workloads is putting unprecedented pressure on traditional data architectures. In this session, we’ll explore why modern data warehouses need to be rearchitected for the new AI era — and how engineering and data leaders can adapt.

You'll hear from infrastructure experts, data platform leaders, and an independent analyst on:

• Why your current data warehouse might be your biggest AI bottleneck
• How performance, cost, and agility play into real-world trade-offs
• What leading engineering teams are doing to stay ahead of the AI curve

The session includes a live benchmark walkthrough & real-world success stories so you leave with actionable insights — not just high-level theory.

Who Will Get the Most Value‍

This session is designed for anyone thinking critically about the future of data infrastructure in the age of AI — whether you’re scaling platforms, optimizing performance, or evaluating new architectural trade-offs. Especially relevant for:

• Heads of Data, Analytics, and Infrastructure who own platform decisions
• Directors and VPs of Engineering scaling AI and data workloads
• AI & ML Platform Teams looking for faster access to clean, performant data
• CIOs and Tech Execs with cloud budget responsibility
• Enterprise Architects and Solution Engineers designing for scale

Speakers

• David Menninger: Executive Director, Technology Research at ISG Software Research.
• Igor Stanko: Chief Product Officer at Firebolt
• Cole Bowden: Developer Advocate at Firebolt
• Ryan McWilliams: CTO at Vrio
• ‍Yaron Cohen-Leo: Head of BI & Data Ops at Bigabid