<![CDATA[Artificial intelligence (AI) is increasingly applied in healthcare, improving diagnostic accuracy, personalized treatment, and data management. However, its adoption raises ethical challenges related to patient privacy, algorithmic bias, clinical autonomy, and governance. This narrative review synthesizes peer-reviewed studies (2020–2025) identified through Scopus, PubMed, Google Scholar, and Web of Science. Findings indicate persistent risks of data breaches, algorithmic inequities, and loss of clinical autonomy. While techniques such as differential privacy and explainable AI offer solutions, their implementation remains uneven. Effective governance requires multi-stakeholder engagement and strong regulation. We conclude that responsible AI integration depends on transparent governance and inclusive model development to ensure equitable and trustworthy healthcare outcomes.]]>
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