BackgroundArtificial Intelligence (AI) has emerged as a transformative technology in modern medicine, offering significant improvements in diagnostics, treatment planning, disease prediction, drug discovery, and healthcare management. Despite its immense potential, AI implementation raises complex ethical challenges related to privacy, fairness, accountability, transparency, and patient autonomy.ObjectiveThis study explores the major ethical challenges associated with AI in medicine, evaluates their implications for healthcare delivery, and discusses strategies for ensuring responsible and ethical AI deployment.MethodsA narrative review of literature published between 2018 and 2025 was conducted using PubMed, Scopus, Web of Science, IEEE Xplore, Google Scholar, and policy documents from healthcare organizations. Relevant studies addressing ethical considerations, governance frameworks, AI regulation, and clinical implementation were analyzed.ResultsKey ethical concerns include algorithmic bias, patient privacy, informed consent, transparency, accountability, explainability, healthcare disparities, and legal responsibility. While AI can enhance healthcare efficiency and outcomes, inadequate governance may result in inequitable care, reduced trust, and potential patient harm.ConclusionEthical AI implementation requires multidisciplinary collaboration, transparent governance, robust regulatory frameworks, and continuous monitoring. Responsible integration of AI into medicine is essential to ensure patient safety, maintain trust, and maximize healthcare benefits.