Somewhat Resilient

Last Update: 6/19/2026

AI Resilience Score for Highway Maint. Workers:

49.7%

Median Score

Meaningful human contribution

High

Long-term employer demand

Med

Sustained economic opportunity

Low

Our confidence in this score:
Medium

Contributing sources

Methodology and Scoring Rationale

To score how resilient highway maintenance work is to AI, we ask one question in three parts:

First, how much of the job still needs a human, read from four AI-exposure sources: our own AI Resilience Model, Anthropic's Observed Exposure, Microsoft's AI Applicability, and Will Robots Take My Job. We call this dimension Meaningful Human Contribution (MHC) and weight it at 40%.

Next, whether employers will keep hiring for this job over the long term. This dimension, which we call Long-term Employer Demand (LTE), is calculated from BLS data and weighted at 30%.

Last, whether pay and mobility will hold up. We use wage bill and adaptive capacity data from independent researchers (Althoff & Reichardt, 2026; Manning & Aguirre, 2026). We call this dimension Sustained Economic Opportunity (SEO) and weight it at 30%.

For highway maintenance workers, six of seven sources had data (only Anthropic was missing), which pulls confidence to medium. On AI exposure, AI Resilience Model and Microsoft both rated it low, while Will Robots Take My Job rated it medium, a mild split. Strong human contribution kept the score up, but low pay and mobility signals dragged it down, landing this role at "Somewhat Resilient."

AI Resilience Report forHighway Maintenance Workers

$49,070 median salary12,300 annual openingsSOC Code: 47-4051.00

Highway Maintenance Workers are somewhat less resilient to AI impacts than most occupations, according to our analysis of 6 sources.

Highway maintenance is "Somewhat Resilient" because AI is genuinely changing how this work gets done, even if it is not eliminating the jobs themselves. Tools like AI-powered pothole detection and smarter equipment are taking over the inspection and routing tasks that workers used to handle manually, which means the job is shifting toward more hands-on, physical work like actually patching pavement, operating heavy machinery, and managing traffic control in real conditions.

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This role is somewhat resilient

Highway maintenance is "Somewhat Resilient" because AI is genuinely changing how this work gets done, even if it is not eliminating the jobs themselves. Tools like AI-powered pothole detection and smarter equipment are taking over the inspection and routing tasks that workers used to handle manually, which means the job is shifting toward more hands-on, physical work like actually patching pavement, operating heavy machinery, and managing traffic control in real conditions.

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Analysis of Current AI Resilience

Highway Maint. Workers

Updated Quarterly

Analysis
Suggested Actions
State of Automation

How is AI changing Highway Maint. Workers jobs?

Good news first: highway maintenance is one of those hands-on jobs where AI is mostly helping workers, not replacing them. Most of the action right now is in detection and inspection — letting computers spot problems faster so crews know where to go. For example, fleet management company Samsara has trained an AI model called "Ground Intelligence" that uses cameras on millions of trucks to detect multiple types of potholes and gauge how fast they are deteriorating, and the city of Chicago recently signed on as a customer (TechCrunch [1]).

Researchers at Purdue have built a similar system called PaveX where, in pilots across Indiana, the AI yielded pavement condition results within ±5 points of an experienced human evaluator while avoiding individual subjectivity across inspections (ASCE Civil Engineering [2]). On the repair side, equipment is getting smarter too — a new Cimline spray-injection pothole truck [3] lets a single operator patch a hole in two minutes using joystick controls from inside the cab. The Transportation Research Board's Autonomous Maintenance Technologies Phase 2 program [4] is also expanding research into autonomous crack sealing, mowing, and snow plowing, all aimed at improving worker safety and addressing workforce shortages.

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AI Adoption

How fast is AI adoption growing for Highway Maint. Workers?

Adoption is moving steadily but carefully. A national AASHTO survey of 50+ state DOTs [5] found that the biggest challenges to AI deployment are data quality (76%), security (69%), and reliability (61%), with workforce skills gaps (56%) and implementation costs (47%) also slowing progress. Importantly, agencies are framing AI as augmentation, not replacement: a Delaware DOT official noted that many fear AI will eliminate jobs, but he believes it will instead allow state DOT workforces to become more productive.

The big push is on safety — Roads & Bridges reports [6] that AI is helping turn individual smart work zones into coordinated, system-wide safety strategies that warn drivers and protect crews. The skills that stay valuable are exactly the human ones: physically patching pavement, operating heavy equipment in messy weather, judging unsafe conditions on a real worksite, and setting up traffic control around live traffic. AI can find the pothole and route the truck — but a person still has to fill it.

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Will AI replace Highway Maint. Workers?

Will AI replace Highway Maint. Workers?

Not entirely. We think AI will take over some tasks, but not the whole job.

Highway maintenance sits at a 49.7% AI Resilience Score, which tells you this career is changing in real ways, but it is far from disappearing. Right now, AI is mostly handling detection and inspection work: systems like Samsara's "Ground Intelligence" use cameras on trucks to spot potholes and track how fast they are getting worse [1], while research tools can evaluate pavement condition close to what an experienced human inspector would find [2]. That frees up crews to focus on actual repairs rather than scouting for problems.

The physical work stays human. Patching pavement, operating heavy equipment in bad weather, reading a dangerous worksite in real time, and setting up traffic control around live traffic are all things AI cannot reliably do yet. A national survey of state DOTs found agencies are framing AI as a productivity tool, not a replacement, with one official saying it will help workforces become more productive rather than smaller [5].

The honest caveat is that wages and career flexibility in this field are under real pressure, so the economic picture is tighter than the job security picture. The role is evolving, and workers who get comfortable with smarter equipment and data tools will be better positioned than those who do not.

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Latest AI news for Highway Maint. Workers

These articles highlight how AI is transforming the highway maintenance sector, offering both challenges and opportunities for future workers. For instance, Amey's integration of FYLD's AI technology aims to enhance maintenance workflows, suggesting a future where tech-savvy workers will be in demand. Additionally, the partnership between Honda and the Ohio Department of Transportation shows that AI can improve road safety through better hazard detection. Embracing AI can help highway maintenance workers adapt and thrive in an evolving job landscape, fostering resilience in their careers.

More Career Info

Career: Highway Maintenance Workers

They keep roads safe and smooth by fixing potholes, clearing debris, and painting road lines.

Employment & Wage Data

Median Wage

$49,070

Jobs (2024)

159,100

Growth (2024-34)

+3.0%

Annual Openings

12,300

Education

High school diploma or equivalent

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2024-2034

Task-Level AI Resilience Scores

AI-generated estimates of task resilience over the next 3 years

1

92% ResilienceCore Task

Flag motorists to warn them of obstacles or repair work ahead.

2

91% ResilienceCore Task

Erect, install, or repair guardrails, road shoulders, berms, highway markers, warning signals, and highway lighting, using hand tools and power tools.

3

90% ResilienceCore Task

Dump, spread, and tamp asphalt, using pneumatic tampers, to repair joints and patch broken pavement.

4

90% ResilienceCore Task

Haul and spread sand, gravel, and clay to fill washouts and repair road shoulders.

5

89% ResilienceCore Task

Remove litter and debris from roadways, including debris from rock and mud slides.

6

88% ResilienceCore Task

Set out signs and cones around work areas to divert traffic.

7

88% ResilienceCore Task

Perform preventative maintenance on vehicles and heavy equipment.

Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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