Mostly Resilient

Last Update: 6/19/2026

AI Resilience Score for Maintenance and Repair Worker:

60.9%

Median Score

Meaningful human contribution

High

Long-term employer demand

High

Sustained economic opportunity

Low

Our confidence in this score:
Medium-high

Contributing sources

Methodology and Scoring Rationale

To score how resilient maintenance and repair 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 maintenance and repair workers, six of seven sources had data (Anthropic had none) and mostly agreed: AI Resilience Model and Microsoft both rated AI exposure as low, while Will Robots Take My Job rated it medium, nudging confidence to medium-high. Strong hiring outlook lifted the score, but weak pay and mobility signals kept it at "Mostly Resilient."

AI Resilience Report forMaintenance and Repair Workers, General

$48,620 median salary159,800 annual openingsSOC Code: 49-9071.00

Maintenance and Repair Workers, General are somewhat more resilient to AI impacts than most occupations, according to our analysis of 6 sources.

Maintenance and repair work is labeled "Mostly Resilient" because the physical, hands-on parts of the job (climbing into mechanical rooms, dismantling equipment, welding, and diagnosing problems on the spot) still require human skill and judgment that AI simply cannot replicate. AI tools are changing the paperwork and planning side of things, helping with scheduling, work orders, and predicting when equipment might fail, but those tools are meant to support technicians, not replace them.

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This role is mostly resilient

Maintenance and repair work is labeled "Mostly Resilient" because the physical, hands-on parts of the job (climbing into mechanical rooms, dismantling equipment, welding, and diagnosing problems on the spot) still require human skill and judgment that AI simply cannot replicate. AI tools are changing the paperwork and planning side of things, helping with scheduling, work orders, and predicting when equipment might fail, but those tools are meant to support technicians, not replace them.

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Analysis of Current AI Resilience

Maintenance and Repair Worker

Updated Quarterly

Analysis
Suggested Actions
State of Automation

How is AI changing Maintenance and Repair Worker jobs?

If you're worried that robots are about to take over building maintenance, take a breath — the picture in 2026 looks much more like teamwork than replacement. The Building Service Contractors Association International argues that AI isn't here to take the place of the people who clean buildings, care for spaces, and show up night after night — it's here to support an industry under real pressure that needs better tools, clearer insight, and more humane systems, an idea echoed at the 2025 BSCAI Contracting Success Conference [1]. Most current AI tools focus on the paperwork and planning parts of the job rather than the wrench-turning.

At the Mechanical Contractors Association of America's 2026 MEP Innovation Conference [2], breakout sessions focused on connecting field and fabrication data, and applying AI to automate routine tasks such as estimating, document review, and reporting. Predictive-maintenance software, AI-powered CMMS platforms, and augmented-reality headsets are increasingly used to flag failing motors and walk technicians through repair steps, and Plant Services' top stories for early 2026 [3] revolved around digital maintenance transformation and asset health. But hands-on tasks — dismantling machines, welding, climbing into mechanical rooms — still require humans, which is why Manufacturing Dive reports [4] that traditional assembly roles are declining while demand is growing for technicians who can work with robotics, maintain advanced equipment and use data to keep production running smoothly.

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AI Adoption

How fast is AI adoption growing for Maintenance and Repair Worker?

Adoption is moving faster on the "office" side of maintenance (work orders, scheduling, parts ordering, diagnostics) and slower on the physical side. A huge driver is the labor shortage: one BSCAI panelist warned that "we're not going to have enough workers to do the job in the next 20 years. AI is the least of our problems.

It's a resource we're going to need". The U.S. Bureau of Labor Statistics [5] still projects employment of general maintenance and repair workers to grow 4 percent from 2024 to 2034, about as fast as the average for all occupations, with about 159,800 openings projected each year — meaning demand for human technicians remains strong. Costs and trust are slowing things down: BSCAI leaders caution "Don't trust it.

Trust but verify… at least 50% of what we get back is not entirely true", and many small contractors can't afford big sensor rollouts. The World Economic Forum's Future of Jobs Report [6] notes that employers expect 39% of key skills required in the job market will change by 2030, so the smartest move for young people entering this field is learning to read sensor data, use AI work-order tools, and keep the diagnostic skills that machines still can't replicate.

Sources

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Will AI replace Maintenance and Repair Worker?

Will AI replace Maintenance and Repair Worker?

No. We don't think AI will replace Maintenance and Repair Workers, General, though we do expect the job to change.

Our 60.9% AI Resilience Score reflects a field where the physical, hands-on core of the work remains stubbornly human. Climbing into mechanical rooms, welding, dismantling equipment, and troubleshooting on the fly are tasks that robots and software still can't replicate reliably. AI is making real inroads on the paperwork side, things like scheduling, estimating, work orders, and predictive diagnostics, but those changes free up technicians rather than replace them (mcaa.org, plantservices.com).

Demand for human workers is holding up well. The Bureau of Labor Statistics projects employment in this role to grow 4 percent through 2034, with roughly 159,800 openings expected each year [5]. One industry voice at a major contractor conference put it plainly: the bigger threat isn't automation, it's not having enough workers to meet demand [1].

The honest caveat is on the economic side. Wages and career flexibility for this role score lower in our model, so the financial ceiling is a real consideration. The smartest path forward is building skills around the tools AI is bringing in, reading sensor data, using AI-powered maintenance platforms, and staying sharp on the diagnostics that machines still get wrong [6].

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Latest AI news for Maintenance and Repair Worker

These articles highlight how AI is transforming the landscape for Maintenance and Repair Workers. For instance, the Caterpillar AI Assistant enhances heavy equipment management by streamlining maintenance tasks, allowing workers to focus on more complex repairs. Additionally, the BLS article discusses how AI is creating new roles even as it automates some tasks, emphasizing the importance of adaptability. Understanding these trends can help students prepare for a future where AI complements their skills, ensuring resilience in their careers.

More Career Info

Career: Maintenance and Repair Workers, General

They fix and maintain machines, equipment, and buildings to keep everything working smoothly and safely.

Employment & Wage Data

Median Wage

$48,620

Jobs (2024)

1,629,700

Growth (2024-34)

+3.8%

Annual Openings

159,800

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

97% ResilienceCore Task

Operate cutting torches or welding equipment to cut or join metal parts.

2

97% ResilienceSupplemental

Lay brick to repair or maintain buildings, walls, arches, or other structures.

3

97% ResilienceSupplemental

Grind and reseat valves, using valve-grinding machines.

4

97% ResilienceSupplemental

Install equipment to improve the energy or operational efficiency of residential or commercial buildings.

5

96% ResilienceCore Task

Assemble, install, or repair wiring, electrical or electronic components, pipe systems, plumbing, machinery, or equipment.

6

96% ResilienceCore Task

Paint or repair roofs, windows, doors, floors, woodwork, plaster, drywall, or other parts of building structures.

7

96% ResilienceCore Task

Dismantle machines, equipment, or devices to access and remove defective parts, using hoists, cranes, hand tools, or power tools.

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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