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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 concept
 ual frameworks—based on a recent initiative led by the DAMA Uruguay communi
 ty. Through surveys and interviews with professionals across multiple secto
 rs, we explored how organizations are approaching AI projects, which govern
 ance 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 beginning to t
 ake to build their AI governance capabilities. Although these findings orig
 inate in Uruguay, they mirror a global reality: AI governance is still in i
 ts early stages everywhere, while pressure to deploy AI systems continues t
 o grow. Attendees will gain practical insights, lessons learned, and emergi
 ng practices to guide their own governance efforts.\nKey takeaways:\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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