As AI becomes deeply embedded the need for ethical oversight has never been more urgent. While 77% of organizations are actively developing AI governance strategies (rising to 90% among those with operational AI), the industry still grapples with a fundamental question: how do we govern AI responsibly in environments here the stakes are high, and the consequences of failure even higher? This session will explore:

• How organizations can move from capability to responsibility when automating tasks with AI, balancing efficiency with ethical considerations, especially in contexts where human judgment remains essential
• How to implement governance frameworks that provide guardrails, not guesswork, evaluating AI outputs for accuracy, mitigating hallucinations, and reducing bias to build trust in systems making increasingly high-impact decisions
• How to identify and address bias and behavior in AI models by uncovering hidden biases, understanding model behavior patterns, and training teams to critically assess AI-generated outputs