As artificial intelligence adoption accelerates across every industry, internal audit functions are being asked to provide credible assurance and advisory support over a still-evolving technology. This session brings together internal audit leaders — key contributors to the Internal Audit Collective's AI Governance Playbook — for a candid conversation about how their organizations are actually approaching AI governance today. Panelists will discuss how they identify and evaluate AI-related risk, what a well-designed AI policy should include, and how to scope an AI governance review even when an organization's AI maturity is still developing. They'll also cover practical starting points for teams without leadership buy-in for a full AI audit, plus tangential projects that build momentum over time. This is an honest, peer-to-peer look at where audit leaders actually stand — not a prescriptive how-to. Learning Objectives: Upon completion of this session, participants will be able to: Identify key categories of AI-related risk internal audit should consider, including undisclosed or "shadow" AI use Evaluate the essential components of an effective AI governance policy and spot gaps in existing ones Describe practical approaches for scoping an AI governance audit or advisory engagement in organizations with limited AI maturity Recognize alternative starting points for audit involvement when leadership isn't ready for a full governance review Identify complementary projects (e.g., data governance reviews, AI-related general controls) that support ongoing AI assurance Apply the AI Governance Playbook's framework to benchmark their own function's approach to AI governance.