AI Data Privacy & Governance: Risks, Roles & What’s Next | (IAPP)
As generative AI tools become embedded in daily business workflows, privacy and data protection teams face unprecedented challenges. Employees routinely plug confidential corporate information into external AI systems, creating severe exposure risks like shadow AI, re-identification, and unintended data training loops.
In this session of InfosecTrain Tech Talks, Jay sits down with Ashley Casovan, Managing Director of the IAPP AI Governance Center. Ashley unpacks why traditional data protection frameworks must adapt to the massive scale of modern machine learning. They discuss actionable guardrails organizations can deploy today, how to balance rapid innovation with strict risk management, and why privacy experts are uniquely positioned to lead broader digital governance initiatives. If you are looking to advance your expertise in AI Data Privacy, bridge the gap between technical engineering teams and executive leadership, or earn credentials in AI governance, this discussion gives you a practical, real-world roadmap.
What You Will Learn
00:00 - Introduction: The Intersection of Privacy and Artificial Intelligence
03:15 - Unpacking Generative AI Privacy Concerns & Unsanctioned Shadow AI
10:05 - Building Practical Guardrails Against Accidental Data Leaks
16:40 - Fostering AI Innovation While Maintaining Data Protection Standards
23:10 - The Evolution of Privacy Roles Into Comprehensive AI Data Privacy Management
34:45 - Skill Upskilling Paths and Earning Your AI Governance Certification
43:15 - Rapid-Fire Q&A: Shadow AI, Human Oversight, and AI Regulation Speed
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