AI Governance sounds perfect on paper but why does it so often fail in the real world? In this episode of InfosecTrain Tech Talks, host Anas Hamid sits down with AI Governance & GRC Expert Nancy Paul to uncover the "implementation gap" that many organizations overlook. As AI adoption accelerates, the struggle isn't just creating policies; it’s translating those policies into practical, enforceable controls that actually mitigate risk.

The "course titled" AI Governance and Risk Management is becoming a cornerstone for modern enterprises, yet many organizations still fall into the trap of treating governance as a one-time checklist. We explore the high-level challenges of managing algorithmic bias, technical compliance, and the critical role GRC plays in ensuring that AI systems remain transparent and accountable.

📘 What You’ll Learn:

The Reality Gap: Why theoretically sound AI policies often crumble during technical execution.
Common Pitfalls: Identifying the mistakes enterprises make when scaling AI without a mature governance framework.
The Role of GRC: How Governance, Risk, and Compliance professionals act as the bridge between "safe AI" and "useful AI."
Bias & Compliance: Managing the complex technical challenges of algorithmic fairness and regulatory alignment in real-time.
Practical Strategies: A roadmap for building a governance model that is both resilient and adaptable to the evolving AI landscape.

🎧 Essential listening for GRC leaders, CISOs, and anyone responsible for the safe deployment of AI across the enterprise.

Watch the full episode on YouTube: https://www.youtube.com/watch?v=x4CqLNob9QE

Decoding AI Governance Failures: Moving from Policy to Practice