AI in Healthcare: Accuracy, Ethics, and Clinical Integration

Abstract

Artificial Intelligence (AI) is transforming healthcare by enhancing diagnostic accuracy, operational efficiency, and personalized care. As AI systems become increasingly embedded in clinical workflows, questions of ethical alignment, trustworthiness, and equitable access emerge alongside technological optimism. This narrative review examines three key dimensions of AI adoption in healthcare: diagnostic accuracy and performance, ethical challenges including bias and transparency, and strategies for clinical integration. Drawing from recent literature, we highlight both progress and obstacles in ensuring that AI supports safe, human-centered, and inclusive healthcare delivery. We argue that meaningful integration requires a systems-level approach that includes regulatory clarity, clinical collaboration, and ethical safeguards.