Medium AI Risk Average

Rock splitters, quarry

SOC Code: 47-5051

Rock splitters, quarry carries a 26% AI exposure score (Medium automation risk), with a median annual wage of $47,460 and +4.4% projected employment growth from 2024 to 2034 (BLS), affecting approximately 3,200 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
26% Medium

Proportion of tasks susceptible to AI automation (O*NET analysis)

Projected Growth
+4.4%
2024–2034 (BLS)
+100 jobs
Median Annual Wage
$47,460
BLS May 2024
How wage figures are sourced →

AI Exposure vs Industry Growth

Workforce demand by occupation Sanctioned bespoke signature viz (@signature-viz, KIZ-799) showing occupation-level workforce demand from BLS OEWS data. Pure SVG, no external dependencies.Projected Growth 2024-2034 (BLS)Technology+12.8%Healthcare+10.2%Professional+7.8%Education+5.8%Construction+4.5%Finance+4.6%Logistics+3.2%Government+1.2%Manufacturing-2.1%Retail-3.4%
National AI Exposure
40%
Average across all occupations
Avg Wage Growth
+3.2%
Median annual wage change
High-Risk Roles
127
Occupations with >70% AI exposure

Total occupations tracked

832

Covering all SOC major groups

Data currency

2024

BLS Employment Projections

AI exposure avg

40%

Fleet-wide median across all roles

Methodology confidence 92.0%
Industry standard

Composite score weighing O*NET task data completeness, BLS projection methodology, and cross-validation with employer risk grades.

Employment Projections

3,200
Employment 2024
3,400
Projected 2034
+4.4%
Change (%)
+100
Change (jobs)

Occupation Insight

Rock splitters, quarry (SOC 47-5051) carries an AI exposure score of 26%, placing it in the Medium automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score below 40% reflects tasks anchored in physical dexterity, unstructured environments, or high-touch human interaction that current AI cannot reliably replicate.

The economic context matters alongside the risk score. BLS counted approximately 3,200 workers in this occupation in 2024, and projects a +4.4% change through 2034 — modest growth that keeps the occupation viable even as tasks evolve. Median annual compensation stands at $47,460, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires No formal educational credential, plus None of related experience.

For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Rock splitters, quarry. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.

Education & Entry Requirements

Typical Education
No formal educational credential
Work Experience
None
On-the-Job Training
Short-term on-the-job training

Top Tasks (O*NET)

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

Key Skills Required

  • Operation and Control
  • Operations Monitoring
  • Active Listening
  • Monitoring
  • Reading Comprehension
  • Critical Thinking
  • Coordination
  • Complex Problem Solving
  • Time Management
  • Speaking

Knowledge Areas

  • Production and Processing
  • Mechanical
  • Mathematics
  • Education and Training
  • Public Safety and Security
  • Administration and Management
  • English Language
  • Personnel and Human Resources
  • Customer and Personal Service
  • Transportation

Frequently Asked Questions

Will AI replace Rock splitters, quarry?

Rock splitters, quarry has an AI exposure score of 26%, indicating a medium level of automation risk. The majority of tasks in this role require human judgment, creativity, or physical presence that AI cannot easily replicate.

What is the job outlook for Rock splitters, quarry?

According to BLS Employment Projections 2024-2034, Rock splitters, quarry is projected to grow by 4.4% over the decade. Current employment stands at approximately 3,200 workers.

What skills are needed for Rock splitters, quarry?

Key skills for Rock splitters, quarry include Operation and Control, Operations Monitoring, Active Listening, and others. Typical entry-level education is No formal educational credential.

How much do Rock splitters, quarry earn?

The median annual wage for Rock splitters, quarry is $47,460, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.

What education is required for Rock splitters, quarry?

The typical entry-level education for Rock splitters, quarry is No formal educational credential. Employers generally expect None of related work experience. On-the-job training typically involves Short-term on-the-job training. Requirements can vary by employer and specialization.

Which companies employ Rock splitters, quarry?

Rock splitters, quarry roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.

AI Exposure Rating

1.3
out of 5.0

Medium automation risk based on 9 analyzed tasks. Most tasks require human judgment and are resistant to automation.

Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).

Related

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainWorkforce Editorial