You don't need another post-mortem to know why enterprise AI projects fail. Organizations that have moved AI from pilot to production know it runs on context. A knowledge layer shows AI how facts relate, what's changed, and what's already been decided. Trained on siloed data, a model sees disconnected records, not relationships, and can't reason well without that context. The knowledge layer connects GenAI and agentic systems to data that's organized and accessible.

In this session, we'll cover why the knowledge layer is the missing piece your enterprise AI needs, and what your organization gains from implementing one:

     - Trust every AI answer, back to your source data
     - Prove every AI decision with a complete audit trail

     - Synthesize intelligence across disparate systems and teams
     - Use your existing data investments instead of replacing them