An AI pilot can look successful while leaving basic questions unanswered. Who owns the outcome? Which risks have been reviewed? What evidence will show that the system works fairly and safely? Who can pause it when something goes wrong? This three-module course gives institutional leaders a practical way to answer those questions.
The first module turns responsible AI principles into decisions about real workflows. You will map uses to relevant risk frameworks and governance standards, and connect responsible AI review to model risk, legal, privacy, security, or clinical review processes already used by the institution.
The second module focuses on assessment and control design. You will conduct a Responsible AI Impact Assessment, describe plausible harms, rank risks, and plan safeguards across system instructions, content safety, data protection, human review, and monitoring.
The third module covers what happens before and after launch. You will create evaluation sets, combine automated tests and red-teaming with expert review, interpret scorecard results, and design telemetry that leads to action. You will also work through a role-based incident exercise and prepare a runbook for containment, rollback, communication, and follow-up.
Across the course, you will build an AI Corporate Strategy Roadmap, a Guardrail Deployment Matrix, and a Crisis Simulation Runbook. Together, these form a governance portfolio that can be adapted for an institutional review.
