AI Career Risk For Highway Maintenance Workers

Will AI Replace Highway Maintenance Workers in 2026?

Also known as: Road Maintenance Worker, DOT Worker, Highway Worker, Road Crew Worker.

Highway maintenance workers repair and maintain roads and highways. AI absorbs nothing material in the hands-on work; the durable work is the in-person physically demanding skilled work, the on-site safety judgment, and the role within the infrastructure-maintenance chain.

Exposure ScoreLow Exposure
35/ 100
Rank: 30 of 62 in Skilled Trades & Manual LaborCategory avg: 30/100All roles avg: 39/100
This is the role's AI exposure (0 to 100, lower is safer), not your personal AI Career Index (0 to 1000). Get your own score.
Median pay: $50,260 / yr· BLS OEWS, May 2025 · occupational category
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At a Glance

Highway Maintenance Workers at a glance

A quick read on Highway Maintenance Workers: the AI risk band, where the role sits inside Skilled Trades & Manual Labor, and the headline numbers worth knowing before reading more.

Role Overview

How AI is reshaping Highway Maintenance Workers

Highway Maintenance Workers do the physical road and infrastructure maintenance work at state Departments of Transportation, county road agencies, and municipal public works: pothole repair, snowplow operation, mowing right-of-way, traffic-control setup, bridge maintenance, and the seasonal work that keeps roads operating. Equipment is increasingly AI-augmented (autonomous snowplow assist, AI-driven pavement-condition monitoring), but the physical work remains entirely human. The migration path runs into highway maintenance supervisor, equipment operator specialty, or DOT field-management roles where wages step up.

The work depends on accountability, licensure, complex judgment, or being physically present in ways AI tools cannot match. AI is absorbing the layers around the role, the coordination, the paperwork, the reporting, and that tends to make the role more valuable, not less.

The reading below covers the specific AI exposure rating for Highway Maintenance Workers, the tasks AI can already do today, the authority band the role typically operates at, and a six-month plan tied to where the role actually sits. Same framework used for every role in the index.

Exposure Profile

AI exposure profile for Highway Maintenance Workers

How Highway Maintenance Workers stack up against other roles. How much of the work AI can speed up, how much stays with people, and where the role sits compared to the Skilled Trades & Manual Labor average.

Exposure Score
35OUT OF 100
Ranks 30 of 62 in the Skilled Trades & Manual Labor category, above the category average
How this role compares
Highway Maintenance Workers35
Category average30
All roles average39
Where AI reaches this role's tasks
AI can do directly0%(halves the time)
AI with tools2%(with software built on AI)
Stays with people98%(no real speed-up)

Share of this occupation's O*NET tasks where AI can cut the time by at least half. Source: Eloundou et al., "GPTs are GPTs", Science (2024).

Exposure trajectory
Rising

Rising: robots can already do about 79% of this role's working time, at least in settings built for them.

Direction from research on AI (Science, 2024) and robots (Anthropic, 2026); 0% of this role's work already shows real AI use (Anthropic Economic Index). The line's shape is illustrative, not a measured year-by-year series.

202420252026 (now)2027
Career Simulator

What moves the score for Highway Maintenance Workers?

This starts from a typical profile for a low exposure role. Drag any of the five dimensions to see how a structural shift would move the AI Career Index, using the exact weighting behind every reading on the site.

The AI Career Index (0 to 1000) measures your personal structural positioning. It is a different measure from this role's AI exposure score (0 to 100) shown above, which rates the role itself.

Career Simulator

Model the impact of structural shifts

A typical starting profile for highway maintenance workers. Move any dimension to model the impact on the AI Career Index.

AI Career Index
714/1000
Tier
AI Competitive Professional
Authority band: Strategic
01000
Strategic Clarity· 25%72Advanced
AI Adaptability· 20%70Advanced
Income Leverage· 20%68Transitional
Skill Resilience· 20%74Advanced
Market Alignment· 15%73Advanced
This is a model. Run the real reading to simulate on your own scores.Run my real reading

This simulator applies the same dimension weighting used in your structural reading to estimate directional movement. It does not alter any stored assessment. Actual outcomes depend on implementation quality, sequencing, and market conditions.

Open the full Career Simulator to model all five dimensions from scratch, or see how the score is built in the structural framework.

Key Takeaways

Quick read on Highway Maintenance Workers

The short version on Highway Maintenance Workers: AI exposure, how much of the role AI can already do, what stays valuable, and the move worth making in the next six months. A quick summary before the deeper read.

Real-world signal

How AI is being used by Highway Maintenance Workers today

Two figures for Highway Maintenance Workers that sit outside our scoring framework. The adoption figure shows how much of the day-to-day work done by Highway Maintenance Workers is already being absorbed by AI tools in the wild. The economic impact figure gives the macro stakes attached to the role at a national level.

AI adoption among Highway Maintenance Workers
< 0.1%
(None observed)

Share of the work done by Highway Maintenance Workers already showing real-world AI usage today, sourced from the Anthropic Economic Index (MIT licence). A 0% reading means the dataset observed no measurable usage for this occupation in its sample, not that AI cannot apply to the role.

Economic impact
$7.79B

Total US economic value generated by Highway Maintenance Workers: median annual wage multiplied by total US employment, both from BLS OEWS.

24-Month Trajectory

Where Highway Maintenance Workers are heading by 2028

Where Highway Maintenance Workers sit today and where the role is heading over the next two years. We don't predict an exact future score. The direction is what the data already shows. If you're in this role or considering it, this is the direction worth planning around.

Today
35/100
Low Exposure
→ ↑
Appreciating
In 24 months · By 2028
Holds and gains value
AI takes care of routine work around this role. The core skills stay in demand and tend to get more valuable, not less.
Category outlook

Over the next two years, demand for Highway Maintenance Workers stays strong and in many regions intensifies. The existing trades workforce is aging out faster than new entrants come in, and AI has not narrowed the gap. The shift is administrative: more AI dispatch, more digital service records, more AI-assisted parts and quoting workflows. Highway Maintenance Workers who absorb these tools and use the reclaimed time on jobs (or apprentice supervision) earn more.

What AI Can Do

What AI can and can't do for Highway Maintenance Workers

The work AI can take over today versus the work it cannot. Where Highway Maintenance Workers spend their time on this split largely decides whether the role grows or shrinks over the next two years.

Deprioritise

Stop investing in these

  • Customer communication and appointment reminders
  • Standard estimating from quantity templates
  • Parts inventory reconciliation and reorder suggestions
  • Routine maintenance scheduling and dispatch optimisation
Stays human

Structurally insulated

  • Physical dexterity in confined, hazardous, or live-system environments
  • Licensure-bearing trade work and code-compliant installations
  • Tool, equipment, and material selection for non-standard jobs
  • Customer trust built on repeat-visit reliability
AI Tools

AI tools currently affecting Highway Maintenance Workers

The tools actually reshaping Highway Maintenance Workers work in 2026. Each one takes over a slice of the routine work; staying valuable means owning the work that sits above them.

ServiceTitan
AI dispatch, scheduling, and CRM platform widely used across electrical, plumbing, and HVAC contractors.
Jobber
Field-service management with AI-assisted scheduling, quoting, and customer communication.
Housecall Pro
AI scheduling and dispatch for home-service trades plus voice-driven invoice generation.
BuildOps
Commercial-trades platform with AI optimisation for service operations and field productivity.
FieldEdge
AI-augmented work-order management and dispatch optimisation for trade service businesses.
Workiz
AI-driven scheduling, lead routing, and quote generation for small-trade businesses.

Tool list is editorial, not exhaustive. Listing does not imply endorsement. Updated Methodology v3 · 2026.

Structural Reading

Where Highway Maintenance Workers sit structurally

Where AI is hitting the work, where it cannot reach, where Highway Maintenance Workers are heading over the next two years, and what stays durable. The cards below address each question; the per-role reading underneath them grounds the answers in this role's actual tasks and knowledge layers.

Will AI Replace

Will AI Replace Highway Maintenance Workers?

AI will not replace Highway Maintenance Workers. The work depends on physical presence, on-site judgment, licensure, and dexterity in environments AI cannot enter. Compression in the trade is concentrated on the office and admin layer: scheduling, dispatching, estimating, customer communication, and documentation. The field work itself remains the most durable knowledge work on the index.

Automation Risk

Automation Risk for Highway Maintenance Workers

Highway Maintenance Workers face concentrated automation pressure on the back-office layer. AI dispatch tools, route-optimisation software, voice-driven service reports, and automated estimating compress the time spent on admin. The risk does not extend to the field work, which is protected by physical presence, code-compliance requirements, and the on-site judgment that defines the trade. The wage growth here often comes from time reclaimed on admin and reinvested in billable jobs.

Career Outlook

AI Career Outlook for Highway Maintenance Workers

Over the next two years, demand for Highway Maintenance Workers stays strong and in many regions intensifies. The existing trades workforce is aging out faster than new entrants come in, and AI has not narrowed the gap. The shift is administrative: more AI dispatch, more digital service records, more AI-assisted parts and quoting workflows. Highway Maintenance Workers who absorb these tools and use the reclaimed time on jobs (or apprentice supervision) earn more.

Stay Relevant

How Highway Maintenance Workers Stay Relevant

Highway Maintenance Workers stay relevant by adopting the AI tools that compress the admin side of the trade (digital dispatch, automated invoicing, AI-assisted estimating) so the field hours are spent earning, not on paperwork. Pursue advanced licensure, specialty certifications, and crew-leadership roles where the wage band is highest. Mentor apprentices to entrench your value at the shop level. The role is durable; positioning above the entry tier is where the wage growth lives.

Inside the Work

A typical week as a Highway Maintenance Worker

What the work looks like in practice: meetings, deliverables, tools, and the decisions that get escalated. Useful context for anyone weighing this role against the AI-exposure reading above.

Week-in-the-life
Authored by editorial · Highway Maintenance Worker
MonTueWedThuFri

A typical week for a highway maintenance worker runs at state DOT, county road agencies, or municipal public works on shift schedules including winter snow operations. Most days are 8-10 hour shifts of physical outdoor work: pothole repair, road striping, mowing right-of-way, brush clearing, traffic control setup at work zones, snowplow operation (winter), bridge maintenance, and the seasonal work that keeps roads operating. Equipment is increasingly AI-augmented but the physical work remains entirely human. The migration path runs into highway maintenance supervisor, equipment operator specialty, or DOT field-management roles.

Compression and Durability

Where Highway Maintenance Workers compress, and where they hold

A role-specific reading grounded in Highway Maintenance Workers's actual O*NET tasks and knowledge layers. The paragraph below is the structural reading; the two columns name the specific layers where compression is hitting and where the work holds.

Structural reading

What holds for Highway Maintenance Workers is the layer of work that requires public safety and security under conditions where outdoors, exposed to all weather conditions matters. AI absorbs set out signs and cones around work areas to divert traffic and the production around it. It cannot absorb the judgment that frames it. The role appreciates as the surrounding production layer compresses across skilled trades & manual labor.

Where compression is hitting
  • Set out signs and cones around work areas to divert traffic is the production-layer task AI tools speed up; the durability of the role isn't anchored here, so the speedup is a net gain.
  • Flag motorists to warn them of obstacles or repair work ahead runs through AI assistance now, which compresses the time cost of the task without compressing the role itself.
  • Perform preventative maintenance on vehicles and heavy equipment is augmented rather than absorbed by AI; the work runs faster but the human still has to be in the room.
Where the role holds
  • Public Safety and Security compounds with experience. AI-assisted highway maintenance workers working at this layer get faster without the role being absorbed.
  • English Language is the part of the work that signals authority. Visible, hard to template, and increasingly the only durable position.
  • Transportation is the layer where accountability lands. AI augments around it but cannot bear the decision.
Salary & Occupation Data

Salary and occupational data for Highway Maintenance Workers

Median annual wage, common task statements, and alternate titles drawn from O*NET 30.2 (USDOL/ETA, CC BY 4.0) · Wages: BLS OEWS May 2025. BLS reports median wages at the occupational category level, so highway maintenance workers and related roles that map to the same category share the same source wage. The descriptive occupational data below sits alongside the structural reading; the AI exposure score above is independent of it.

Occupation Snapshot · Highway Maintenance Workers
O*NET-SOC 47-4051.00
Median annual wage
$50,260
BLS OEWS · May 2025
Junior
$43,500
Senior
$61,040
Common task statements (O*NET)
  • Set out signs and cones around work areas to divert traffic.
  • Flag motorists to warn them of obstacles or repair work ahead.
  • Perform preventative maintenance on vehicles and heavy equipment.
  • Drive trucks to transport crews and equipment to work sites.
  • Erect, install, or repair guardrails, road shoulders, berms, highway markers, warning signals, and highway lighting, using hand tools and power tools.
Knowledge domains (O*NET importance, 1–5)
  • Public Safety and Security4.2
  • English Language3.5
  • Transportation3.3
  • Building and Construction3.2
  • Administration and Management3.0
Work context (importance, 1–5)
  • Outdoors, Exposed to All Weather Conditions4.9
  • Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets4.9
  • Face-to-Face Discussions with Individuals and Within Teams4.8
  • Exposed to Contaminants4.7
  • Work With or Contribute to a Work Group or Team4.6
Preparation level
Job Zone 2· Some preparation
Tools and equipment (O*NET)
10-ton crawlers10-ton tandem-axle dump trucks13000-23000 pound graders30-ton clam buckets4-6 ton roller patchers8-ton dump trucksAdjustable widemouth pliersAdjustable wrenches
Source: O*NET 30.2 (USDOL/ETA, CC BY 4.0) · Wages: BLS OEWS May 2025 · Descriptive occupational data; the AI exposure reading is independent.
Reviewed by AI Career Index Research · Methodology v3 · 2026 ·Read the methodology →
Common Feeders

Roles commonly transitioning into Highway Maintenance Workers.

These skilled trades & manual labor roles are under more pressure than Highway Maintenance Workers, and people often path out of them into a seat like yours. If you work in one of these today, Highway Maintenance Workers is the kind of role most worth moving toward.

6-Month Action Plan

Six concrete moves for Highway Maintenance Workers over the next six months

Highway Maintenance Workers are structurally insulated within skilled trades & manual labor, but the coordination layer around the role is being absorbed by AI tooling. The six moves below help you reclaim hours from that layer and reinvest them in the licensed and judgment-heavy work that compounds. Each move is one month, with a week-by-week sprint inside. The downloadable PDF adds end-of-month reflection prompts in a print-friendly format.

Go deeper

Take the plan with you

The downloadable PDF gives you the full plan in a print-friendly format you can keep at your desk and check against month by month. Take the AI Career Assessment to get a plan tailored to your specific situation.

FAQ

Common questions about Highway Maintenance Workers and AI

The reading above answers the headline question. These FAQs cover the follow-up questions Highway Maintenance Workers typically ask: wage benchmarks, the tasks most at risk, the skills that stay valuable, and the six-month plan for this role.

Further Reading

Articles relevant to Highway Maintenance Workers

Hand-picked AI Career Index articles on the shifts affecting Highway Maintenance Workers and nearby roles. Useful next reads for the broader context behind the reading on this page.

Testimonials

What Professionals Are Saying

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"As a CFO I assumed my job was safe from AI. The report gently disagreed. It showed that the routine modelling and reporting in my week is the part AI can take over, while the board and governance work is the part that stays valuable. I shifted about a fifth of my time toward that work, and I can already feel the difference."

Oluwaseun Adeyemi
Chief Financial Officer · Lagos, Nigeria

"My skills scored well, but my earning potential scored low. That is the classic sign of a strong operator who is underpaid. The report pointed to the single change that would lift my earning potential the most. I made it, and it worked."

Noah Kimura
Head of Growth · Auckland, New Zealand

"The report placed me in the senior strategic group and showed that my pay was trailing what that level usually earns. I took that into my pay review. The conversation was short and productive, and the numbers did the convincing."

Amira El-Hassan
Principal Product Manager · Dubai, UAE

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