This chapter examines the ethical dimensions of AI agents, with particular focus on autonomous systems capable of independent decision-making in real-world environments. The chapter distinguishes between standard AI agents and autonomous systems, exploring their components including perception, decision-making, and action mechanisms. Through critical analysis of real-world case studies from healthcare (Babylon Health), law enforcement (PredPol), and customer service (Facebook chatbots), we identify key ethical concerns including bias, transparency, accountability, and unintended consequences. The chapter also covers practical frameworks for implementing AI agents using modern tools like LangChain, LangGraph, and Hugging Face, while emphasizing the importance of ethical design principles. Current benchmarking practices are critically evaluated, revealing gaps in cost-effectiveness analysis and real-world applicability. The chapter concludes with governance strategies and recommendations for responsible AI agent development and deployment.