Clinical artificial intelligence competence in obstetrics and gynecology: patient safety, physician accountability, and responsible use.

Abstract

Artificial intelligence, especially generative large language models, has rapidly entered obstetric and gynecologic care through patient use, clinician documentation, counseling support, medical education, and evidence retrieval. This integration has occurred faster than formal training, specialty-specific standards, or governance structures have developed. The relevant clinical question is, therefore, no longer whether obstetricians and gynecologists will encounter artificial intelligence, but whether they can use it competently, verify its outputs, protect patient privacy, and remain accountable for clinical decisions. This Clinical Opinion proposes clinical artificial intelligence competence as an emerging component of safe professional practice in obstetrics and gynecology. We define this competence as the ability to use artificial intelligence tools for appropriate clinical tasks while critically appraising output, recognizing hallucinations and outdated guidance, verifying sources, preserving confidentiality, communicating uncertainty, and maintaining independent clinical judgment. Potential benefits include improved readability of patient materials, more efficient evidence retrieval, documentation support, informed consent assistance, and reduced cognitive burden during complex care. Risks include fabricated citations, incorrect recommendations, algorithmic bias, privacy breaches, deskilling of trainees, and inappropriate delegation of clinical reasoning. Historical experience with ultrasound, electronic fetal monitoring, cell-free DNA screening, and other obstetric technologies suggests that the profession should neither reject new tools reflexively nor adopt them uncritically. Instead, artificial intelligence use should be structured, supervised, version-specific, and proportionate to clinical risk. Clinical artificial intelligence competence should be incorporated gradually into residency, fellowship, continuing medical education, departmental teaching, morbidity and mortality review, and patient safety programs. Outcome-based evaluation remains essential as these tools enter practice.