Collibra

Join AIUC + Collibra to learn how to supervise agents at scale and act fast when they cross the line.

Learn how to scale agentic AI without losing the wheel. Live Nov. 4 with AIUC + Collibra. Save your seat.

Get ahead of AIUC-1, an emerging standard for AI agent safety and security. Live webinar on Nov. 4.

Enterprise AI is moving fast. Trust isn’t keeping up. On October 6, we’re bringing together AI, data and technology leaders in New York City for the Collibra AI Summit to talk about what it actually takes to close that gap. How do you give AI the business context it needs to make better decisions? How do you maintain control as agents become more autonomous? And how do you move from promising pilots to AI you can confidently put into production? We’ll hear directly from leaders working through these questions today and share what we’re learning along the way. If you’re responsible for making AI work in the enterprise, I hope you’ll join us. October 6 | New York City Register: https://lnkd.in/e5WsANn5 #EnterpriseAI #AIGovernance #Collibra

72% of tech decision-makers say their AI initiatives are falling short and the problem isn’t the models. It’s the foundation underneath them. We surveyed more than 300 data, privacy, and AI decision-makers with The Harris Poll for our 2026 Hallucination Tax Report. 76% have hit roadblocks moving AI from pilot to production. 87% say their teams are spending significant time re-verifying the context their agents are working from. That’s the hallucination tax: the hidden cost of manual oversight, rework, and risk that grows with every new agent put into production. It doesn’t show up as a line item. It shows up in teams checking and rechecking AI output. In pilots that struggle to reach production. And ultimately, in a ceiling on how far enterprises can scale AI. A smarter model won’t solve that. Enterprises need governed context and controls built into how agents work, so they can trust AI to act without having a human double-check every step. Read more in our new research with The Harris Poll: https://lnkd.in/et9U234M

Cisco, Intuit, Workday, and ServiceNow are all building versions of the same thing: a control layer for AI agents. And they're building it in from the start. But for most enterprises, the bigger risk isn't an agent going rogue. It's an agent doing exactly what was asked, confidently, on data and context nobody governed. The agent isn't going rogue. It's guessing, and it has no way to know it's guessing. Our latest research with The Harris Poll found that more than half of data and AI decision-makers spend significant staff hours manually reviewing and correcting agent output before it goes live. That's the hallucination tax. And it grows with every agent you put in production. Monitoring isn't enough. Enterprises need visibility into what agents are doing, governed context for the decisions they're making, and controls that can be enforced at runtime. https://lnkd.in/egddh4KA