Governing AI: From Model Risk to Strategic Control

AI is no longer an emerging consideration for financial institutions. From established machine learning models to generative and agentic AI, organisations are adopting increasingly sophisticated technologies while governance, risk and control frameworks work to keep pace. In this webinar, industry experts explore what effective AI governance means in practice, how to define AI systems and risks, and how institutions can determine the appropriate level of oversight based on use case and risk.

The discussion examines how organisations can build on existing model risk, third-party risk, data and control frameworks rather than creating entirely new governance structures from scratch. Speakers explore the importance of lifecycle oversight, use-case classification, human involvement, third-party due diligence, data governance and ongoing reassessment as AI systems evolve. The panel also considers the growing gap between AI adoption and governance readiness, the risks of autonomous and agentic AI, and how financial institutions can balance innovation with responsible, proportionate control.