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Nurse Midwives

Occupation · SOC 29-1161.00

Diagnose and coordinate all aspects of the birthing process, either independently or as part of a healthcare team. May provide well-woman gynecological care. Must have specialized, graduate nursing education.

Also called: Certified Nurse-Midwife (CNM) · Nurse Midwife · Staff Certified Nurse Midwife · Staff Nurse Midwife · Direct-Entry Midwife · Postpartum Nurse · Postpartum RN (Postpartum Registered Nurse) · Registered Nurse Midwife

Job family: Healthcare Practitioners and Technical Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-29-1161-00/context.md directly.

AI work map

A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.

Use as a copilot

Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.

  • Manage newborn care during the first weeks of life. · 0.8%
  • Develop and implement individualized plans for health care management. · 0.6%
  • Explain procedures to patients, family members, staff members or others. · 0.6%
See collaboration patterns →

Keep a human in the loop

Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.

  • Manage newborn care during the first weeks of life. · 100.0% need a human
  • Explain procedures to patients, family members, staff members or others. · 93.1% need a human
  • Develop and implement individualized plans for health care management. · 75.0% need a human
See the boundary tasks →

47th-percentile task overlap — yet about 500 openings a year (+11.1% projected, BLS), and observed AI use leans 6935% copilot, not hand-off (AEI) . What exposure means →

AI & job outlook

What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.

Exposure to current AI

Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.

Measure Rank vs all occupations Percentile Score
Overall AI exposure (Felten et al.) Moderate 54th 0.2
LLM task exposure, γ (OpenAI / Eloundou) Moderate 48th 0.6
AI assistant applicability (Microsoft) Moderate 41st 0.1

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.2), with simple added tooling (β 0.4), and including AI-powered software (γ 0.6). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.

This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.

How AI is actually used in this job

Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.

Write information in medical records or provide narrative summaries to communicate patient information to other health care providers. 2.2%
Develop and implement individualized plans for health care management. 1.0%
Plan, provide, or evaluate educational programs for nursing staff, health care teams, or the community. 0.8%
Conduct clinical research on topics such as maternal or infant health care, contraceptive methods, breastfeeding, and gynecological care. 0.7%
Explain procedures to patients, family members, staff members or others. 0.6%
Document patients' health histories, symptoms, physical conditions, or other diagnostic information. 0.5%

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook Growing fast · +11.1% by 2034
Projected annual openings 500
Employment 2024 → 2034 8,600 → 9,500

“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.

Where this work sits on the global GenAI gradient

The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.

30% mean task exposure (2025)
56th percentile of 427 placed occupations
+5 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Midwifery Professionals · 2222 30% Minimal

Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.

Working with AI in this job

How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.

Augmentation vs. automation 69.3% working with AI · 7.5% handed to AI
Most common way people use AI here Learning · you ask AI to explain or teach
Typical AI autonomy 3.0 / 5 · higher = AI acts more independently

What people delegate to AI

The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.

Task How Usage
Manage newborn care during the first weeks of life. Learning 0.8%
Develop and implement individualized plans for health care management. Learning 0.6%
Explain procedures to patients, family members, staff members or others. Learning 0.6%

Where a human is still needed

Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.

Manage newborn care during the first weeks of life. 100.0%
Explain procedures to patients, family members, staff members or others. 93.1%
Develop and implement individualized plans for health care management. 75.0%

What people most often hand AI here

Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.

  • Help me manage newborn care during the first weeks of life.

    From: Manage newborn care during the first weeks of life. · 0.8% of measured AI use · learning

  • Help me develop and implement individualized plans for health care management.

    From: Develop and implement individualized plans for health care management. · 0.6% of measured AI use · learning

  • Help me explain procedures to patients, family members, staff members or others.

    From: Explain procedures to patients, family members, staff members or others. · 0.6% of measured AI use · learning

Tasks

All 21 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Emerging tasks

Newer responsibilities O*NET has flagged as growing for this occupation.

  • Evaluate mental health of patients.
  • Screen patients for gynecologic conditions such as infections.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Knowledge

Medicine and Dentistry 4.8
Psychology 4.3
Customer and Personal Service 4.2
English Language 4.2
Biology 4.1
Sociology and Anthropology 3.8
Therapy and Counseling 3.7
Education and Training 3.7
Mathematics 3.1

Abilities

Written Comprehension 4.3
Oral Comprehension 4.1
Oral Expression 4.1
Problem Sensitivity 4.1
Deductive Reasoning 4.1
Written Expression 4.0
Inductive Reasoning 4.0
Near Vision 3.8
Speech Recognition 3.8
Speech Clarity 3.8
Information Ordering 3.6
Category Flexibility 3.4
Selective Attention 3.4
Fluency of Ideas 3.1
Memorization 3.1

Essential skills

Active Listening 4.1
Speaking 4.1
Critical Thinking 4.1
Reading Comprehension 4.0
Active Learning 4.0
Monitoring 4.0
Writing 3.9
Learning Strategies 3.3

Transferable skills

Social Perceptiveness 4.1
Coordination 3.9
Service Orientation 3.9
Complex Problem Solving 3.9
Judgment and Decision Making 3.8
Instructing 3.3
Systems Analysis 3.1
Time Management 3.1

Skills in demand

Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.

Tools & technology

Example Category
eClinicalWorks EHR software Medical software Hot technology
Epic Systems Medical software Hot technology
Microsoft Excel Spreadsheet software Hot technology
Microsoft Office software Office suite software Hot technology
Acrendo Medical Software Ob/Gyn EMR Medical software
Allscripts Professional EHR Medical software
Amkai AmkaiCharts Medical software
Bizmatics PrognoCIS EMR Medical software
Cerner Millennium Medical software
ChartWare EMR Medical software
digiChart OB-GYN Medical software
e-MDs software Medical software
GE Healthcare Centricity EMR Medical software
Greenway Medical Technologies PrimeSUITE Medical software
Medscribbler Enterprise Medical software
MicroFour PracticeStudio.NET EMR Medical software
NextGen Healthcare Information Systems EMR Medical software
Practice Partner Total Practice Partner Medical software
Prognosis Innovation Healthcare ChartAccess Medical software
SOAPware EMR Medical software
StatCom Patient Flow Logistics Enterprise Suite Medical software
SynaMed EMR Medical software
Texas Medical Software SpringCharts EMR Medical software

Work context

How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.

Face-to-Face Discussions with Individuals and Within Teams 5.0
Physical Proximity 4.9
Contact With Others 4.9
E-Mail 4.8
Telephone Conversations 4.8
Frequency of Decision Making 4.8
Indoors, Environmentally Controlled 4.7
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 4.7
Consequence of Error 4.7
Freedom to Make Decisions 4.7
Work With or Contribute to a Work Group or Team 4.6
Exposed to Disease or Infections 4.6
Impact of Decisions on Co-workers or Company Results 4.5
Deal With External Customers or the Public in General 4.5
Importance of Being Exact or Accurate 4.5
Coordinate or Lead Others in Accomplishing Work Activities 4.2
Determine Tasks, Priorities and Goals 4.1
Health and Safety of Other Workers 4.0
Time Pressure 3.8
Conflict Situations 3.7
Written Letters and Memos 3.7
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 3.6
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 3.6
Dealing With Unpleasant, Angry, or Discourteous People 3.5
Exposed to Contaminants 3.5
Work Outcomes and Results of Other Workers 3.4
Spend Time Standing 3.2
Importance of Repeating Same Tasks 3.1
Exposed to Cramped Work Space, Awkward Positions 3.0
Level of Competition 2.9
Spend Time Sitting 2.9
Spend Time Bending or Twisting Your Body 2.6
Spend Time Making Repetitive Motions 2.5
Spend Time Walking or Running 2.4
Wear Specialized Protective or Safety Equipment such as Breathing Apparatus, Safety Harness, Full Protection Suits, or Radiation Protection 2.3
Exposed to Extremely Bright or Inadequate Lighting Conditions 2.2
Public Speaking 2.1
Dealing with Violent or Physically Aggressive People 2.0
Spend Time Kneeling, Crouching, Stooping, or Crawling 2.0
Exposed to Hazardous Conditions 2.0

How to get in

Job zone
Zone 5 — Job Zone Five: Extensive Preparation Needed
Education
Most of these occupations require graduate school. For example, they may require a master's degree, and some require a Ph.D., M.D., or J.D. (law degree).
Typical entry-level education
Master's degree · BLS, the typical path — not a requirement
Related experience
Extensive skill, knowledge, and experience are needed for these occupations. Many require more than five years of experience. For example, surgeons must complete four years of college and an additional five to seven years of specialized medical training to be able to do their job.
Preparation level
SVP (8.0 and above) — total schooling plus on-the-job experience.

What to study: Health Professions and Related Programs . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.

Education of current workers

Share of people in this occupation at each level of education.

Master's Degree 81.3%
Post-Master's Certificate 15.6%
Post-Baccalaureate Certificate 3.1%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Work styles

Integrity 10.0
Cautiousness 9.0
Cooperation 8.0
Social Orientation 7.0
Self-Control 6.0
Stress Tolerance 5.0
Empathy 4.0

Interest areas

Health Care Service 6.8
Social Service 5.6
Medical Science 4.3
Teaching/Education 4.0
Professional Advising 3.9
Life Science 3.7

Career interests (Holland / RIASEC)

Social 6.0
Investigative 4.3
Conventional 3.4

Wages & employment

U.S. · annual wages (BLS OEWS)

$75k10th$104k25th$129kMedian$147k75th$177k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
9k202410k2034 (proj.)+11.1% · Growing fast
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $74,670
25th percentile $104,260
Median (50th) $128,790
75th percentile $146,520
90th percentile $177,040
People employed 8,280

Industries that employ this occupation

Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.

Industry Workers National median pay
Health Care and Social Assistance · Sector 8,030 $129,130
Educational Services · Sector 100 $116,190

Where this work is most concentrated

Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).

Industry Concentration Workers
Health Care and Social Assistance · Sector 6.47× 8,030
Educational Services · Sector 0.14× 100

Part of the Healthcare & Human Services career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Nurse Midwives sits at the 47th percentile of AI task-overlap and the 94th percentile of median pay, placed here against 10 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Nurse Midwives Licensed Practical and Licensed Vocational Nurses Nurse Anesthetists Acute Care Nurses Family Medicine Physicians AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.

What you can do with this

Options the data surfaces for Nurse Midwives — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Skills that travel

Capabilities this work builds that are used across many other occupations.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 56th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Nurse Midwives show 47th-percentile AI task overlap — and about 500 annual U.S. openings

  • Nurse Midwives rank in the 47th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
  • The occupation is projected to see about 500 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
  • BLS projects employment to be growing fast (+11.1%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $128,790, across about 8,280 U.S. workers.BLS OEWS (May 2024)
  • Of the AI use actually observed for this work, 69% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census.2026-01-15-v4-plus-2025-03-27-v2
Copy the whole kit
Nurse Midwives show 47th-percentile AI task overlap — and about 500 annual U.S. openings

• Nurse Midwives rank in the 47th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE)
• The occupation is projected to see about 500 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34)
• BLS projects employment to be growing fast (+11.1%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $128,790, across about 8,280 U.S. workers. (BLS OEWS (May 2024))
• Of the AI use actually observed for this work, 69% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2)

Source: Singulariki — "Nurse Midwives". https://singulariki.com/roles/role-29-1161-00
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.

AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom

Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Nurse Midwives." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-29-1161-00

APA

Singulariki. (2026). Nurse Midwives. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-29-1161-00

BibTeX
@misc{singulariki-role-29-1161-00,
  title  = {Nurse Midwives},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-29-1161-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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