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Operating Engineers and Other Construction Equipment Operators

Occupation · SOC 47-2073.00

Operate one or several types of power construction equipment, such as motor graders, bulldozers, scrapers, compressors, pumps, derricks, shovels, tractors, or front-end loaders to excavate, move, and grade earth, erect structures, or pour concrete or other hard surface pavement. May repair and maintain equipment in addition to other duties.

Also called: Equipment Operator (EO) · Heavy Equipment Operator (HEO) · Machine Operator · Operating Engineer · Back Hoe Operator · Engineering Equipment Operator · Forklift Operator · Hot Mix Asphalt Operator · Motor Grader Operator · Track Hoe Operator · Angle Dozer Operator · Asphalt Roller Operator

Job family: Construction and Extraction Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-47-2073-00/context.md directly.

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.

17th-percentile task overlap — yet about 41,900 openings a year (+3.6% 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
Overall AI exposure (Felten et al.) Low 22nd -0.9
LLM task exposure, γ (OpenAI / Eloundou) Low 9th 0.1
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 0.1), and including AI-powered software (γ 0.1). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.

This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.

Mixed signals. Today's AI/LLM studies show relatively low exposure for this job, but the older (2013) Frey–Osborne work rated it higher for computerization and robotics. Different eras, different technologies — the AI measures above reflect the current state.

Historical automation estimate (2013)

A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.

Frey–Osborne probability 0.9 · 89th percentile among occupations · High

Job outlook

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

Outlook About average · +3.6% by 2034
Projected annual openings 41,900
Employment 2024 → 2034 489,300 → 507,100

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

Where this work sits on the global GenAI gradient

The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.

13% mean task exposure (2025)
11th percentile of 427 placed occupations
+1 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Earthmoving and Related Plant Operators · 8342 13% Not exposed

Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.

Tasks

All 28 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 3.3
Equipment Maintenance 3.3
Troubleshooting 3.0
Time Management 3.0

Abilities

Control Precision 4.1
Depth Perception 4.0
Multilimb Coordination 3.9
Near Vision 3.9
Far Vision 3.6
Rate Control 3.5
Reaction Time 3.4
Problem Sensitivity 3.3
Arm-Hand Steadiness 3.3
Response Orientation 3.3
Oral Comprehension 3.1
Perceptual Speed 3.1
Visualization 3.1
Manual Dexterity 3.1
Oral Expression 3.0
Deductive Reasoning 3.0
Inductive Reasoning 3.0
Information Ordering 3.0
Selective Attention 3.0
Time Sharing 3.0
Finger Dexterity 3.0
Static Strength 3.0
Visual Color Discrimination 3.0
Hearing Sensitivity 3.0
Auditory Attention 3.0
Speech Recognition 3.0
Speech Clarity 3.0

Knowledge

Mechanical 3.6
English Language 3.3
Public Safety and Security 3.1

Essential skills

Monitoring 3.1
Active Listening 3.0
Reading Comprehension 2.9
Speaking 2.9
Critical Thinking 2.9

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 Windows Operating system software Hot technology
Maintenance record software Facilities management software
Work record software Time accounting 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.

Outdoors, Exposed to All Weather Conditions 5.0
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 5.0
Consequence of Error 4.9
Face-to-Face Discussions with Individuals and Within Teams 4.8
Frequency of Decision Making 4.8
Exposed to Hazardous Equipment 4.7
Contact With Others 4.7
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.7
Impact of Decisions on Co-workers or Company Results 4.6
Exposed to Contaminants 4.5
Work Outcomes and Results of Other Workers 4.4
In an Open Vehicle or Operating Equipment 4.3
Health and Safety of Other Workers 4.3
Spend Time Making Repetitive Motions 4.2
Determine Tasks, Priorities and Goals 4.2
Telephone Conversations 4.1
Work With or Contribute to a Work Group or Team 4.0
Time Pressure 4.0
In an Enclosed Vehicle or Operate Enclosed Equipment 4.0
Freedom to Make Decisions 4.0
Pace Determined by Speed of Equipment 4.0
Exposed to Whole Body Vibration 3.9
Importance of Being Exact or Accurate 3.9
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 3.8
Physical Proximity 3.8
Exposed to Very Hot or Cold Temperatures 3.6
Coordinate or Lead Others in Accomplishing Work Activities 3.5
Deal With External Customers or the Public in General 3.5
Exposed to Minor Burns, Cuts, Bites, or Stings 3.4
Spend Time Sitting 3.2
Indoors, Not Environmentally Controlled 3.1
Spend Time Bending or Twisting Your Body 3.1
Level of Competition 2.9
Exposed to Extremely Bright or Inadequate Lighting Conditions 2.9
Dealing With Unpleasant, Angry, or Discourteous People 2.8
Conflict Situations 2.8
Spend Time Standing 2.8
Exposed to Hazardous Conditions 2.7
Wear Specialized Protective or Safety Equipment such as Breathing Apparatus, Safety Harness, Full Protection Suits, or Radiation Protection 2.6
Outdoors, Under Cover 2.4

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.

Less than a High School Diploma 1.4%
Post-Secondary Certificate 0.6%

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 3.9
Investigative 2.9

Interest areas

Transportation/Machine Operation 6.5
Physical/Manual Labor 5.1
Mechanics/Electronics 3.7
Engineering 3.6
Construction/Woodwork 2.5
Nature/Outdoors 2.2
Management/Administration 1.3

Work styles

Cautiousness 2.5
Dependability 2.4
Stress Tolerance 1.8
Perseverance 1.6
Integrity 1.5
Attention to Detail 1.5

Wages & employment

U.S. · annual wages (BLS OEWS)

$40k10th$48k25th$59kMedian$76k75th$101k90th
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.
489k2024507k2034 (proj.)+3.6% · About average
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $40,080
25th percentile $47,780
Median (50th) $58,710
75th percentile $75,750
90th percentile $100,690
People employed 469,270

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
Construction · Sector 295,700 $60,950
Mining, Quarrying, and Oil and Gas Extraction · Sector 26,430 $57,840
Administrative and Support and Waste Management and Remediation Services · Sector 25,950 $51,080
Power and Communication Line and Related Structures Construction · National industry 16,380 $59,840
Manufacturing · Sector 9,760 $51,950
Wholesale Trade · Sector 7,780 $47,260
Poured Concrete Foundation and Structure Contractors · National industry 7,770 $71,520
Transportation and Warehousing · Sector 6,090 $53,930
Temporary Help Services · National industry 5,020 $44,630
Landscaping Services · National industry 5,020 $52,650
Utilities · Sector 4,020 $81,040
Electrical Contractors and Other Wiring Installation Contractors · National industry 3,500 $65,890

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
Power and Communication Line and Related Structures Construction · National industry 22.98× 16,380
Mining, Quarrying, and Oil and Gas Extraction · Sector 15.14× 26,430
Construction · Sector 11.96× 295,700
Poured Concrete Foundation and Structure Contractors · National industry 9.87× 7,770
Solar Electric Power Generation · National industry 6.59× 280
Fossil Fuel Electric Power Generation · National industry 3.18× 690
Masonry Contractors · National industry 2.7× 1,180
Utilities · Sector 2.28× 4,020

Part of the Construction career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Operating Engineers and Other Construction Equipment Operators sits at the 17th percentile of AI task-overlap and the 44th 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 Operating Engineers and Other Construction Equipment Operators Helpers--Extraction Workers Pile Driver Operators Paving, Surfacing, and Tamping Equipment Operators Industrial Truck and Tractor Operators Continuous Mining Machine Operators 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 Operating Engineers and Other Construction Equipment Operators — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Skills that travel

Capabilities this work builds that are used across many other occupations.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 11th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Operating Engineers and Other Construction Equipment Operators show 17th-percentile AI task overlap — and about 41,900 annual U.S. openings

  • Operating Engineers and Other Construction Equipment Operators rank in the 17th 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 41,900 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 about average (+3.6%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $58,710, across about 469,270 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Operating Engineers and Other Construction Equipment Operators show 17th-percentile AI task overlap — and about 41,900 annual U.S. openings

• Operating Engineers and Other Construction Equipment Operators rank in the 17th 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 41,900 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 about average (+3.6%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $58,710, across about 469,270 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Operating Engineers and Other Construction Equipment Operators". https://singulariki.com/roles/role-47-2073-00
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. "Operating Engineers and Other Construction Equipment Operators." 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; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-47-2073-00

APA

Singulariki. (2026). Operating Engineers and Other Construction Equipment Operators. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-47-2073-00

BibTeX
@misc{singulariki-role-47-2073-00,
  title  = {Operating Engineers and Other Construction Equipment Operators},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-47-2073-00}
}

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

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