Helpers--extraction workers
SOC Code: 47-5081
Helpers--extraction workers carries a 24% AI exposure score (Medium automation risk), with a median annual wage of $48,400 and -1.7% projected employment growth from 2024 to 2034 (BLS), affecting approximately 7,000 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 24% AI exposure, Helpers--extraction workers sits 13 points below the 37.2% average across 832 U.S. occupations - more exposed than 13% of them. It ranks among the more AI-resilient roles in the dataset.
Where Helpers--extraction workers sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Helpers--extraction workers has ai exposure of 24%. Distribution: 1 occupations at 0-10%; 43 occupations at 10-20%; 184 occupations at 20-30%; 332 occupations at 30-40%; 158 occupations at 40-50%; 64 occupations at 50-60%; 29 occupations at 60-70%; 15 occupations at 70-80%; 5 occupations at 80-90%; 1 occupations at 90-100%.
Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.
Helpers--extraction workers vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Helpers--extraction workers is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Occupation Insight
Helpers--extraction workers (SOC 47-5081) carries an AI exposure score of 24%, 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 7,000 workers in this occupation in 2024, and projects a -1.7% change through 2034 - a decline that often compounds with high AI exposure to create displacement headwinds. Median annual compensation stands at $48,400, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires High school diploma or equivalent, 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 Helpers--extraction workers. 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
Top Tasks (O*NET)
- 1. Provide assistance to extraction craft workers, such as earth drillers and derrick operators.
- 2. Observe and monitor equipment operation during the extraction process to detect any problems.
- 3. Drive moving equipment to transport materials and parts to excavation sites.
- 4. Unload materials, devices, and machine parts, using hand tools.
- 5. Set up and adjust equipment used to excavate geological materials.
- 6. Organize materials to prepare for use.
- 7. Repair and maintain automotive and drilling equipment, using hand tools.
- 8. Collect and examine geological matter, using hand tools and testing devices.
- 9. Signal workers to start geological material extraction or boring.
- 10. Clean up work areas and remove debris after extraction activities are complete.
Key Skills Required
- Monitoring
- Operations Monitoring
- Operation and Control
- Equipment Maintenance
- Troubleshooting
- Repairing
- Critical Thinking
- Coordination
- Equipment Selection
- Quality Control Analysis
Knowledge Areas
- Mechanical
- English Language
- Transportation
- Mathematics
- Administration and Management
- Public Safety and Security
- Education and Training
- Production and Processing
- Customer and Personal Service
- Engineering and Technology
Frequently Asked Questions
Will AI replace Helpers--extraction workers?
Helpers--extraction workers has an AI exposure score of 24%, 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 Helpers--extraction workers?
According to BLS Employment Projections 2024-2034, Helpers--extraction workers is projected to decline by 1.7% over the decade. Current employment stands at approximately 7,000 workers.
What skills are needed for Helpers--extraction workers?
Key skills for Helpers--extraction workers include Monitoring, Operations Monitoring, Operation and Control, and others. Typical entry-level education is High school diploma or equivalent.
How much do Helpers--extraction workers earn?
The median annual wage for Helpers--extraction workers is $48,400, 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 Helpers--extraction workers?
The typical entry-level education for Helpers--extraction workers is High school diploma or equivalent. Employers generally expect None of related work experience. On-the-job training typically involves Moderate-term on-the-job training. Requirements can vary by employer and specialization.
Which companies employ Helpers--extraction workers?
Helpers--extraction workers 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
Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.
Related Occupations
Career Guides
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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).