Artificial Intelligence (AI) is no longer confined to laboratory research or specialised applications; it has become a pervasive force influencing healthcare, law, finance, transportation, and social governance. With this growing ubiquity comes an equally pressing need to address the ethical dilemmas arising from AI design, deployment, and governance. This chapter provides a comprehensive overview of the ethical dimensions of AI, integrating technical foundations with societal considerations. It begins by outlining the types of AI, their core components, and lifecycle stages, each associated with specific ethical concerns such as bias, fairness, transparency, accountability, and data protection. Through real-world case studies—including criminal justice algorithms, facial recognition technologies, and autonomous vehicles—the chapter highlights how ethical lapses translate into tangible risks for individuals and communities. Moving beyond problem identification, it discusses frameworks for responsible AI, including ethical guidelines, regulatory measures, stakeholder engagement, and capacity-building through education. The chapter also examines emerging challenges such as global inequality, cultural pluralism, and adversarial vulnerabilities, emphasising the need for adaptive, interdisciplinary, and globally inclusive approaches. By situating technical innovations within broader moral, social, and regulatory contexts, this work underscores that ethical AI is not merely a technical aspiration but a societal imperative. The insights presented aim to guide researchers, practitioners, and policymakers in developing AI systems that are fair, transparent, accountable, and aligned with human values.