AI and the Next Transformation in Obstetrics
From fetal monitoring to maternal risk prediction, artificial intelligence will reshape how obstetricians practice, teach, and ensure safety. The Prognosis — Forecasting where medicine goes next.
Artificial intelligence is no longer a futuristic concept in health care. According to the 2025 JAMA Summit Report on AI, it is transforming diagnosis, documentation, and decision-making across every medical field. Obstetrics, long defined by high-stakes decisions and data-rich environments, may be one of the specialties most affected by this disruption.
The JAMA Summit Report brought together 50 leading physicians, data scientists, ethicists, and regulators. Their message is clear: AI will touch every layer of health care—from imaging and documentation to patient counseling and workforce design. Yet its impact will depend on how wisely we integrate, evaluate, and govern these tools.
1. Clinical AI: From Decision Support to Safety Net
AI-driven clinical tools already influence the daily work of obstetricians. Algorithms can interpret ultrasound images to detect fetal anomalies, predict preeclampsia by analyzing longitudinal blood pressure trends, or calculate individualized risks for cesarean delivery and postpartum hemorrhage. Some centers are piloting “smart labor monitors” that continuously evaluate fetal heart rate tracings and uterine activity to alert clinicians before deterioration occurs.
The report underscores that such tools, though promising, face the same challenge as any medical intervention: proof of benefit. Unlike drugs or devices, AI tools often bypass rigorous evaluation and FDA review. Their accuracy depends not only on code but on human context—training, workflow, and trust. In obstetrics, where seconds can separate safety from tragedy, a false reassurance or an unnecessary alarm can have serious consequences. True algorithmovigilance—continuous real-world validation—will be essential. Imagine a national obstetric AI registry that links algorithmic alerts to outcomes, allowing continuous recalibration and transparency. That would move AI from hype to evidence.
2. Direct-to-Consumer AI: Empowering or Misleading Patients?
The fastest-growing AI presence in pregnancy is not in hospitals but on smartphones. More than half of pregnant women already use apps for tracking fetal movements, diet, contractions, or emotional health.
AI chatbots now offer “virtual prenatal coaching,” analyze sleep and heart rate from smartwatches, and claim to predict early labor onset.
The JAMA report notes that most such tools fall outside FDA oversight and often lack clinical validation. While many foster patient engagement, others risk spreading misinformation or inducing anxiety. A pregnant woman might receive contradictory AI-generated advice about contractions or diet, without her physician even knowing the tool was used. The opportunity lies in bridging these digital ecosystems: integrating validated patient-generated data into electronic health records and linking patients’ self-tracking with professional oversight. Done right, direct-to-consumer AI could reduce disparities by bringing reliable guidance to underserved areas. Done wrong, it could widen the information gap and fragment care.
3. Business Operations AI: The Invisible Hand Behind Care
Behind the delivery room, another AI revolution is quietly underway—this time in scheduling, resource allocation, and billing. The JAMA Summit identifies health care business operations as one of AI’s most rapidly expanding frontiers. In obstetrics, these systems can forecast labor unit volume, predict neonatal intensive care census, and optimize staff assignments or operating room schedules. Some hospitals already use AI to automate prior authorizations or insurance verifications for prenatal testing and cesarean procedures.
While such tools can reduce administrative burden, they also pose ethical risks. Algorithms trained primarily on cost and efficiency data may inadvertently prioritize revenue over patient access. For example, an AI that optimizes operating room use might delay a medically indicated induction because it classifies it as “low urgency.” The report warns that few of these systems undergo evaluation for their downstream effects on patient outcomes. Obstetricians, often unaware that AI-driven scheduling determines their workflow, must recognize that administrative algorithms can shape clinical opportunity. Transparent evaluation—“who benefits and how”—should become a standard ethical inquiry before adopting any operational AI.
4. Hybrid AI: Where Clinical and Operational Worlds Converge
The fastest-moving innovations are hybrid tools that merge clinical and administrative functions. AI scribes now record patient encounters, generate documentation, and even suggest treatment plans based on guideline prompts. In obstetrics, such tools can transcribe a prenatal visit, draft a birth plan, recommend follow-up intervals, and update billing codes simultaneously. Large language models integrated into patient portals may soon answer common prenatal questions or flag symptoms for review.
The JAMA report predicts that every patient–clinician conversation could soon include a live AI participant. This raises both potential and peril. Hybrid systems could free clinicians from data entry, allowing more eye contact and empathy. But they could also silently shape decisions, influencing tone, phrasing, and even patient perception of care. In obstetrics, where rapport and reassurance are central to trust, clinicians must preserve human presence as technology becomes more ambient. Hybrid AI should enhance—not replace—the moral and emotional fabric of the patient relationship.
5. The Coming Data Revolution
The JAMA Summit calls for a national learning infrastructure to monitor and refine AI tools in real time. Obstetrics is ideally suited to lead this movement. Birth data are continuous, structured, and abundant, from prenatal labs to Apgar scores. Linking these datasets across hospitals could allow rapid evaluation of AI performance in diverse populations.
The challenge is equity. If AI systems are trained mainly on urban or privately insured patients, they will fail those most at risk—rural women, women of color, and those with limited prenatal care. Responsible obstetric AI must include representative data and transparent labeling, just as a drug label lists known risks and populations studied.
6. Redefining the Workforce
AI will not eliminate obstetricians, but it will redefine their work. Routine charting and risk calculations may be delegated to machines, while human clinicians focus on interpretation, empathy, and ethical reasoning. Training programs will need to teach AI literacy alongside anatomy and ethics—how to question, audit, and correct algorithmic recommendations. Nurses, midwives, and sonographers may gain new authority as AI-guided diagnostics expand their scope. The obstetric team of the future will need to manage not just patients but digital collaborators.
My Take: Predictions, Impact, and What We Must Do Now
Artificial intelligence will transform obstetrics in five irreversible ways.
First, clinical decision-making will become data-verified rather than intuition-based. Protocols will increasingly draw from real-time analytics instead of consensus committees.
Second, documentation and communication will be largely automated. The obstetrician’s time will shift from typing to explaining, from data entry to decision synthesis.
Third, safety systems will become predictive. AI will detect subtle deterioration patterns long before clinicians recognize them—preeclampsia, sepsis, or fetal distress may one day be anticipated, not merely treated.
Fourth, patient empowerment will expand. Pregnant women will use validated AI companions to interpret lab results, prepare for delivery, and engage in shared decision-making on equal informational footing.
Fifth, disparities could shrink—or grow—depending on access, oversight, and inclusion. If we fail to ensure diverse data and equitable distribution, AI could mirror medicine’s worst biases rather than correct them.
What must we do now?
Demand transparency and validation. Every AI tool used in obstetrics should disclose its training data, performance, and known limitations—just as drugs disclose side effects.
Build AI literacy and prompt engineering education. Medical schools, residency programs, and continuing education must teach clinicians how to communicate effectively with AI systems. Understanding how to write, evaluate, and interpret prompts will become as essential as interpreting lab results.
Train patients too. Pregnant patients should learn how to use generative AI safely—knowing which prompts yield accurate information and which may spread misinformation. Hospitals and professional societies should lead this education effort, just as they once taught prenatal nutrition and childbirth preparation.
Ensure inclusion in data design. National perinatal databases must include all populations and outcomes, not only those easiest to study.
Put physicians in charge of governance. Obstetricians must lead the development of AI-related guidelines, policies, consents, and patient information materials. These documents should be clear, ethically sound, and transparent about risks, limitations, and responsibilities.
Preserve the human role. No algorithm can replace the presence, empathy, or ethical responsibility of a clinician guiding a family through childbirth.
AI will not make obstetrics easier. It will make it more accountable. Those who embrace it wisely will deliver safer, more equitable, and more humane care. Those who resist may find themselves left behind by a technology that is already in the room.
Reflection / Closing:
Artificial intelligence will touch every contraction, every scan, and every decision in obstetrics. It can either magnify human wisdom or automate human error. The JAMA Summit reminds us that technology is not destiny—it is design. Whether AI becomes obstetrics’ greatest ally or its next safety crisis will depend on how we build, test, and teach it. The real frontier is not the algorithm, but our accountability.