Artificial Intelligence in Nursing: A Comprehensive Review


Abyad A 1, Abyad R 2

1 MD, MPH, MBA, DBA, AGSF , AFCHSE
Consultant internal medicine & Geriatric. Dar Al Shifa Hospital -Kuwait
Chairman, Middle-East Academy for Medicine of Aging. www.mea-ma.com
President, Middle East & North Africa Association on Aging & Alzheimer’s www.menaaa.org
Coordinator, Middle-East Primary Care Research Network
Coordinator, Middle-East Network on Aging www.me-jaa.com/menar-index.htm
Editor, Middle-East Journal of Family Medicine www.mejfm.com
Editor, Middle-East Journal of Age & Aging www.me-jaa.com
Editor, Middle-East Journal of Nursing www.me-jn.com
2 Bsc, MSc International Health, General Manager, Abyad Medical Center, Lebanon

Correspondence:
A Abyad
Email: aabyad@cyberia.net.lb

Received: October 2025; Accepted: November 2025; Published: November-December 2025
Citation: Abyad A, Abyad R. Artificial Intelligence in Nursing: A Comprehensive Review. Middle East Journal of Nursing 2025; 19(1): 38-50. DOI: 10.5742/MEJN2025.9378108

..............................................................................................................................................

..............................................................................................................................................

ABSTRACT

Artificial intelligence (AI) represents one of the most consequential technological transformations in modern healthcare, enabling unprecedented capabilities in prediction, automation, simulation, and decision support. Nursing, as the largest segment of the global health workforce, stands at the center of this transformation. AI not only enhances clinical decision-making and early recognition of patient deterioration, but it also impacts nursing education, administrative processes, and research methodologies. This expanded narrative review synthesizes a wide range of empirical evidence and conceptual literature to examine how AI is reshaping the nursing profession. The review discusses machine learning (ML), natural language processing (NLP), robotics, virtual simulation, and decision-support systems in the context of clinical practice, education, management, and research. Ethical, legal, and professional implications are also explored, with emphasis on algorithmic bias, data governance, explainability, and the preservation of the nurse–patient relationship. Two comprehensive tables summarize clinical applications and implementation challenges.
The review concludes with recommendations for practice, governance, and future research, emphasizing the critical importance of AI literacy and human-centered design to ensure equitable, transparent, and compassionate use of AI technologies in nursing.

Keywords: artificial intelligence, nursing, machine learning, decision support, nursing education, ethics, robotics