Knowledge representation… the next steps for information management and the grounding for AI

As AI adoption accelerates, organisations are racing to make their data ‘AI-ready’ – often without addressing the information foundations that really matter – creating risk through bias to inaccuracy. The only real way to tackle those risks is through better information… which means finally getting serious about knowledge representation. This is the piece we’ve ignored for far too long, and we can’t keep pushing it aside.

The aim of the presentation is to put knowledge at the centre of the conversation. It’s one of the most critical topics for the future of information management, yet barely anyone talks about it because it’s scary. Concepts like ontologies, taxonomies, semantics and knowledge graphs might sound daunting, but they’re exactly what we need if we want both information management and AI to mature responsibly, providing more accurate and transparent results.

Reflecting on lessons learned from BIM, the session argues that we cannot afford to repeat the same mistakes with AI. Attendees will leave with a clearer understanding of how information management must evolve, why knowledge representation should sit at the heart of AI strategy, and how this approach helps retain trust and control in an increasingly AI-driven world.