Headline risk
23%
Moderate RiskTextile cutting machine setters, operators, and tenders
AI displacement pressure score for United States AI Work Index, combining global AI task overlap with local wages, employment trends, and demand signals.
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
Set up, operate, or tend machines that cut textiles.
Task evidence
100% weighted task match · 3% effective coverage
Scores combine AI task overlap, human advantages, and local demand. How it works
United States Now
Median Wage
USD 37,940
Employment 2024
9.3K
Projected Change (2024–34)
-11.7%
Openings (2024–34)
1.0K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Inspect products to ensure that the quality standards and specifications are met. AI use: 0%
- 2. Start machines, monitor operations, and make adjustments as needed. AI use: 0%
- 3. Notify supervisors of mechanical malfunctions. AI use: 0%
- 4. Confer with coworkers to obtain information about orders, processes, or problems. AI use: 0%
- 5. Record information about work completed and machine settings. AI use: 0%
- 6. Place patterns on top of layers of fabric and cut fabric following patterns, using electric or manual knives, cutters, or computer numerically controlled cutting devices. AI use: 0%
Technologies
Requirements
Work context
Worker profile
Median age 39.3 · 53K employed
Under 25: 15% · 25–54: 66% · 55+: 19%
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
Data quality
Employment data available
Narrative & sources
Important context
This score measures structural AI displacement pressure, not actual job losses. Local wages and demand data are specific to United States AI Work Index; the underlying AI task overlap analysis is consistent across all countries.