Richard Hall

AI is only as effective as it’s ability to understand your business. But as organizations look to make their data “AI-ready”, the distinctions between semantic models, ontologies, and context engineering can quickly become confusing. This talk cuts through the terminology and shows how these three approaches fit together. Using real-world examples, we'll examine how semantic models define business meaning, how ontologies capture rich relationships and how context engineering delivers the right information and instructions to AI at the moment they are needed. Most importantly, we'll explore when each approach is useful and when it isn't. Attendees will leave with a simple framework for thinking about the layers of context required to move AI from understanding data to understanding—and acting within—the business.