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Most organizations are deploying AI faster than they can govern it. Models influence operations, customer outcomes, and compliance exposure while accountability and risk visibility lag behind. This is not innovation but unmanaged risk. This session examines how AI risk shows up in real production systems, why conventional risk frameworks collapse under AI complexity, and what disciplined organizations do to establish control without slowing down deployment. If your enterprise is using machine learning, generative AI, or automated decision systems, ignoring AI lifecycle risk is not a strategy. It is a liability. In this session, you will learn • How AI risk differs from traditional risk • Where AI risk appears • How to measure AI risk • Controls that reduce AI risk • Who is accountable for AI systems Who this is for Enterprise executives, AI governance leaders, risk and compliance teams, cybersecurity professionals, and engineers responsible for deploying or overseeing AI in regulated or high-impact environments. #AIRisk #AIGovernance #ResponsibleAI #EnterpriseAI #AIControls #AICompliance #RiskManagement