
The Real Reason Enterprise AI Adoption Is Moving Slower Than Everyone Expected
Eye on AI3 July 2026Watch on YouTube
Part of series
Ep. 13 · Devvret Model Rishi
View the seriesDescription
Enterprise AI adoption is moving much slower than almost anyone predicted. And the reason isn't the technology. It's trust. AI systems from the expert system era - the ones enterprises relied on for decades - were deterministic. You put in an input, you got a predictable output, every single time. That's what large organizations are built around: knowing what the answer is going to be before you commit to it. Generative AI doesn't work that way. It's probabilistic. It produces answers that are often excellent - but not guaranteed, not predictable, not always the same twice. And for an enterprise that's managing customer relationships, financial decisions, or sensitive workflows, "often excellent" isn't the same as "trustworthy enough to deploy." That's the trust gap. Does the shift from deterministic to probabilistic AI concern you, or do you think enterprises are being too cautious? Full conversation with Alberto Pan, Chief Technical Officer at Denodo, on Eye on A.I.
What you'll learn
- Enterprise AI adoption is slower mainly due to trust concerns, not technological limitations
- Traditional deterministic AI systems provide predictable outputs, while generative AI is probabilistic with no guaranteed results
- For large organizations managing customer relationships and financial decisions, 'often excellent' isn't reliable enough for deployment