Bruno Aziza

AI and automation increasingly need to understand the business as it changes—not hours later after the next batch refresh. Learn how a real-time data architecture can continuously capture, process and govern changing enterprise data, combine it with historical and business context, and serve an always-current view directly to applications, operations and AI agents. By connecting live signals across hybrid environments without first centralizing the entire data estate, organizations can make faster, more confident decisions while improving resilience, strengthening security and optimizing price-performance.

In the 11th year of Big Data LDN, in its flagship keynote debate, conference chair and leading industry analyst Mike Ferguson welcomes executives from leading software vendors to discuss key topics in data management and analytics. Panellists will debate the challenges and success factors in building an agentic enterprise, implementing and sharing AI context, creating AI ready data, the rising importance of unified data and AI governance, data architecture changes needed for AI, how best to deal with real-world customer challenges, and issues on-the-horizon that companies should be planning for today. Attendees will learn best practices for data and AI implementation in a modern data and AI -driven enterprise from seasoned executives and an experienced industry analyst in a packed, unscripted, candid discussion.

Most organizations adopt AI, but few truly transform. The difference isn’t models or use cases—it’s how they operate. Leaders are shifting from isolated initiatives to an AI Operating Model uniting real-time intelligence, coordinated action, enterprise operations, and trust. In this session, IBM shares how enterprises become agentic, while Agassi Sports Entertainment shows how IBM solutions turn data into insights and deliver standout customer experiences.