As Artificial Intelligence (AI) continues to advance, particularly in the realm of Agentic AI, which is characterized by autonomous task execution, dynamic adaptation, and real-time decision optimization, it is crucial to develop effective governance frameworks that ensure ethical integrity, societal trust, and the transformative potential of these systems. This chapter explores the key principles and strategies necessary for responsible AI governance, emphasizing the importance of defining ethical principles, establishing accountability structures, implementing proactive risk management, fostering human-AI collaboration, and engaging with policymakers and regulatory bodies. The integration of explainability tools, bias detection mechanisms, and robust logging systems is essential to promote transparency, mitigate potential discrimination, and enhance accountability. Dynamic risk-assessment frameworks, scenario-based simulations, and fail-safe mechanisms are vital for identifying and mitigating vulnerabilities, ensuring resilience, and maintaining operational integrity. This highlights the significance of adaptive control systems, behavioral anchors, multi-stakeholder monitoring tools, and distributed accountability networks in addressing the complexities of Agentic AI governance. By aligning innovation with accountability and fostering a collective effort among policymakers, technologists, and communities, we can shape a responsible AI future that empowers humanity, safeguards shared values and enables sustainable progress in a rapidly changing world.