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DESCRIPTION:Click for Latest Location Information: http://dgiq-edw2026.data
 versity.net/sessionPop.cfm?confid=165&proposalid=16440\nAs organizations ac
 celerate their adoption of Artificial Intelligence, the need for practical 
 and structured AI Governance becomes increasingly critical. This session pr
 ovides a real-world look at what AI governance truly entails—beyond c
 onceptual frameworks—based on a recent initiative led by the DAMA Uru
 guay community. Through surveys and interviews with professionals across mu
 ltiple sectors, we explored how organizations are approaching AI projects, 
 which governance practices they are trying to establish, and where the most
  significant gaps and risks are emerging.\nWe will share the key challenges
  identified and will also highlight the concrete steps organizations are be
 ginning to take to build their AI governance capabilities. Although these f
 indings originate in Uruguay, they mirror a global reality: AI governance i
 s still in its early stages everywhere, while pressure to deploy AI systems
  continues to grow. Attendees will gain practical insights, lessons learned
 , and emerging practices to guide their own governance efforts.\nKey takeaw
 ays:\n\n
 What AI governance looks like in real organizational contexts, based on com
 munity-driven research.\n
 Key challenges identified: data quality gaps, unclear ownership, and emergi
 ng risks.\n
 Concrete steps organizations are beginning to take as AI adoption accelerat
 es.\n
 Lessons learned from surveys and interviews conducted by the DAMA community
 .\n
 Emerging practices and actionable recommendations to strengthen AI governan
 ce.\n\n 
DTSTART:20260505T154500
SUMMARY:AI Governance: Findings and Lessons from across Industry (Presented
  in Spanish)
DTEND:20260505T162959
LOCATION: See Description
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