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Excavating and Loading Machine and Dragline Operators, Surface Mining

Occupation · SOC 47-5022.00

Operate or tend machinery at surface mining site, equipped with scoops, shovels, or buckets to excavate and load loose materials.

Also called: Dragline Oiler · Dragline Operator · Heavy Equipment Operator · Loader Operator · Backhoe Operator · Equipment Operator · Excavator Operator · Pit Operator · Track Hoe Operator · Aerial Tram Operator · Air Shovel Operator · Back Digger Operator

Job family: Construction and Extraction Occupations

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AI work map

A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.

13th-percentile task overlap — yet about 3,100 openings a year (-0.4% projected, BLS) . What exposure means →

AI & job outlook

What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.

Exposure to current AI

Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.

Measure Rank vs all occupations Percentile Score
LLM task exposure, γ (OpenAI / Eloundou) Low 3rd 0.0
AI assistant applicability (Microsoft) Low 30th 0.1

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.0), and including AI-powered software (γ 0.0). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.

How AI is actually used in this job

Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.

Measure and verify levels of rock or gravel, bases, or other excavated material. 0.3%
Receive written or oral instructions regarding material movement or excavation. 0.2%

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook Declining · -0.4% by 2034
Projected annual openings 3,100
Employment 2024 → 2034 35,800 → 35,600

“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.

Tasks

All 16 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Transferable skills

Operation and Control 4.1
Operations Monitoring 3.6
Social Perceptiveness 3.0
Coordination 3.0
Persuasion 3.0
Complex Problem Solving 3.0
Equipment Selection 3.0
Equipment Maintenance 3.0
Troubleshooting 3.0
Repairing 3.0
Judgment and Decision Making 3.0
Time Management 3.0

Abilities

Control Precision 4.1
Multilimb Coordination 4.1
Depth Perception 4.0
Manual Dexterity 3.9
Reaction Time 3.9
Arm-Hand Steadiness 3.8
Response Orientation 3.8
Rate Control 3.8
Far Vision 3.8
Spatial Orientation 3.6
Near Vision 3.6
Finger Dexterity 3.5
Auditory Attention 3.5
Peripheral Vision 3.4
Hearing Sensitivity 3.3
Oral Comprehension 3.1
Oral Expression 3.1
Problem Sensitivity 3.1
Speech Recognition 3.1
Written Comprehension 3.0

Knowledge

Mechanical 3.2
Building and Construction 3.2

Essential skills

Monitoring 3.1
Reading Comprehension 3.0
Active Listening 3.0
Speaking 3.0
Critical Thinking 3.0
Active Learning 3.0

Skills in demand

Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.

Tools & technology

Example Category
Microsoft Excel Spreadsheet software Hot technology
Microsoft Office software Office suite software Hot technology
Microsoft Outlook Electronic mail software Hot technology
Microsoft PowerPoint Presentation software Hot technology
Microsoft Windows Operating system software Hot technology
Microsoft Word Word processing software Hot technology
Email software Electronic mail software
Google Gmail Electronic mail software
Machine control systems Industrial control software
Machine monitoring software Industrial control software

Work context

How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.

Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 4.9
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.7
Face-to-Face Discussions with Individuals and Within Teams 4.5
Work With or Contribute to a Work Group or Team 4.5
Contact With Others 4.4
Exposed to Whole Body Vibration 4.4
Exposed to Contaminants 4.4
Frequency of Decision Making 4.1
Outdoors, Exposed to All Weather Conditions 4.1
Spend Time Making Repetitive Motions 4.1
Exposed to Hazardous Equipment 4.1
Freedom to Make Decisions 4.1
In an Enclosed Vehicle or Operate Enclosed Equipment 4.0
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 4.0
Spend Time Sitting 4.0
Health and Safety of Other Workers 4.0
Determine Tasks, Priorities and Goals 3.9
Pace Determined by Speed of Equipment 3.9
Importance of Being Exact or Accurate 3.8
Consequence of Error 3.8
Exposed to Very Hot or Cold Temperatures 3.7
In an Open Vehicle or Operating Equipment 3.7
Impact of Decisions on Co-workers or Company Results 3.6
Coordinate or Lead Others in Accomplishing Work Activities 3.6
Time Pressure 3.6
Level of Competition 3.4
Importance of Repeating Same Tasks 3.3
Telephone Conversations 3.3
Work Outcomes and Results of Other Workers 3.3
Exposed to Minor Burns, Cuts, Bites, or Stings 3.1
Exposed to Extremely Bright or Inadequate Lighting Conditions 2.9
Exposed to Cramped Work Space, Awkward Positions 2.6
Physical Proximity 2.6
Exposed to Hazardous Conditions 2.6
Spend Time Bending or Twisting Your Body 2.5
Exposed to High Places 2.5
Dealing With Unpleasant, Angry, or Discourteous People 2.5
Spend Time Standing 2.5
Conflict Situations 2.4
Written Letters and Memos 2.3

How to get in

Job zone
Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
Education
Usually requires a high school diploma or GED, though some occupations may not.
Typical entry-level education
High school diploma or equivalent · BLS, the typical path — not a requirement
Related experience
Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
Preparation level
SVP (Below 6.0) — total schooling plus on-the-job experience.

What to study: Transportation and Materials Moving . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.

Education of current workers

Share of people in this occupation at each level of education.

High School Diploma 71.1%
Less than a High School Diploma 23.2%
Post-Secondary Certificate 5.7%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Career interests (Holland / RIASEC)

Realistic 7.0
Conventional 3.5
Investigative 2.4

Interest areas

Transportation/Machine Operation 6.2
Physical/Manual Labor 4.9
Mechanics/Electronics 3.4
Engineering 2.8
Construction/Woodwork 2.0
Nature/Outdoors 1.8
Management/Administration 1.1
Agriculture 1.1
Accounting 1.1

Work styles

Dependability 2.4
Cautiousness 2.3
Attention to Detail 1.6
Stress Tolerance 1.3

Wages & employment

U.S. · annual wages (BLS OEWS)

$40k10th$46k25th$53kMedian$64k75th$81k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
36k202436k2034 (proj.)-0.4% · Declining
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $39,650
25th percentile $46,290
Median (50th) $52,550
75th percentile $63,630
90th percentile $80,970
People employed 34,210

Industries that employ this occupation

Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.

Industry Workers National median pay
Mining, Quarrying, and Oil and Gas Extraction · Sector 20,530 $53,520
Construction · Sector 8,470 $54,570
Manufacturing · Sector 1,280 $52,550
Administrative and Support and Waste Management and Remediation Services · Sector 1,180 $45,390
Temporary Help Services · National industry 700 $44,090
Plumbing, Heating, and Air-Conditioning Contractors · National industry 310 $60,640
Wholesale Trade · Sector 300 $52,840
Landscaping Services · National industry 300 $49,420
Transportation and Warehousing · Sector 290 $49,560
Utilities · Sector 280 $133,570
Poured Concrete Foundation and Structure Contractors · National industry 260 $62,740
Masonry Contractors · National industry 260 $50,980

Where this work is most concentrated

Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).

Industry Concentration Workers
Mining, Quarrying, and Oil and Gas Extraction · Sector 161.35× 20,530
Masonry Contractors · National industry 8.16× 260
Construction · Sector 4.7× 8,470
Poured Concrete Foundation and Structure Contractors · National industry 4.53× 260
Power and Communication Line and Related Structures Construction · National industry 2.5× 130
Utilities · Sector 2.18× 280
Landscaping Services · National industry 1.48× 300
Temporary Help Services · National industry 1.19× 700

Part of the Construction and Energy & Natural Resources career clusters.

Exposure quadrant: AI task-overlap percentile vs Median pay Excavating and Loading Machine and Dragline Operators, Surface Mining sits at the 13th percentile of AI task-overlap and the 38th percentile of median pay, placed here against 12 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Excavating and Loading Machine and Dragline Operators, Surface Mining Helpers--Extraction Workers Pile Driver Operators Industrial Truck and Tractor Operators Continuous Mining Machine Operators Earth Drillers, Except Oil and Gas Crane and Tower Operators AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.

What you can do with this

Options the data surfaces for Excavating and Loading Machine and Dragline Operators, Surface Mining — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Write a report on thisheadline · factoids · citation

Excavating and Loading Machine and Dragline Operators, Surface Mining show 13th-percentile AI task overlap — and about 3,100 annual U.S. openings

  • Excavating and Loading Machine and Dragline Operators, Surface Mining rank in the 13th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
  • The occupation is projected to see about 3,100 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
  • BLS projects employment to be declining (-0.4%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $52,550, across about 34,210 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Excavating and Loading Machine and Dragline Operators, Surface Mining show 13th-percentile AI task overlap — and about 3,100 annual U.S. openings

• Excavating and Loading Machine and Dragline Operators, Surface Mining rank in the 13th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE)
• The occupation is projected to see about 3,100 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34)
• BLS projects employment to be declining (-0.4%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $52,550, across about 34,210 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Excavating and Loading Machine and Dragline Operators, Surface Mining". https://singulariki.com/roles/role-47-5022-00
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.

AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom

Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Excavating and Loading Machine and Dragline Operators, Surface Mining." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026. https://singulariki.com/roles/role-47-5022-00

APA

Singulariki. (2026). Excavating and Loading Machine and Dragline Operators, Surface Mining. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-47-5022-00

BibTeX
@misc{singulariki-role-47-5022-00,
  title  = {Excavating and Loading Machine and Dragline Operators, Surface Mining},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-47-5022-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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