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DESCRIPTION:Click for Latest Location Information: http://dgiq-edw2026.data
 versity.net/sessionPop.cfm?confid=165&proposalid=16359\nAutonomous and semi
 -autonomous AI agents are transforming how businesses operate—taking 
 on tasks, making decisions, and interacting with systems and users with min
 imal human input. These agentic systems promise major gains in innovation, 
 productivity, and ROI. At the same time, they introduce new layers of compl
 exity in transparency, accountability, ethics, and compliance. As organizat
 ions adopt these technologies, the ability to govern them effectively is cr
 itical to managing risk and building trust.\n\nThe tutorial presents a
  13-part Agentic AI Governance Framework, grounded in real-world case studi
 es and practical application. Participants will learn to identify the core 
 characteristics of AI agents and navigate issues such as bias mitigation, h
 uman-in-the-loop design, security vulnerabilities, intellectual property co
 ncerns, data privacy, and compliance with global regulations like the EU AI
  Act and U.S. sector-specific laws.\n\nBy the end of the Agentic AI Go
 vernance tutorial, participants will be able to:\n\n
 Identify the characteristics and functional capabilities of AI agents acros
 s different industries.\n
 Recognize governance challenges and implications related to the deployment 
 of agentic AI systems.\n
 Gain a working knowledge of global AI regulations, including the EU AI Act 
 and U.S. sector-specific laws.\n	Understand the importance of Data Risk.\n
 Apply risk management strategies tailored to the lifecycle of AI agents.\n
 Assess AI systems for bias, fairness, reliability, security, and transparen
 cy.\n
 Understand the ethical and legal considerations related to AI agents, inclu
 ding issues like voice cloning and autonomous decision-making.\n
 Navigate the Agentic AI Governance Framework and its 13 components.\n
 Clarify organizational roles and responsibilities for AI governance, includ
 ing the function of a Chief AI Officer.\n
 Evaluate and implement human oversight mechanisms and explainability requir
 ements.\n
 Leverage AI governance strategies to drive business value and return on inv
 estment.\n
 Analyze real-world governance failures and successes through detailed case 
 studies.\n
 Anticipate emerging trends in agentic AI systems and prepare adaptive gover
 nance strategies.\n\n
DTSTART:20260504T083000
SUMMARY:T8: Aligning Agentic AI Governance and Data Risk
DTEND:20260504T114459
LOCATION: See Description
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