Headline risk
36%
High RiskHealthcare practitioners and technical workers, all other
United States AI Work Index tracks this occupation on the shared structural baseline and then layers on local demand resilience, wages, and confidence.
Why This Score
Share of job tasks that overlap with current AI capabilities
Median annual wage
Projected employment change over 10 years
Typical preparation needed for this occupation
Occupation profile
All healthcare practitioners and technical workers not listed separately.
Task evidence
100% weighted task match · 0% effective coverage
Scores combine AI task overlap, human advantages, and local demand. How it works
United States Now
Median Wage
USD 64,030
Employment 2024
41.7K
Projected Change (2024–34)
3.6%
Openings (2024–34)
2.6K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Identify tubal and ectopic pregnancies and refer patients for treatments. AI use: 0%
- 2. Conduct ongoing prenatal health assessments, tracking changes in physical and emotional health. AI use: 0%
- 3. Monitor fetal growth and well-being through heartbeat detection, body measurement, and palpation. AI use: 0%
- 4. Establish and follow emergency or contingency plans for mothers and newborns. AI use: 0%
- 5. Monitor maternal condition during labor by checking vital signs, monitoring uterine contractions, or performing physical examinations. AI use: 0%
- 6. Identify, monitor, or treat pregnancy-related problems such as hypertension, gestational diabetes, pre-term labor, or retarded fetal growth. AI use: 0%
Technologies
Requirements
Work context
Worker profile
Median age 41.1 · 139K employed
Under 25: 8% · 25–54: 73% · 55+: 19%
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Source coverage
11/11 source families · O*NET 30.2 / OEWS 2024 / ORS 2025 / OOH 2025-08-28 / Projections 2024-34 / CPS 2025 / Anthropic task penetration
Mapping quality
title_match · employment series present
Narrative & sources
Published limitations
This page shows the local country layer, not realised individual job outcomes. The global structural baseline is shared across countries; only the local demand and wage layer changes here.
Built from O*NET occupation descriptions, task statements, technology skills, work context, Job Zones, Anthropic task penetration, BLS OEWS wages, BLS projection tables, BLS ORS requirements, BLS OOH narrative content, BLS skills data, and BLS CPS occupation age tables.