Gini Loh System Tools

AI Automation Index

Will AI Replace Excavating and Loading Machine and Dragline Operators, Surface Mining?

Task-level automation exposure for Excavating and Loading Machine and Dragline Operators, Surface Mining: 16 O*NET tasks scored against their work activities, plus the simulator.

E-E-A-T Verified
Developed & audited by Gini Loh

Automation Exposure

20% weighted task index

16 of 16 tasks scored

Median Salary

$57,430 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

34,480 people hold this job — size, not growth

Projected 2025–35

+1.0% employment change

2,400 openings a year · BLS line item

Pay by state

BLS OEWS publishes 50 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$35,870 – $90,380

Highest medians

North Dakota $90,380
Illinois $80,600
New Jersey $80,310
Wyoming $78,230
New Mexico $76,350

Lowest medians

Puerto Rico $35,870
Arkansas $46,170
Delaware $46,900
Oklahoma $47,100
Alabama $47,770

State figures come from the 47-5022 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 21%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 55%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 22%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 0%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 53/100 High

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

16 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 15%

2 tasks

Medium exposure (≥ 35%) 5%

1 tasks

Low exposure (below 35%) 80%

13 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Constituent Tasks

#12777 · Core · 8% automatable

Move levers, depress foot pedals, and turn dials to operate power machinery, such as power shovels, stripping shovels, scraper loaders, or backhoes.

physical manipulation — Excavation equipment operated by hand in field

Operate excavation equipment.
#12778 · Core · 18% automatable

Set up or inspect equipment prior to operation.

visual inspection — Physical inspection of moving equipment

Inspect material-moving equipment to detect problems.
#12780 · Core · 70% automatable

Become familiar with digging plans, machine capabilities and limitations, and efficient and safe digging procedures in a given application.

information retrieval — AI supports study; certification requires human

Maintain professional knowledge or certifications.
#12779 · Core · 5% automatable

Observe hand signals, grade stakes, or other markings when operating machines so that work can be performed to specifications.

physical manipulation — Physical hand signals to direct vehicle movement

Signal others to coordinate vehicle movement.
#12781 · Core · 8% automatable

Operate machinery to perform activities such as backfilling excavations, vibrating or breaking rock or concrete, or making winter roads.

physical manipulation — Excavation equipment operated by hand in field

Operate excavation equipment.
#12786 · Core · 62% automatable

Receive written or oral instructions regarding material movement or excavation.

information retrieval — Receiving instructions is passive; AI can parse and relay

Receive information or instructions for performing work assignments.
#12784 · Core · 8% automatable

Move materials over short distances, such as around a construction site, factory, or warehouse.

physical manipulation — Manual moving of materials and supplies

Move materials, equipment, or supplies.
#20458 · Core · 10% automatable

Create or maintain inclines or ramps.

physical manipulation — Erecting temporary structures requires physical assembly

Assemble temporary equipment or structures. Maintain work equipment or machinery.
#12783 · Core · 8% automatable

Lubricate, adjust, or repair machinery and replace parts, such as gears, bearings, or bucket teeth.

physical manipulation — Physical maintenance of material moving equipment

Maintain material moving equipment in good working condition.
#20459 · Core · 5% automatable

Handle slides, mud, or pit cleanings or maintenance.

physical manipulation — Physical cleaning of facilities and work areas

Clean facilities or work areas.
#12791 · Supplemental · 22% automatable

Direct workers engaged in placing blocks or outriggers to prevent capsizing of machines when lifting heavy loads.

physical manipulation — Material handling direction is on-floor supervision

Direct material handling or moving activities.
#12785 · Supplemental · 53% automatable

Measure and verify levels of rock or gravel, bases, or other excavated material.

information retrieval — Spec verification against references, human confirms edge cases

Measure product or material dimensions. Verify information or specifications.
#12790 · Supplemental · 22% automatable

Direct ground workers engaged in activities such as moving stakes or markers, or changing positions of towers.

physical manipulation — Material handling direction is on-floor supervision

Direct material handling or moving activities.
#12787 · Supplemental · 8% automatable

Adjust dig face angles for varying overburden depths and set lengths.

physical manipulation — Excavation equipment operated by hand in field

Operate excavation equipment.
#12788 · Supplemental · 8% automatable

Drive machines to work sites.

physical manipulation — Excavation equipment operated by hand in field

Operate excavation equipment.
#12789 · Supplemental · 3% automatable

Perform manual labor to prepare or finish sites, such as shoveling materials by hand.

physical manipulation — Manual shoveling of loose materials

Shovel materials.
Embed this calculator on your site ↓

Bloggers & authors: Embed this interactive calculator directly in your articles or comparison guides. It loads dynamically via a responsive iframe (auto-resizing to prevent double scrollbars) and provides a direct, high-value tool for your audience.

<div class="giniloh-calculator-embed" data-calculator="excavating-and-loading-machine-and-dragline-operators-surface-mining"></div> <script src="https://giniloh.com/embed.js" async></script>

Community Sentiment

Do you agree?

Do you agree with the AI automation risk score calculated for this occupation?

Method

How this was scored

  1. 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
  2. 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
  3. 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
  4. 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

Related Article

Engineer at work

Best AI Proof Jobs in a Changing Market

Worried robots are coming for your paycheck? You’re not alone—but the real story is far more hopeful. This guide cuts through the scare headlines to reveal exactly where smart, sustainable career opportunities exist right now. We’ve curated a list of true ai proof jobs—roles in healthcare, skilled trades, and cybersecurity that not only survive automation but thrive because of human judgment and empathy. You’ll get specific, money-making data on projected growth (the BLS says wind turbine technicians, for instance, will grow 44% by 2032), real salary ranges from active job listings, and a simple self-assessment quiz to identify your own most resilient path. Plus, we name companies hiring today and the niche job boards they use. Stop worrying and start planning—your secure career is closer than you think.

Read Article ->