This course is built for chief risk officers, heads of compliance, model risk leaders, AI governance partners, and second-line professionals in banking, insurance, asset management, and other regulated environments. It assumes you have a working understanding of risk management and regulatory compliance, and that you have begun to encounter AI use cases that don't fit neatly into your existing model risk framework.
We start from a contrarian premise: governance done well is an accelerator of AI deployment, not a brake on it. Most organisations experience AI governance as the function that says no, slows things down, and demands documentation that nobody reads. Done properly, governance is the function that unblocks AI work — by removing the institutional friction that normally kills enterprise AI initiatives, by giving the business a defensible posture in front of regulators, and by turning compliance into a competitive advantage rather than a tax.
Across seven modules you will learn how AI fits into existing model risk frameworks (and where it breaks them), how to design three-lines-of-defence for AI deployments, how to map AI use cases to the EU AI Act risk tiers and PRA SS1/23 model lifecycle expectations, how to build governance that operates inside the workflow rather than alongside it, and how to handle the operational realities of model monitoring, drift, override tracking, and incident response. Every framework is mapped to specific regulatory expectations across the EU, UK, and US.
This course pairs with our AI Enablement service and the supporting pillar essay on AI enablement. Complete all seven modules and pass the final assessment to earn your AI Governance Practitioner certification from Insight Centric.