BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//hacksw/handcal//NONSGML v1.0//EN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260722T230819Z
DESCRIPTION:Click for Latest Location Information: http://dgiq-aigov2026.da
 taversity.net/sessionPop.cfm?confid=166&proposalid=16781\nAsk ten people wh
 at "customer" means, and you may get ten answers. Ask your AI sys
 tem, and it will confidently give you one — inherited from whatever m
 eaning your data already carries. If that meaning is inconsistent or ungove
 rned, your AI amplifies the problem.\n\nReporting-oriented semantic models 
 weren't designed for this. AI governance requires a broader foundation:
  governed concepts, contextual definitions, lineage, provenance, data class
 ification, and clear distinctions between observed, derived, inferred, pred
 icted, and generated information. This tutorial explains how semantic 
 layers become a core governance capability — and gives you two tools 
 to take back: a Semantic Governance Readiness Assessment and a Semantic Lay
 er Governance Blueprint.\n\nParticipants will learn to:\n\n
 Distinguish reporting-oriented semantic models from semantic layers designe
 d for AI governance\n
 Ground AI responses in approved definitions, trusted sources, lineage, and 
 business context\n
 Connect concepts, policies, data assets, and permitted uses into a governed
  semantic architecture\n
 Apply semantic layers to support explainability, auditability, and responsi
 ble AI use\n
 Identify gaps in current glossaries, catalogs, and metadata practices\n
 Assess semantic governance readiness and prioritize next steps\n
DTSTART:20261116T083000
SUMMARY:Meaning Matters: Semantic Layers for AI Governance, Grounding, and 
 Contextualization
DTEND:20261116T114459
LOCATION: See Description
END:VEVENT
END:VCALENDAR