Can AI Agents Be Trusted With Enterprise Data? | Big Data LDN Special

Two different teams in an enterprise built two AI agents, but both asked the AI the same question: What are last quarter’s customer stats? Both agents answer promptly and quite assertively. However, the figures on the same inquiry are different. The agents’ answers don’t match. Nothing has broken because neither team is aware of the other’s AI agent. What happened here is that each agent drew the answer from different contextual data. The business holds two variations of truth delivered with equal confidence. This is the kind of oblivious failure Angelita Frozza Sanches, Head of Data at Scout24, is working to prevent at the leading German real estate platform where AI agents have already been deployed in production. In this episode of the Don't Panic It's Just Data podcast, recorded live at Big Data London 2026 in Kensington Olympia, host Mike Ferguson, Managing Director of Intelligent Business Strategies and Conference Chair of Big Data London, sits down with Sanches and Suresh Srinivas, CEO and Co-Founder of Collate and OpenMetadata. They talk about who now consumes enterprise data, how much of the context layer should be centralised, and why enterprises making progress are the ones that start small and tie every agent to a business outcome. According to Sanchez, the concerns from 20 years ago to now remain the same, and it comes back to governance. “How people consume, how they interact with data,” remains the same. What’s new is that “AI has changed the velocity and the impact of all those aspects.” “Now we can take advantage of AI to help us build governance,” Sanchez says. “How can we prepare everything not just for humans but agents–another persona in the game.” Also Watch: How to Increase Agent Accuracy & Reduce Cost with Context #AIAgents #DataGovernance #ContextLayer #AgenticAI #OpenMetadata #BigDataLondon #EM360Tech #AIAgents #DataGovernance #ContextLayer #AgenticAI #OpenMetadata #BigDataLondon #EM360Tech