Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Highway Maintenance Workers
Occupation · SOC 47-4051.00
Maintain highways, municipal and rural roads, airport runways, and rights-of-way. Duties include patching broken or eroded pavement and repairing guard rails, highway markers, and snow fences. May also mow or clear brush from along road, or plow snow from roadway.
Also called: Equipment Operator (EO) · Highway Maintainer · Highway Maintenance Worker · Transportation Maintenance Specialist (TMS) · Highway Maintenance Crew Worker · Highway Maintenance Technician · Maintenance Technician · Maintenance Worker · Transportation Maintenance Operator · Transportation Worker · Asphalt Raker · Caltrans Equipment Operator
Job family: Construction and Extraction Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-47-4051-00/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.
Market signal
Independent published positions, read together — not a forecast.
- About average employment outlook (+3.0% by 2034)
- 12,300 openings/yr
- Low AI exposure
- Median pay $49,070/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (74th); today's AI task-overlap is comparatively low (3rd)
3rd-percentile task overlap — yet about 12,300 openings a year (+3% 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 | 9th | -1.3 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 6th | 0.0 | |
| AI assistant applicability (Microsoft) Low | 3rd | 0.0 |
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.
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 · 74th 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 · +3.0% by 2034 |
| Projected annual openings | 12,300 |
| Employment 2024 → 2034 | 159,100 → 163,900 |
“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.
Highway Maintenance Workers sits at the 2nd percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
9% mean task exposure (2025)
2nd percentile of 427 placed occupations
−1 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Civil Engineering Labourers · 9312 | 9% | 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 19 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Set out signs and cones around work areas to divert traffic. Core · importance 4.5
- Flag motorists to warn them of obstacles or repair work ahead. Core · importance 4.4
- Perform preventative maintenance on vehicles and heavy equipment. Core · importance 4.3
- Drive trucks to transport crews and equipment to work sites. Core · importance 4.3
- Erect, install, or repair guardrails, road shoulders, berms, highway markers, warning signals, and highway lighting, using hand tools and power tools. Core · importance 4.2
- Clean and clear debris from culverts, catch basins, drop inlets, ditches, and other drain structures. Core · importance 4.2
- Drive heavy equipment and vehicles with adjustable attachments to sweep debris from paved surfaces, mow grass and weeds, remove snow and ice, and spread salt and sand. Core · importance 4.1
- Haul and spread sand, gravel, and clay to fill washouts and repair road shoulders. Core · importance 4.1
- Inspect, clean, and repair drainage systems, bridges, tunnels, and other structures. Core · importance 4.0
- Remove litter and debris from roadways, including debris from rock and mud slides. Core · importance 4.0
- Dump, spread, and tamp asphalt, using pneumatic tampers, to repair joints and patch broken pavement. Core · importance 4.0
- Apply poisons along roadsides and in animal burrows to eliminate unwanted roadside vegetation and rodents. Supplemental · importance 3.8
- Measure and mark locations for installation of markers, using tape, string, or chalk. Supplemental · importance 3.7
- Paint traffic control lines and place pavement traffic messages, by hand or using machines. Supplemental · importance 3.6
- Perform roadside landscaping work, such as clearing weeds and brush, and planting and trimming trees. Core · importance 3.6
- Apply oil to road surfaces, using sprayers. Supplemental · importance 3.5
- Inspect markers to verify accurate installation. Supplemental · importance 3.4
- Place and remove snow fences used to prevent the accumulation of drifting snow on highways. Supplemental · importance 3.3
- Blend compounds to form adhesive mixtures used for marker installation. Supplemental · importance 2.9
Work activities
- Maintain mechanical equipment.
- Operate equipment or vehicles to clear construction sites or move materials.
- Direct vehicle traffic.
- Pour materials into or on designated areas.
- Compact materials to create level bases.
- Spread concrete or other aggregate mixtures.
- Drive trucks or truck-mounted equipment.
- Inspect industrial or commercial equipment to ensure proper operation.
- Clean equipment or facilities.
- Maintain plumbing structures or fixtures.
- Spread sand, dirt or other loose materials onto surfaces.
- Move construction or extraction materials to locations where they are needed.
- Install fencing or other barriers.
- Remove debris or vegetation from work sites.
- Apply paint to surfaces.
- Inspect completed work to ensure proper installation.
- Treat greenery or surfaces with protective substances.
- Measure work site dimensions.
- Mark reference points on construction materials.
- Operate road-surfacing equipment.
- Mix substances or compounds needed for work activities.
- Dismantle equipment or temporary structures.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Public Safety and Security | 4.2 | |
| English Language | 3.5 | |
| Transportation | 3.3 | |
| Building and Construction | 3.2 | |
| Education and Training | 3.0 | |
| Administration and Management | 3.0 |
Abilities
| Control Precision | 3.9 | |
| Multilimb Coordination | 3.9 | |
| Oral Comprehension | 3.4 | |
| Problem Sensitivity | 3.4 | |
| Arm-Hand Steadiness | 3.4 | |
| Static Strength | 3.4 | |
| Manual Dexterity | 3.3 | |
| Near Vision | 3.3 | |
| Auditory Attention | 3.3 | |
| Oral Expression | 3.1 | |
| Information Ordering | 3.1 | |
| Flexibility of Closure | 3.1 | |
| Visualization | 3.1 | |
| Selective Attention | 3.1 | |
| Finger Dexterity | 3.1 | |
| Response Orientation | 3.1 | |
| Reaction Time | 3.1 | |
| Trunk Strength | 3.1 | |
| Stamina | 3.1 | |
| Extent Flexibility | 3.1 | |
| Far Vision | 3.1 | |
| Deductive Reasoning | 3.0 | |
| Inductive Reasoning | 3.0 | |
| Category Flexibility | 3.0 | |
| Perceptual Speed | 3.0 | |
| Time Sharing | 3.0 | |
| Rate Control | 3.0 |
Transferable skills
| Operation and Control | 3.6 | |
| Operations Monitoring | 3.5 | |
| Coordination | 3.1 | |
| Complex Problem Solving | 3.0 |
Essential skills
| Monitoring | 3.1 | |
| Active Listening | 3.0 | |
| Speaking | 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 Word | Word processing software | Hot technology |
| Database software | Data base user interface and query software | |
| Web browser software | Internet browser 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.
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 | 88.3% | |
| Less than a High School Diploma | 5.2% | |
| Associate's Degree (or other 2-year degree) | 5.1% | |
| Post-Secondary Certificate | 1.4% |
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 | |
| Social | 1.8 | |
| Investigative | 1.7 | |
| Enterprising | 1.5 |
Interest areas
| Physical/Manual Labor | 6.7 | |
| Transportation/Machine Operation | 6.2 | |
| Nature/Outdoors | 2.8 | |
| Mechanics/Electronics | 2.8 | |
| Construction/Woodwork | 2.3 | |
| Engineering | 1.9 | |
| Protective Service | 1.4 |
Work styles
| Dependability | 2.5 | |
| Cautiousness | 1.8 | |
| Attention to Detail | 1.5 | |
| Perseverance | 1.5 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $35,030 |
| 25th percentile | $41,540 |
| Median (50th) | $49,070 |
| 75th percentile | $59,600 |
| 90th percentile | $69,210 |
| People employed | 151,750 |
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 | 5,210 | $45,650 |
| Temporary Help Services · National industry | 380 | $33,280 |
| Transportation and Warehousing · Sector | — | $45,230 |
| Real Estate and Rental and Leasing · Sector | — | $59,960 |
| Administrative and Support and Waste Management and Remediation Services · Sector | — | $36,030 |
| Other Services (except Public Administration) · Sector | — | $44,890 |
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 |
|---|---|---|
| Construction · Sector | 0.65× | 5,210 |
| Temporary Help Services · National industry | 0.15× | 380 |
Related occupations
Part of the Construction and Supply Chain & Transportation career clusters.
- Operating Engineers and Other Construction Equipment Operators · 47-2073.00 Compare →
- Paving, Surfacing, and Tamping Equipment Operators · 47-2071.00 Compare →
- Rail-Track Laying and Maintenance Equipment Operators · 47-4061.00 Compare →
- Pile Driver Operators · 47-2072.00 Compare →
- Septic Tank Servicers and Sewer Pipe Cleaners · 47-4071.00 Compare →
- Construction Laborers · 47-2061.00 Compare →
- Maintenance and Repair Workers, General · 49-9071.00 Compare →
- Excavating and Loading Machine and Dragline Operators, Surface Mining · 47-5022.00 Compare →
- Industrial Truck and Tractor Operators · 53-7051.00 Compare →
- Helpers--Extraction Workers · 47-5081.00 Compare →
- Hazardous Materials Removal Workers · 47-4041.00 Compare →
- Transportation Engineers · 17-2051.01 Compare →
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 Highway Maintenance Workers — 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.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
Paths in
How people typically prepare for this work.
- High school diploma or equivalent · typical entry level
- Job zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
- Transportation and Materials Moving · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 2nd percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Highway Maintenance Workers show 3rd-percentile AI task overlap — and about 12,300 annual U.S. openings
- Highway Maintenance Workers rank in the 3rd 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 12,300 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%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $49,070, across about 151,750 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Highway Maintenance Workers show 3rd-percentile AI task overlap — and about 12,300 annual U.S. openings • Highway Maintenance Workers rank in the 3rd 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 12,300 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%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $49,070, across about 151,750 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Highway Maintenance Workers". https://singulariki.com/roles/role-47-4051-00 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.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Highway Maintenance Workers." 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-47-4051-00
APA
Singulariki. (2026). Highway Maintenance Workers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-47-4051-00
BibTeX
@misc{singulariki-role-47-4051-00,
title = {Highway Maintenance Workers},
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-47-4051-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.