In this module, you will turn oversight and accountability from documents into daily practice. Most oversight schemes do not fail at design time; they fail at adoption, when review queues go unread and the accountability matrix is never opened. You will map oversight and accountability touchpoints onto a realistic team operating rhythm, design decision-log practices that capture what oversight produced without becoming bureaucratic, build escalation rituals that surface failures early, and adjust the rhythm as the team matures. The labs have you design a complete operating rhythm for an agentic team

In this module, you will bring the trust and ethics dimensions of agentic teams together into one substantial body of practice. You will treat trust, transparency, and explainability as practical disciplines rather than slogans, choose transparency defaults and plan how the team responds to explainability requests, and survey the wider considerations a leader cannot ignore: bias and fairness, legal and regulatory exposure, labor and workforce implications, and the organizational signals that a deployment is straying off course. The module closes by surfacing concerns constructively rather than letting them fester. The culminating lab produces a combined trust-and-considerations package.

In this module, you will bring the IBM AI Ethics and Trust Framework into daily operation. Most teams produce a thoughtful responsible-AI document and then watch it gather dust. You will learn the practices that keep responsible-AI commitments alive: team rituals that surface ethical questions early, refreshed framework reviews as the team and technology evolve, edge-case handling when something genuinely goes wrong, and how the team communicates its responsible-AI posture externally without overpromising. The labs have you turn each framework principle into a specific ritual, decision rule, or recurring conversation.

In this final module, you will assemble everything from Modules 1 through 4 into a cumulative project: a Governance and Responsible Agentic AI Package. The deliverable includes an accountability matrix and auditability plan, an operating-rhythm design with oversight touchpoints, a trust, transparency, and explainability plan with an open-concerns brief, and a responsible-AI operating practice with an external statement and edge-case response template. The module closes with a wrap-up featuring an SME interview, a day-in-the-life view of a Head of AI Governance, and a bridge into the performance and capstone work of Course 5.