JobAIRisk

Midwives

Midwives — AI exposure, safer roles, and a pivot plan.

Also known as: Birth Doula · Lay Midwife · Certified Midwife · Homebirth Midwife · Birth Center Midwife · Direct-Entry Midwife

AI Task Exposure Score

Moderate exposure

More exposed than 35% of 968 occupations · Rank #587 (1 = most exposed)

This score estimates how exposed the tasks in a role are to current and near-term AI capabilities. It does not predict whether a specific person will lose a job.

Most exposed tasks

Highest structured exposure values in this role’s task mix — the work AI systems can already do most of.

No strongly automatable task in the current data release.

Augmentable tasks

Work where AI assists rather than replaces — the productivity frontier of this role.

  • Provide information about the physical and emotional processes involved in the pregnancy, labor, birth, and postpartum periods.58
  • Evaluate patients' laboratory and medical records, requesting assistance from other practitioners when necessary.55
  • Maintain documentation of all patients' contacts, reviewing and updating records as necessary.54

Most durable tasks

Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.

  • Counsel women regarding the nutritional requirements of pregnancy.29
  • Provide necessary medical care for infants at birth, including emergency care such as resuscitation.30

Task exposure values and classifications come from the versioned data release — they are structured data, not model output. Bars show exposure contribution relative to this role’s task mix.

What this means

A score of 43 puts Midwives in the second quartile of analyzed occupations. In practice, exposure this level is about the mix: 0 of 20 analyzed tasks lean automatable, 18 augmentable, and 2 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.

One next move: adopt AI deliberately on the augmentable tasks and build visible evidence of the durable ones.

Lower-exposure adjacent roles

No adjacent role in the current data release is at least 10 points lower with ≥50% skill overlap — we don’t label anything “safer” unless the data supports it.

Labor-market context

  • $65,790median wage
  • 35,010employed
  • 2,600annual openings
  • +3.4%projected growth

Context only — labor statistics are not inputs to the exposure score. See methodology.

Your week probably doesn’t match the average

This page scores the occupation. The $9 Personalized Risk & Action Report scores your task mix — paste what you actually do and get your own score, confidence level, task matrix, human moat, and a 7/30/90-day plan.

Personalize my result — $9

Related roles

Adjacent by skills or family — no exposure claim implied.

FAQ — Midwives

What does a score of 43 mean for a Midwives?
It means that, weighted across the 20 tasks we analyzed for this role, the task mix sits at 43 on a 0–100 exposure scale — in the second quartile of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.
Which tasks in this role are most exposed to AI?
This role has no strongly automatable task in the current data release.
Which parts of this job are most durable?
The most durable responsibilities are: Counsel women regarding the nutritional requirements of pregnancy; Provide necessary medical care for infants at birth, including emergency care such as resuscitation. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.
Is this score personalized to me?
No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.

Score version jr-v1 · data release 2026.07.11-r1 · updated 2026-07-11 · baseline mapping: 20 of 20 tasks carry source-level provenance · methodology