Implement ITIL AI Governance Controls

An AI use case clearing architecture review isn't the same as it being governed. This course teaches compliance managers, AI governance leads, and model risk managers in financial services to run the full AI governance control cycle — not sign off on a checklist someone else already filled in. You'll conduct an AI use-case risk assessment, assigning impact and likelihood scores across the model, data, security, operational, governance, and agentic-AI risk categories, and facilitate a workshop with architects and legal counsel to rank the controls a proposed chatbot needs before approval. You'll draft a minimum viable AI governance policy for an AIOps anomaly-detection system — specific enough to be audited, short enough that a compliance steering committee will actually read it. And you'll evaluate an automated patching runbook against ITIL 5 ethical guardrails, documenting the compliance gaps a clean track record hides and recommending approval steps an operations director will actually adopt. Through a realistic risk-scoring workshop, a policy-drafting exercise, and a capstone presentation to a skeptical operations director, you'll build skills you can apply to your own organization's AI governance program immediately. Designed for financial regulation and compliance roles (CB3). Beginner (Foundation) level; no prior ITIL certification required. By the end of this course, learners will be able to: - Conduct an AI use-case risk assessment by assigning impact and likelihood scores and prioritizing control implementation in line with ITIL 5 AI Governance guidelines - Draft a minimum viable AI governance policy that specifies approval gates, model traceability requirements, and incident response protocols for a given automation workflow - Evaluate existing automated service workflows against ITIL 5 ethical guardrails to identify compliance gaps and recommend remedial controls No prior ITIL certification required. This course assumes working familiarity with AI/ML systems terminology (models, training, inference) and exposure to your organization's risk or compliance review process, and is written for CB3 Managerial Professionals in Financial Regulation and Compliance — compliance managers, AI governance leads, and model risk managers who own an AI use case's risk posture end to end and are accountable for outcomes across legal, architecture, and operations, not just a single review step. Access to the provided AI use-case risk matrix, minimum viable governance policy template, and workflow compliance gap analysis worksheet is needed for the applied activities.