Mostly Resilient

Last Update: 8/30/2026

AI Resilience Score for Installation & Repair Worker:

56.3%

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 installation 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 five AI-exposure sources: our own AI Resilience Model, Anthropic's Observed Exposure, Microsoft's AI Applicability, Will Robots Take My Job, and OpenAI Signals. 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 installation and repair workers, five of eight sources had data. The sources that did weigh in mostly agreed: hands-on physical work keeps AI exposure low to medium, with AI Resilience Model rating it High and Microsoft rating it Medium. Employer demand looks steady, but pay and mobility signals pulled the economic score down, landing this career at "Mostly Resilient" with medium confidence.

AI Resilience Report forInstallation, Maintenance, and Repair Workers, All Other

$49,230 median salary18,300 annual openingsSOC Code: 49-9099.00

Installation, Maintenance, and Repair Workers, All Other are somewhat more resilient to AI impacts than most occupations, according to our analysis of 5 sources.

This career holds up well against AI because the core work is deeply hands-on and unpredictable, requiring real human judgment, physical dexterity, and on-the-spot problem solving that robots and software simply cannot replicate in the field. AI tools like predictive maintenance software are entering the picture, but they act more like a helpful assistant, flagging problems early and helping prioritize repairs, while a skilled technician still has to show up, diagnose the issue, and do the actual fix.

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This role is mostly resilient

This career holds up well against AI because the core work is deeply hands-on and unpredictable, requiring real human judgment, physical dexterity, and on-the-spot problem solving that robots and software simply cannot replicate in the field. AI tools like predictive maintenance software are entering the picture, but they act more like a helpful assistant, flagging problems early and helping prioritize repairs, while a skilled technician still has to show up, diagnose the issue, and do the actual fix.

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Analysis of Current AI Resilience

Installation & Repair Worker

Updated Quarterly

Analysis
Suggested Actions
State of Automation

How is AI changing Installation & Repair Worker jobs?

If your future job involves fixing equipment, patching torn canvas, restitching seams, or setting up systems, here's some encouraging news: AI is showing up mostly as a helper, not a replacement. Across the wider maintenance and repair world, tools like predictive maintenance software use sensors and machine learning to flag equipment problems early, but a human still has to inspect, diagnose, and do the physical fix. A senior editor at Facilities Management Insights explains that "AI augments diagnosis and prioritization.

It still takes a skilled technician to execute the repair and validate the root cause." For repair jobs that involve hands-on work with fabric, grommets, hemming, and sewing machines, robots exist for factory-scale garment production, but roving repair work in the field—on tents, awnings, curtains, or custom coverings—still relies on human eyes and hands. As one industry blog puts it, technician roles are among the most AI-resistant jobs because of their hands-on, site-specific nature and unpredictable troubleshooting demands, and AI is more often used to spot failures early so workers can be dispatched to fix them.

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AI Adoption

How fast is AI adoption growing for Installation & Repair Worker?

Adoption in this field is moving, but slowly and unevenly. An IIoT World analysis published in August 2026 [1] reports that roughly two-thirds of maintenance teams plan to adopt AI by year's end, but only 32% have partially or fully implemented it, and the biggest barriers are budget (25%), skills gaps (24%), and cybersecurity concerns (22%). Trade associations are trying to close the skills gap: the Association of Physical Plant Administrators is running hands-on AI training [2], noting that AI is changing how work gets done in facilities management, but most facilities professionals haven't had a practical way to get started.

Labor market conditions also slow full replacement: the U.S. Bureau of Labor Statistics projects installation, maintenance, and repair occupations to add about 301,400 jobs and grow 4.6% from 2024–34 [3], faster than the 3.1% average for all occupations. With demand high and physical dexterity hard to automate, expect AI to help you work smarter—reading dashboards, prioritizing repairs, and ordering parts—while your hands-on skills stay valuable.

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Will AI replace Installation & Repair Worker?

Will AI replace Installation & Repair Worker?

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

Our 56.3% AI Resilience Score reflects a field where human hands and judgment still matter a lot. AI is showing up in predictive maintenance tools that flag equipment problems early, but someone still has to show up, inspect the situation, and do the physical fix. That hands-on, site-specific troubleshooting is genuinely hard to automate, especially for repair work involving fabric, custom coverings, or unpredictable field conditions.

Adoption is real but uneven. Only about 32% of maintenance teams have partially or fully implemented AI so far, with budget and skills gaps slowing things down [1]. Trade groups like the Association of Physical Plant Administrators are working to help workers get practical AI training so they can use these tools rather than be sidelined by them [2]. The labor market is also holding up: the BLS projects installation, maintenance, and repair occupations to grow 4.6% through 2034, faster than the average for all occupations [3].

The economic picture is the one honest caution here. Wages and career flexibility in this field score lower than the demand numbers suggest, so building skills that travel across industries is worth thinking about early.

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Latest AI news for Installation & Repair Worker

These articles highlight that careers in installation, maintenance, and repair are among the least threatened by AI advancements. For instance, Anthropic's research shows skilled trades are less likely to face job loss due to their reliance on physical skills and human judgment. Additionally, the McKinsey article emphasizes collaboration between humans and robots, indicating that AI can enhance rather than replace these roles. This suggests a resilient future for students entering this field, where adaptability and hands-on expertise will remain crucial.

More Career Info

Career: Installation, Maintenance, and Repair Workers, All Other

They fix and set up various equipment and systems, ensuring everything works correctly and safely in different settings.

Employment & Wage Data

Median Wage

$49,230

Jobs (2025)

205,200

Growth (2025-35)

+2.6%

Annual Openings

18,300

Education

High school diploma or equivalent

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2025-2035

Task-Level AI Resilience Scores

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

1

88% ResilienceSupplemental

Replace defective shrouds, and splice connections between shrouds and harnesses, using hand tools.

2

86% ResilienceSupplemental

Pull knots to the wrong sides of garments, using hooks.

3

85% ResilienceSupplemental

Re-knit runs and replace broken threads, using latch needles.

4

82% ResilienceSupplemental

Repair holes by weaving thread over them, using needles.

5

80% ResilienceSupplemental

Sew fringe, tassels, and ruffles onto drapes and curtains, and buttons and trimming onto garments.

6

78% ResilienceCore Task

Patch holes, sew tears and ripped seams, or darn defects in items, using needles and thread or sewing machines.

7

72% ResilienceCore Task

Operate sewing machines to restitch defective seams, sew up holes, or replace components of fabric articles.

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.

The AI Resilience Report is a project from CareerVillage.org®, a registered 501(c)(3) nonprofit.

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