Headline risk
2%
Very Low RiskRock splitters, quarry
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
Separate blocks of rough dimension stone from quarry mass using jackhammers, wedges, or chop saws.
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 47,460
Employment 2024
3.2K
Projected Change (2024–34)
4.4%
Openings (2024–34)
0.4K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Remove pieces of stone from larger masses, using jackhammers, wedges, and other tools. AI use: 0%
- 2. Insert wedges and feathers into holes, and drive wedges with sledgehammers to split stone sections from masses. AI use: 0%
- 3. Locate grain line patterns to determine how rocks will split when cut. AI use: 0%
- 4. Mark dimensions or outlines on stone prior to cutting, using rules and chalk lines. AI use: 0%
- 5. Drill holes along outlines, using jackhammers. AI use: 0%
- 6. Drill holes into sides of stones broken from masses, insert dogs or attach slings, and direct removal of stones. 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
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.