The emergence of agentic AI signifies a pivotal change in the realm of artificial intelligence, altering autonomy, decision-making, and human–machine interaction. In contrast to conventional AI systems constrained by task-specific functions, Agentic AI demonstrates context-sensitive adaptability, ethical reasoning, and autonomous decision-making, establishing itself as a fundamental element of human-centric innovation. This chapter examines the progression of AI autonomy, transitioning from primitive rule-based systems to contemporary adaptive models, and emphasizes the transformative impact of Agentic AI on sectors including health care, supply chain management, and climate change mitigation. This study analyzes the principles of agentic AI, focusing on its ability for contextual decision-making and human collaboration, while also addressing ethical and social challenges, including accountability, bias, and transparency. This chapter examines the contributions of multi-agent systems, reinforcement learning, and cognitive architectures to the development of agentic AI capabilities. Looking ahead, we discuss the future of human-AI collaboration, emphasizing trends like codesign and co-creation, and outline the critical need for global governance frameworks and ethical development practices. This chapter ultimately calls for a collective effort from researchers, industries, and policymakers to harness the full potential of agentic AI in an equitable, responsible, and human-centered manner.