Artificial intelligence (AI) is rapidly transforming healthcare by enabling advanced data analysis, predictive modeling, and intelligent clinical decision support systems. In obstetrics and gynecology (OBG) nursing, AI technologies are increasingly recognized as valuable tools for improving maternal and women’s healthcare outcomes. These technologies facilitate early identification of high-risk pregnancies, enhance fetal monitoring accuracy, and support gynecologic cancer screening. This narrative review examines current evidence on the emerging applications of AI in obstetric and gynecologic practice, with particular emphasis on its relevance to nursing roles and responsibilities. A structured search of electronic databases, including PubMed, Scopus, Excerpta Medica Database (EMBASE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Web of Science, was conducted for studies published between January 2010 and July 2025. The search yielded 612 records, of which 62 studies met the inclusion criteria and were included in the thematic synthesis. Key domains explored include predictive analytics for maternal risk assessment, AI-assisted clinical decision support systems for labor and emergency management, wearable and remote monitoring technologies for continuous maternal and fetal surveillance, and image-based diagnostic tools used in gynecologic oncology screening and early disease detection. The review also highlights applications of AI in nursing education, including adaptive learning platforms and simulation-based training that enhance clinical reasoning and preparedness for obstetric emergencies. Ethical and implementation challenges, including algorithmic bias, data privacy, transparency, and equitable access, are also discussed. While AI shows promising potential to improve diagnostic accuracy, support evidence-based decision-making, and optimize workflow efficiency, much of the current evidence remains in developmental or pilot phases, with limited large-scale validation. Overall, AI has the potential to strengthen obstetrics and gynecology nursing practice by facilitating proactive, data-driven care while preserving the essential human-centered and compassionate nature of nursing in maternal and women’s health.
Sivasankari et al. (2026) studied this question.