AI exposure by occupation, O*NET 47-5081.00
Will AI replace Helpers--Extraction Workers?
Helpers--Extraction Workers: AI does not yet handle any of the role's 14 tasks; most of the work is hands-on, and the part AI can address mostly needs an efficient-tier model.
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Every task, scored
The 14 tasks O*NET 30.3 lists for Helpers--Extraction Workers, from most to least exposed. None reaches 60, the level at which AI already handles a task.
| Task | AI exposure | Evidence | Model tier |
|---|---|---|---|
| Repair and maintain automotive and drilling equipment, using hand tools. | Estimated | Efficient | |
| Provide assistance to extraction craft workers, such as earth drillers and derrick operators. | Estimated | No tier | |
| Observe and monitor equipment operation during the extraction process to detect any problems. | Estimated | No tier | |
| Unload materials, devices, and machine parts, using hand tools. | Estimated | No tier | |
| Set up and adjust equipment used to excavate geological materials. | Estimated | No tier | |
| Organize materials to prepare for use. | Estimated | No tier | |
| Collect and examine geological matter, using hand tools and testing devices. | Estimated | No tier | |
| Signal workers to start geological material extraction or boring. | Estimated | No tier | |
| Clean up work areas and remove debris after extraction activities are complete. | Estimated | No tier | |
| Dismantle extracting and boring equipment used for excavation, using hand tools. | Estimated | No tier | |
| Clean and prepare sites for excavation or boring. | Estimated | No tier | |
| Load materials into well holes or into equipment, using hand tools. | Estimated | No tier | |
| Dig trenches. | Estimated | No tier | |
| Drive moving equipment to transport materials and parts to excavation sites. | Estimated | No tier |
Observed: scored from AI use recorded in the Anthropic Economic Index (June 2026 release), 0 of 14 tasks. Estimated: scored from the task's O*NET 30.3 work activity, 14 of 14. Importance is O*NET's 1 to 5 rating of how central the task is. Model tier is the lowest tier that can do the task under the published rubric; "No tier" marks hands-on work.
The model tier this role needs
An efficient-tier model or lower covers 7% of the role's importance-weighted task work. 7% of the work is something AI can address at some tier, and 93% is hands-on.
Efficient, standard and frontier tiers come from the JobRoute model tier reference. The recommended tier is the lowest one that covers 80% of the work AI can address. How the method works.
Wages, employment and outlook
- US employment
- 6,700
- Median annual wage
- $47,730
- Middle half of earners
- $41,430 to $57,920
- Projected change, 2024 to 2034
- -1.7%
Employment and wages: BLS Occupational Employment and Wage Statistics, May 2025, national. Projection: BLS Employment Projections 2024 to 2034.
Adjacent roles
The occupations that reuse the most of this role's skills, with the usual time to move. These are the first places to look when you plan to redeploy or retrain people in this role.
- Earth Drillers, Except Oil and Gas 70% skill overlap, about 11 months to move Exposure28
- Helpers--Production Workers 70% skill overlap, about 11 months to move Exposure18
- Helpers--Brickmasons, Blockmasons, Stonemasons, and Tile and Marble Setters 66% skill overlap, about 12 months to move Exposure18
- Helpers--Installation, Maintenance, and Repair Workers 66% skill overlap, about 12 months to move Exposure23
- Excavating and Loading Machine and Dragline Operators, Surface Mining 66% skill overlap, about 12 months to move Exposure22
Skill overlap and transition time from the JobRoute role adjacency graph on O*NET 30.3 skills.
Questions about Helpers--Extraction Workers and AI
Will AI replace Helpers--Extraction Workers?
Not on current evidence. None of the 14 tasks O*NET lists for this occupation reaches a task exposure of 60, the level at which JobRoute counts a task as handled by AI, and the role's importance-weighted exposure is 15 out of 100. JobRoute scores tasks, not whole jobs, so the score shows how much of the work changes rather than whether the job disappears.
What is the AI exposure of Helpers--Extraction Workers?
15 out of 100 on JobRoute's task exposure measure, the importance-weighted average of the role's O*NET task scores. Higher means more of the work is AI-doable today. 0 of the 14 task scores are observed in the Anthropic Economic Index (June 2026 release), and the other 14 are estimated from each task's O*NET work activity.
Which Helpers--Extraction Workers tasks can AI already do?
None reaches 60 yet. The most exposed task is: Repair and maintain automotive and drilling equipment, using hand tools, at 20 out of 100.
What AI model tier does this role need?
An efficient-tier model or lower covers 7% of the role's importance-weighted task work, and 93% is hands-on work that no model tier covers. JobRoute assigns each task the lowest tier that can do it under a published rubric and recommends the lowest tier that covers 80% of the work AI can address.
How many people work as Helpers--Extraction Workers, and what do they earn?
6,700 people in the United States, with a median annual wage of $47,730 (BLS Occupational Employment and Wage Statistics, May 2025). BLS Employment Projections expect a change of -1.7% from 2024 to 2034.
How to cite
Data version 2026-11-02, JobRoute method v1.0.0. Download all occupations or this occupation as JSON. Methodology.
JobRoute (2026). AI exposure: Helpers--Extraction Workers. Data version 2026-11-02, method v1.0.0. Built on O*NET 30.3, BLS OEWS May 2025 and the Anthropic Economic Index (June 2026). CC BY 4.0. https://www.jobroute.ai/jobs/helpers-extraction-workers
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