Headline risk
3%
Very Low RiskExcavating and loading machine and dragline operators, surface mining
United States AI Work Index tracks this occupation on the shared structural baseline and then layers on local demand resilience, wages, and confidence.
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
Operate or tend machinery at surface mining site, equipped with scoops, shovels, or buckets to excavate and load loose materials.
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 52,550
Employment 2024
35.8K
Projected Change (2024–34)
-0.4%
Openings (2024–34)
3.1K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Move levers, depress foot pedals, and turn dials to operate power machinery, such as power shovels, stripping shovels, scraper loaders, or backhoes. AI use: 0%
- 2. Set up or inspect equipment prior to operation. AI use: 0%
- 3. Become familiar with digging plans, machine capabilities and limitations, and efficient and safe digging procedures in a given application. AI use: 0%
- 4. Observe hand signals, grade stakes, or other markings when operating machines so that work can be performed to specifications. AI use: 0%
- 5. Receive written or oral instructions regarding material movement or excavation. AI use: 0%
- 6. Operate machinery to perform activities such as backfilling excavations, vibrating or breaking rock or concrete, or making winter roads. AI use: 0%
Technologies
Requirements
Work context
Worker profile
Median age 40.4 · 242K employed
Under 25: 16% · 25–54: 64% · 55+: 21%
Related
No direct US role match is available yet for this occupation.
Source coverage
11/11 source families · O*NET 30.2 / OEWS 2024 / ORS 2025 / OOH 2025-08-28 / Projections 2024-34 / CPS 2025 / Anthropic task penetration
Mapping quality
title_match · employment series present
Narrative & sources
Published limitations
This page shows the local country layer, not realised individual job outcomes. The global structural baseline is shared across countries; only the local demand and wage layer changes here.
Built from O*NET occupation descriptions, task statements, technology skills, work context, Job Zones, Anthropic task penetration, BLS OEWS wages, BLS projection tables, BLS ORS requirements, BLS OOH narrative content, BLS skills data, and BLS CPS occupation age tables.