Headline risk
2%
Very Low RiskAcupuncturists
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
Diagnose, treat, and prevent disorders by stimulating specific acupuncture points within the body using acupuncture needles. May also use cups, nutritional supplements, therapeutic massage, acupressure, and other alternative health therapies.
Task evidence
100% weighted task match · 5% effective coverage
Scores combine AI task overlap, human advantages, and local demand. How it works
United States Now
Median Wage
USD 78,140
Employment 2024
15.3K
Projected Change (2024–34)
6.8%
Openings (2024–34)
0.9K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Maintain and follow standard quality, safety, environmental, and infection control policies and procedures. AI use: 0%
- 2. Adhere to local, state, and federal laws, regulations, and statutes. AI use: 0%
- 3. Treat patients using tools, such as needles, cups, ear balls, seeds, pellets, or nutritional supplements. AI use: 0%
- 4. Identify correct anatomical and proportional point locations based on patients' anatomy and positions, contraindications, and precautions related to treatments, such as intradermal needles, moxibustion, electricity, guasha, or bleeding. AI use: 0%
- 5. Develop individual treatment plans and strategies. AI use: 0%
- 6. Insert needles to provide acupuncture treatment. AI use: 0%
Technologies
Requirements
Work context
Related
Source coverage
10/11 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.