Midwifery Associate Professionals

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 4 task statements that define Midwifery Associate Professionals (ISCO-08 3222) score an average of 0.20 on a 0–1 exposure scale — more exposed than about 32% of the 427 placed occupations. Roughly 0% of its tasks fall somewhere on the exposed part of the gradient, and the typical task lands in the Not exposed band.

Exposure is task overlap, not a verdict. A high score means a generative-AI model can do part of the content of these tasks — it says nothing about whether the work is automated, whether anyone uses AI for it today, or whether jobs are lost. The gradient is scored on the international ISCO-08 system; the rest of Singulariki is U.S. O*NET/SOC, bridged below by an approximate, many-to-many crosswalk.

How its tasks split across the gradient

Each of the 4 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Providing advice to women, families and communities on health, nutrition, hygiene, exercise, birth and emergency plans, breastfeeding, infant care, family planning and contraception, lifestyle and other topics related to pregnancy and childbirth;”

Scores 0.28 on the 2025 scale. The task of providing advice on health, nutrition, hygiene, exercise, birth plans, breastfeeding, etc., during pregnancy and childbirth requires significant human interaction, empathy, and the ability to adapt advice based on individual circumstances. While AI can play a supportive role by generating general health guidelines, educational materials, and tracking known health data, the nuanced understanding and personal engagement required are challenging for AI to fully replicate. Comparing this task with similar roles such as conducting educational and health activities (adjusted score: 0.245) and planning standard obstetric care (adjusted score: 0.25), both require personalized and context-specific interaction that AI struggles to automate. These tasks have reflected a slight potential for AI assistance, primarily in supporting roles. Given the high-income context like Poland with common digital access, AI can enhance information delivery, but the core empathetic and adaptive nature of the task remains predominantly human-driven. Thus, an adjusted score of 0.28 reflects the augmentation potential of AI while emphasizing human expertise's critical role in such complex health advisory services.

Moving fastest, 2023 → 2025

“Assessing progress during pregnancy and childbirth, and recognizing signs and symptoms requiring referral to a health professional;”

Model capability on this task changed by +0.11 in two years — the gradient is not static, it is filling in.

U.S. occupations this maps to

The American O*NET/SOC roles that crosswalk to ISCO-08 3222, biggest by employment first, via the published (approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 correspondence. These are the closest U.S. matches — not an asserted one-to-one identity.

• Healthcare Practitioners and Technical Workers, All Other
• Midwives

In context

Part of the 3 - Technicians and associate professionals major group. Return to the full gradient to see how the whole group sits.

Midwifery Associate Professionals sit at the 32nd percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Midwifery Associate Professionals rank in the 32nd percentile for GenAI task exposure — overlap with what generative AI can attempt, not a projection of displacement. (ILO / Gmyrek et al. (2025) GenAI exposure gradient)
• About 0% of this occupation's tasks fall into an exposed gradient band. (ILO / Gmyrek et al. (2025))
• Mean task exposure fell by 0.02 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Providing advice to women, families and communities on health, nutrition, hygiene, exercise, birth and emergency plans, breastfeeding, infant care, family planning and contraception, lifestyle and other topics related to pregnancy and childbirth;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Midwifery Associate Professionals". https://singulariki.com/gradient/3222-midwifery-associate-professionals.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.