In this episode, Karen is joined by Barr Moses, CEO and Co-founder of Monte Carlo, to explore how AI agents are transforming how data teams work — and why trust must sit at the heart of every data and AI initiative.

Barr shares how troubleshooting agents save days of work mimic human reasoning to identify and fix data incidents, how teams can “operationalize trust” in their data and/or AI systems, and what it really takes to bridge the gap between hype and reliable business value.

Together, they unpack the pressure data teams face to deliver AI quickly, the realities of observability, and why technology alone isn’t enough .

Whether you’re building AI systems, leading a data function, or simply trying to make sense of the fast-changing landscape, this episode will help you understand what it takes to build data and AI you can trust.