BRKS206 - Monitoring AI Performance and Accountability in the Public Sector

Course Description

Deploying AI systems is only the beginning. Sustaining responsible AI in government requires robust oversight, proactive monitoring, and systems that learn and adapt over time. The critical challenge goes beyond making AI work to ensuring it continues working ethically, effectively, and accountably throughout its operational life cycle while maintaining public trust and policy compliance evaluation.

In this course, you will develop practical skills for governing AI after it goes live. You'll identify warning signals of system drift, performance degradation, and unintended consequences, building monitoring capabilities that catch problems before they impact citizens. Through realistic failure scenarios and public challenge simulations, you'll practice making critical decisions about when to pause, retrain, or retire AI systems under pressure.

You'll also examine the organizational systems that sustain accountability, developing escalation protocols, assigning oversight responsibilities, and applying institutional learning loops that turn experience into improved governance. Beyond internal processes, you'll build skills for explaining AI decisions to non-technical stakeholders and responding to external scrutiny. Finally, you'll integrate risk assessment, accountability systems, and leadership structures into comprehensive governance approaches that evolve with your AI applications.

By the end of this course, you will be prepared to lead continuous AI accountability efforts that maintain system performance, public trust, and regulatory considerations while enabling your organization to learn and improve its AI governance capabilities over time.

You are required to have completed the following courses or have equivalent experience before taking this course:

• Building AI Foundations for Public Leaders
• Powering AI With Data
• Leading Ethical AI in the Public Sector
• Navigating AI Policy, Regulation, and Public Accountability
• Leading AI Implementation and Measuring Value in the Public Sector

Faculty Author

Benefits to the Learner

• Monitor post-deployment AI systems for drift, harm, and misuse using oversight frameworks
• Build operational accountability systems with clear ownership, performance baselines, feedback loops, and iteration planning
• Apply institutional learning processes that transform operational insights into both system improvements and stronger governance practices
• Lead stakeholder communication and public engagement that turns external oversight into system strengthening rather than threats
• Develop governance frameworks that sustain AI accountability through continuous monitoring, learning, and leadership commitment

Target Audience

• Government executives and agency leaders responsible for AI strategy, digital transformation, technology, innovation, or organizational leadership
• Program and operational leaders managing AI initiatives, modernization efforts, or public service delivery
• Data, privacy, cybersecurity, risk, and compliance professionals responsible for data governance, ethical AI, security, ethics, or regulatory compliance
• Public policy professionals, legislators, and legislative staff shaping AI policy, regulation, oversight, or public accountability
• Procurement, acquisition, and contracting professionals responsible for evaluating, purchasing, or managing AI technologies and vendor relationships
• Consultants, GovTech providers, nonprofits, and other organizations serving the public sector that advise, implement, or support responsible AI adoption

Applies Towards the Following Certificates

• AI Leadership for the Public Sector : Core Courses