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AI exposure Construction and extraction

Will AI replace rock splitters?

Rock Splitters, Quarry. US occupation 47-5051.

0.0%

of the time rock splitters spend on their work goes on tasks where AI is already being used to do that work.of rock splitters' working hours go on tasks AI has already started taking off their plate.

Ranked 346 of 756 US occupations. No AI use seen in the work yet, along with 410 other occupations.No handover started yet, along with 410 other occupations.

Average US job 7.7%

Among the least exposed jobs there are.Still waiting for liberation.

What AI already does for rock splittersWhat rock splitters no longer do alone

O*NET lists 9 tasks for rock splitters. None of them shows meaningful AI use at work yet.

What it does not touch, yetWhat still needs a human

9 of the 9 tasks show no AI use at work in the data.

  • Insert wedges and feathers into holes, and drive wedges with sledgehammers to split stone sections from masses.Core task
  • Locate grain line patterns to determine how rocks will split when cut.Core task
  • Mark dimensions or outlines on stone prior to cutting, using rules and chalk lines.Core task
  • Remove pieces of stone from larger masses, using jackhammers, wedges, and other tools.Core task
  • Cut grooves along outlines, using chisels.
  • Cut slabs of stone into sheets that will be used for floors or counters.
Show the other 3
  • Drill holes along outlines, using jackhammers.
  • Drill holes into sides of stones broken from masses, insert dogs or attach slings, and direct removal of stones.
  • Set charges of explosives to split rock.

How that compares

Among the 56 construction and extraction occupations, rock splitters rank 45. The group averages 0.4%, and its most exposed job is Structural Iron and Steel Workers at 4.9%. The average US occupation sits at 7.7%.

All 756 occupations, ranked

Level with 0.0%

  1. 346Reinforcing Iron and Rebar Workers 0.0%
  2. 346Respiratory Therapists 0.0%
  3. 346Riggers 0.0%

What this does and does not mean

Exposure is observed use, not a forecast. Anthropic maps work conversations with Claude onto the tasks O*NET lists for each job and asks, of the tasks AI could speed up, which are actually being used for at work. A use that does the task outright counts in full and a use that assists a person counts half. The task scores are averaged into the occupation figure by the share of time spent on each task.

A high figure means AI is already part of how this work gets done. It does not mean anyone has been replaced. Anthropic's own reading of the labour market finds no systematic rise in unemployment among exposed workers so far, and about 14% fewer 22 to 25 year olds starting exposed jobs.No measurable rise in unemployment among exposed workers so far, and about 14% fewer 22 to 25 year olds starting these jobs. Gap years for everyone. Labor market impacts, 5 March 2026.

Task list and titles from O*NET 31.0 by the US Department of Labor, Employment and Training Administration, used under the CC BY 4.0 licence. Scores from the Anthropic Economic Index (CC BY). Checked 1 November 2026. How the ranking works.