Artificial Intelligence in Nursing Education and Clinical Practice: A Comprehensive Review

Abstract

Artificial intelligence (AI) is rapidly transforming healthcare delivery and nursing education by supporting clinical decision-making,
documentation, risk prediction, personalized learning, simulation, assessment, and administrative processes. The increasing availability of generative AI and large language models has further expanded opportunities for nurses and nursing students while introducing concerns related to accuracy, privacy, bias, academic integrity, accountability, and professional autonomy. This review examines contemporary applications of AI in nursing education and clinical practice, evaluates its potential benefits and limitations, and discusses ethical, educational, professional, and implementation considerations. A structured narrative literature search was undertaken using major biomedical and nursing databases and relevant authoritative sources, with emphasis on recent literature and evidence concerning nursing-specific applications. Current evidence indicates that AI can support learning, clinical reasoning, documentation, patient monitoring, decision support, workflow efficiency, and personalized education; however, evidence from real-world nursing settings remains less mature than technological development. Responsible integration requires AI literacy, faculty and workforce development, human oversight, transparent governance, protection of patient data, and continuous evaluation. AI should complement rather than replace nursing judgment, therapeutic relationships, and professional accountability.