Headline risk
24%
Moderate RiskGrinding and polishing workers, hand
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
Grind, sand, or polish, using hand tools or hand-held power tools, a variety of metal, wood, stone, clay, plastic, or glass objects. Includes chippers, buffers, and finishers.
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 41,690
Employment 2024
11.8K
Projected Change (2024–34)
-21.2%
Openings (2024–34)
0.8K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Grind, sand, clean, or polish objects or parts to correct defects or to prepare surfaces for further finishing, using hand tools and power tools. AI use: 0%
- 2. Load and adjust workpieces onto equipment or work tables, using hand tools. AI use: 0%
- 3. Verify quality of finished workpieces by inspecting them, comparing them to templates, measuring their dimensions, or testing them in working machinery. AI use: 0%
- 4. Trim, scrape, or deburr objects or parts, using chisels, scrapers, and other hand tools and equipment. AI use: 0%
- 5. Select files or other abrasives, according to materials, sizes and shapes of workpieces, amount of stock to be removed, finishes specified, and steps in finishing processes. AI use: 0%
- 6. Measure and mark equipment, objects, or parts to ensure grinding and polishing standards are met. AI use: 0%
Technologies
Requirements
Work context
Worker profile
Median age 44.9 · 71K employed
Under 25: 6% · 25–54: 68% · 55+: 27%
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.