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DTSTAMP:20260722T235849Z
DESCRIPTION:Click for Latest Location Information: http://dgiq-aigov2026.da
 taversity.net/sessionPop.cfm?confid=166&proposalid=16706\nAI governance pri
 nciples are now widely available, but many organizations still struggle to 
 convert them into measurable operating practices. This session will show ho
 w data and AI leaders can move from high-level responsible AI statements to
  practical controls, evidence requirements, lifecycle checkpoints, and cert
 ification-ready governance.\n\nThe session will use the Saudi Authorit
 y for Data & Artificial Intelligence's (SDAIA) AI trust measur
 ement approach as a case study, including its 13 AI trust measurement templ
 ates available through the Data Governance Platform.\n\nAttendees will leav
 e with a reusable operating model they can adapt in their own organizations
 : how to map AI principles to risks, define measurable controls, assign own
 ers, collect evidence, establish approval gates, and monitor trust after de
 ployment.
DTSTART:20261117T164500
SUMMARY:Building Measurable AI Trust: From Principles to Controls, Evidence
 , and Certification
DTEND:20261117T172959
LOCATION: See Description
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