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As enterprises move AI agents into production, getting the right data to the right systems becomes increasingly important. Traditional data architectures face new demands for speed, governance and context as organizations rethink how information moves across their operations. How can businesses modernize data delivery while ensuring AI agents have access to timely, accurate and trusted information? Shaun Clowes, general manager of Confluent and Data at IBM, joins theCUBE Research analysts John Furrier and Dave Vellante for IBM's AI Operating Model 2026 interview series to discuss how streamhouse architecture, federated data systems and specialized AI agents are changing enterprise data management. The conversation covers the challenges of data gravity, low-latency information delivery and providing AI agents with the context needed to perform specific tasks. Clowes explains why governance should move closer to data sources, how streamhouse architectures can support more efficient information delivery and where agent factories fit into enterprise AI strategies. The discussion also addresses IBM's role in integrating enterprise technologies and why specialized agent workloads, governed data access and reliable context are critical to scaling AI in production. Find more SiliconANGLE news and analysis https://siliconangle.com/ Follow theCUBE's wall-to-wall event coverage https://siliconangle.com/events/ Learn about the latest theCUBE events https://www.thecube.net/ 00:00 - Enterprise Data Architecture for Always-On AI 02:14 - Delivering Fast, Accurate Enterprise Context to LLMs 06:18 - Governed Knowledge for Intelligent Agents and Workloads 09:43 - Flexible AI Automation Versus Rigid RPA 12:59 - Trusted Enterprise AI Agent Deployment With IBM 15:11 - Efficient Context Through Federated Business Data 17:27 - Avoiding Automation Islands With Production Guardrails #IBMAIOperatingModel #theCUBE #IBMAnalystDay #OneMadison #Streamhouse #LLM #DataGravity #DataGovernance #Agents #EnterpriseAI #SiliconANGLE

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