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2 days agoAt Disrupt 2026: Databricks' co-founder on what kills enterprise AI deals | TechCrunch
Enterprise AI adoption fails when organizations cannot absorb operational instability, not when models underperform.
Simply having data isn't enough-how you organize, govern, and activate it makes all the difference. Leading organizations implement three specific practices: connect all your data together, label and organize it so it's easy to find, and set controls to ensure only the right people (or agents) have access to sensitive data sets.
Adoption is high, hype is higher, but meaningful business impact remains elusive. AI is everywhere except on the bottom line. Why this disconnect? It's not that AI technology suddenly hit a wall. The models are more powerful than ever. The problem is how companies are using AI, not what AI can or cannot do. Organizations have treated AI like just another software deployment, expecting a plug-and-play solution.