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DESCRIPTION:Click for Latest Location Information: http://dgiq-aigov2026.da
 taversity.net/sessionPop.cfm?confid=166&proposalid=16812\nThe rise of AI Ag
 ents is revolutionizing data operations, analysis, and management. Dat
 a quality (DQ) management is no exception. DQ and AI are intertwined. 
 Good data quality is necessary to improve AI results, and AI can be used to
  improve DQ, leading to a virtuous cycle. This talk discusses how larg
 e language model (LLM) agents can make DQ operations more effective and mor
 e efficient, while minimizing the risks inherent in AI applications through
  strict governance.  \n\nTopics include:\n\n
 What is an AI agent? How is it different from prompting and pipelines?\n
 How AI agents can augment the DQ management process\n
 Examples of DQ agents\n	The component of an Agentic AI process\n
 Strategies for improving accuracy, trust, performance, scalability, and sec
 urity\n	The key role of governance in Agentic AI\n
DTSTART:20261117T100000
SUMMARY:Data Quality Management in the Age of Agentic AI
DTEND:20261117T104459
LOCATION: See Description
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