Prerequisite: None
AI has captured the world’s imagination, yet most enterprise initiatives still stall at the proof-of-concept stage. The issue is not the models; it is the data. Static snapshots and delayed pipelines leave AI systems reasoning about a world that has already changed. To achieve real-time intelligence, organizations must evolve their architectures to keep data, context, and decisions in constant motion.
In this session, we will explore how the next generation of AI, often called real-time or agentic AI, depends on continuous data synchronization, validation, and feedback. You will learn how emerging architectural patterns like the Model Context Protocol (MCP) enable AI systems to securely access and act on live operational data without compromising governance or compliance. Attendees will leave with a clear framework for transitioning from traditional batch AI to real-time, context-driven systems capable of adaptive decisions and continuous learning.
If your AI projects struggle to scale or deliver measurable impact, this session will show why the future of intelligence begins with real-time data.