# Denodo and The AI Trust Gap: The Enterprise Data Crisis Behind AI Adoption

Page: https://stenobird.com/podcast/tech-talks-daily-3579/denodo-and-the-ai-trust-gap-the-enterprise-data-crisis-behind-ai-adoption
Text version: https://stenobird.com/podcast/tech-talks-daily-3579/denodo-and-the-ai-trust-gap-the-enterprise-data-crisis-behind-ai-adoption.md
Podcast: [Tech Talks Daily](https://stenobird.com/podcast/tech-talks-daily-3579)
Published: 2026-05-26T00:00:00+00:00
Episode link: https://techtalksnetwork.com/
Audio file: https://traffic.libsyn.com/secure/techblogwriter/Tech_Talks_Daily_Denodo_2026.mp3?dest-id=289572
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Duration seconds: 2123

## Resource

What happens when AI systems stop acting like assistants and start acting like autonomous decision-makers inside your business? And if those systems are pulling information from fragmented, inconsistent, and poorly governed data environments, how much trust can organizations really place in the outcomes? In today's episode, I'm joined by Terry Dorsey for a fascinating conversation about the growing gap between AI ambition and enterprise reality. Terry brings decades of experience spanning enterprise architecture, business intelligence, operations, healthcare, utilities, manufacturing, and defense. Long before AI became the headline topic dominating every boardroom conversation, he was already working deeply in semantic modeling, natural language systems, and the architectural foundations that modern AI now depends on. At the center of our discussion is the new AI Trust Gap report from Denodo, which reveals why so many organizations are struggling to move AI projects from experimentation into reliable production environments. We explore why live data matters so much in an agentic AI world, why "more data" often creates more confusion instead of clarity, and how inconsistent business meaning across systems quietly undermines AI trust inside large organizations. Terry explains why many enterprises are still operating on architectures originally designed for historical reporting and analytics, while now expecting those same environments to support autonomous AI systems making real-time operational decisions. From semantic sprawl and duplicated business logic to governance failures and fragmented security models, we unpack the hidden technical debt that AI is now exposing at scale. The conversation also takes a deeper philosophical turn as we discuss why enterprise meaning…

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