Construction and Extraction · United States (national)
Excavating and Loading Machine and Dragline Operators, Surface Mining
How exposed this work is to automation, shown as ranges with the reasoning and sources.
The short version: this role is moderately exposed to automation, and meaningful change looks likely over the next 5 to 10 years.
It is a sourced range, not a verdict, and the detail is below.
Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown.
Data snapshot SNAPSHOT-2026-11-06. How it works
AI / softwarerange 0.0 to 12.0
Physical / roboticsrange 43.8 to 67.8
When the change is likely
Partial, 5 to 10 yearslocal demand stable
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Use your 5 to 10 year runway
Change here is gradual. Build resilient skills steadily and watch the signals rather than waiting for a shock.
2
Move up from the task to the system
Robotics targets the physical work. Shift toward supervising, maintaining, or programming the automation instead of competing with it.
3
Pivot toward Crane and Tower Operators
It is skill-adjacent and less exposed (54.6 vs 56). A lateral move now beats a forced one later.
4
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
5
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.
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Which of my tasks are exposed
Move levers, depress foot pedals, and turn dials to operate power machinery, such as power shovels, stripping shovels, scraper loaders, or backhoes.
55.8
Set up or inspect equipment prior to operation.
100.0
Become familiar with digging plans, machine capabilities and limitations, and efficient and safe digging procedures in a given application.
100.0
Observe hand signals, grade stakes, or other markings when operating machines so that work can be performed to specifications.
55.8
Operate machinery to perform activities such as backfilling excavations, vibrating or breaking rock or concrete, or making winter roads.
55.8
Receive written or oral instructions regarding material movement or excavation.
55.8
Move materials over short distances, such as around a construction site, factory, or warehouse.
55.8
Create or maintain inclines or ramps.
55.8
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Task: Set up or inspect equipment prior to operation.
Task: Become familiar with digging plans, machine capabilities and limitations, and efficient and safe digging procedures in a given application.
Lower-risk adjacent roles
Crane and Tower Operators
54.6
A full, ranked mitigation plan is part of the paid tiers.
How this score is calculated
Map Excavating and Loading Machine and Dragline Operators, Surface Mining to its standard O*NET task list (8 core tasks).
Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
The two axis scores are the task averages: AI 0.0, robotics 55.8.
The timeline comes from the higher axis (55.8), shifted for local demand (stable), and seniority. It is read against your remaining working years.
Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.
Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS.
Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.