
S4 | E16 | The AI Trust Problem Nobody Is Talking About with Uri - Co-Founder - Nimble
From ThinkData Podcast by Dataworks Group Limited
May 12, 2026 · 34 min · Season 4 · Episode 16
About this episode
The episode discusses the trust gap in enterprise AI and the importance of reliable data infrastructure for AI adoption.
Most enterprise AI isn’t failing because of the models… It’s failing because no one trusts the output. In this episode of the ThinkData Podcast, we’re joined by Uri Knorovich, CEO of Nimble, to unpack the growing trust gap in enterprise AI and why bad, delayed, and fragmented data is becoming the biggest blocker to real AI adoption. We explore: • Why AI works in demos but breaks inside enterprises • The hidden risk of AI outputs without traceable data lineage • Why trusted, live data infrastructure matters more than model speed • The shift from “is the AI fast?” to “can we trust the decisions?” • Real-world examples where AI and live data are already driving value A great conversation on the future of enterprise AI, data infrastructure, and building systems companies can actually rely on.
People in this episode
Guest: Uri Knorovich
Topics covered
- AI trust
- enterprise AI
- data infrastructure
- data lineage
- AI adoption
- real-world examples
Keywords
- enterprise AI
- trust gap
- data lineage
- AI outputs
- data infrastructure
- AI adoption
- real-world examples
Mentioned in this episode
Organizations: Nimble
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