The Guardian Algorithm: AI's Promise for Safer Childbirth

ABSTRACT Objective This article reviews the burgeoning applications of artificial intelligence (AI) in obstetrics, evaluating its diagnostic, predictive, and educational value, and addresses implementation challenges and needs for enhanced AI literacy in perinatal medicine. Methods We conducted a comprehensive synthesis of current literature on AI methodologies—ranging from symbolic approaches to deep learning—and their translation into obstetric contexts. Key domains examined include perinatal ultrasonography, foetal monitoring, risk stratification, patient education, clinician decision support, and emerging frameworks for AI adoption. Results AI technologies have advanced perinatal ultrasonography through automated foetal biometric measurements, standard plane detection, gestational age prediction, and anomaly screening; neurosonography and foetal echocardiography benefited from high accuracy even when performed by non‐experts. In foetal monitoring, AI‐enhanced cardiotocography and nonlinear heart rate analysis demonstrated classification accuracy exceeding 96%. Predictive models for adverse outcomes—such as preterm birth, preeclampsia, haemorrhage, and postpartum depression—show AUCs ranging from moderate to excellent (up to 0.99). Generative AI simplifies informed consent, improving readability and comprehension. Obstetricians value AI for clinical decision support, administrative relief, remote assistance, and care delivery in low‐resource settings. Despite this promise, clinical validation is limited, generalisability remains uncertain, and issues of transparency, bias, and regulatory integration persist. Frameworks like OPTICA offer structured pathways for responsible deployment. Conclusions AI holds transformative potential across obstetrics—from improving diagnostic precision and risk prediction to enhancing patient engagement and clinical workflows. To harness these benefits responsibly, clinical validation, ethical oversight, and AI‐focused training—including prompt engineering—must become integral to perinatal education and practice.