The paper “Agentic AI: Autonomy, Accountability, and the Algorithmic Society” by Anirban Mukherjee and Hannah Chang offers a comprehensive framework for understanding the implications of agentic AI, a form of artificial intelligence that operates autonomously and proactively. Unlike traditional AI systems that react to inputs, agentic AI can independently initiate and manage complex processes, raising significant questions about authorship, legal accountability, and market competition. The authors explore how intellectual property laws might need to evolve to accommodate AI-generated works and discuss the challenges of attributing accountability when AI systems make decisions autonomously. They also examine the potential for AI-driven collusion in markets and the need for updated antitrust laws. Looking ahead, Mukherjee and Chang speculate on a future where networks of agentic AI systems establish their own norms, which could lead to both stability and new regulatory challenges. The paper calls for interdisciplinary collaboration to address these issues, offering valuable insights for policymakers, technologists, and legal experts as society adapts to an AI-driven world.