Headline risk
8%
Low RiskSewing machine operators
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
Operate or tend sewing machines to join, reinforce, decorate, or perform related sewing operations in the manufacture of garment or nongarment products.
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 36,000
Employment 2024
124.0K
Projected Change (2024–34)
-10.8%
Openings (2024–34)
13.0K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Monitor machine operation to detect problems such as defective stitching, breaks in thread, or machine malfunctions. AI use: 0%
- 2. Place spools of thread, cord, or other materials on spindles, insert bobbins, and thread ends through machine guides and components. AI use: 0%
- 3. Guide garments or garment parts under machine needles and presser feet to sew parts together. AI use: 0%
- 4. Fold or stretch edges or lengths of items while sewing to facilitate forming specified sections. AI use: 0%
- 5. Select supplies such as fasteners and thread, according to job requirements. AI use: 0%
- 6. Position items under needles, using marks on machines, clamps, templates, or cloth as guides. AI use: 0%
Technologies
Requirements
Work context
Worker profile
Median age 48.9 · 92K employed
Under 25: 5% · 25–54: 59% · 55+: 37%
Related
No direct US role match is available yet for this occupation.
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
crosswalk_exact · 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.