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  • Defining Responsible Agentic AI
  • Principle 1: Define a Clear Purpose and Measure Success
  • Principle 2: Provide Oversight and Ownership
  • Principle 3: Minimize Known Risks
  • Principle 4: Create an Accessible Audit Trail
  • Deploying Agentic AI
  • Practical Guide to Internal-Facing AI Agents
  • Practical Guide to External-Facing AI Agents
  • Governing Responsible AI
  • Governance Approach
  • Change Types and Review Path
  • Glossary and Additional Resources
  • Glossary
  • Additional Resources
  • Acknowledgments
  • Governance Approach

    The recommended operating model combines (a) a management-system backbone that supports continual improvement (Plan–Do–Check–Act), commonly used in mature governance programs (e.g., data/IT governance); and (b) an open, transparent contribution workflow inspired by well-run open-source projects (clear roles, predictable decision paths, and versioning discipline). 

    Roles and Decision Rights 

    The governance approach uses seven core roles: the accountable owner, the evaluation lead, the security lead, the transparency lead, the responsible agentic AI lead, the contributor, and the independent reviewer (if needed). Some roles may be combined initially, but separation is the goal as we mature in this framework.

     


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