AI Resilience Report forNurse Midwives

If you're thinking about becoming a nurse-midwife, here's some reassuring news: AI is showing up in maternity care, but it's mostly being used to support midwives, not replace them. Microsoft's 2025 analysis of "AI-safe jobs" even ranked nursing as the #2 safest career from automation, and the U.S. Bureau of Labor Statistics projects that employment of nurse anesthetists, nurse midwives, and nurse practitioners is projected to grow 35 percent from 2024 to 2034, much faster than the average for all occupations, according to the BLS Occupational Outlook Handbook ^{[1] [1]}.

Where AI is showing up is in documentation and early-warning monitoring — the desk-and-screen parts of the job. Maimonides Medical Center reports that its Medical Brain AI system ^[2] uses natural language processing to put into context information gathered from various sources, including electronic medical records, discharge summaries, lab results, diagnostic images, or provider notes, and leverages machine learning and clinical decision support to analyze the data, helping clinicians catch problems like a non-reassuring fetal heart rate during labor. A 2026 review in the International Journal of Gynecology & Obstetrics ^[3] describes how AI is being combined with remote sensors to "move care, not patients." A scoping review in MDPI's Healthcare journal ^[4] similarly notes that automated processes in documentation, supported through AI, can lead to a significant reduction in administrative burdens, providing more time to focus on patients' care.

The hands-on parts of midwifery — catching a baby, coaching breathing, holding a scared parent's hand — remain firmly human, which is why nurses perform in-person and highly physical patient care that even the most advanced medical robots can't take over, and patients rely on having nurses who listen to their concerns and advocate for them, as the University of Cincinnati's 2026 analysis ^[5] explains.

Adoption is moving forward, but slowly and carefully. On the "faster" side, hospitals have strong financial and safety incentives — Maimonides reports that Medical Brain helped reduce adverse events by nearly 91%, with the rate of "never events" falling from nearly 118 per 1,000 patients to roughly 11 out of 1,000, a result that's hard for administrators to ignore. Persistent staffing shortages and rising maternal mortality also push hospitals to try anything that frees up midwife time.

A recent Journal of Midwifery & Women's Health article ^[6] by Koontz (2025) discusses how generative AI is already being integrated into midwifery education itself.

On the "slower" side, midwives themselves are cautious — and for good reasons. The MDPI scoping review ^[7] found that integration remains limited due to two key obstacles: ethical concerns such as data privacy, and a notable level of anxiety or hesitation among midwives associated with low levels of digital health literacy, and that midwives express prejudices and concerns about trust, ethics, and dehumanization, and reluctance to replace human care with AI. Pregnancy care is also high-stakes, heavily regulated, and deeply personal — patients want a human present at one of the most vulnerable moments of their lives.

So while AI will likely keep taking over charting, alerting, and pattern-spotting, the heart of nurse-midwifery — the trust, touch, and judgment — is exactly the kind of work that's hardest to automate. If you're drawn to this career, lean into those human strengths and get comfortable using AI as a teammate, not a competitor.