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Automotive Glass Installers and Repairers

Occupation · SOC 49-3022.00

Replace or repair broken windshields and window glass in motor vehicles.

Also called: Automotive Glass Installer (Auto Glass Installer) · Automotive Glass Technician (Auto Glass Technician) · Glass Installer Technician · Glass Technician · Automotive Glazier (Auto Glazier) · Glass Installer · Windshield Installer · Windshield Repair Technician · Auto Glass Repair Specialist (Automotive Glass Repair Specialist) · Auto Services Glass Installer (Automotive Services Glass Installer) · Auto Technician · Automobile Installer

Job family: Installation, Maintenance, and Repair Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-49-3022-00/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.

3rd-percentile task overlap — yet about 1,400 openings a year (+3.6% 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 10th -1.2
LLM task exposure, γ (OpenAI / Eloundou) Low 3rd 0.0
AI assistant applicability (Microsoft) Low 4th 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.

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 0.6 · 49th percentile among occupations · Moderate

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 · +3.6% by 2034
Projected annual openings 1,400
Employment 2024 → 2034 20,400 → 21,100

“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.

18% mean task exposure (2025)
26th percentile of 427 placed occupations
+3 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Motor Vehicle Mechanics and Repairers · 7231 18% 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 18 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Knowledge

Customer and Personal Service 4.1
Mechanical 3.7
English Language 3.3
Administration and Management 3.0
Administrative 3.0
Public Safety and Security 2.8

Abilities

Near Vision 3.5
Manual Dexterity 3.1
Multilimb Coordination 3.1
Static Strength 3.1
Oral Comprehension 3.0
Oral Expression 3.0
Problem Sensitivity 3.0
Deductive Reasoning 3.0
Information Ordering 3.0
Visualization 3.0
Arm-Hand Steadiness 3.0
Finger Dexterity 3.0
Control Precision 3.0
Extent Flexibility 3.0
Speech Recognition 3.0
Inductive Reasoning 2.9
Trunk Strength 2.9
Far Vision 2.9
Depth Perception 2.9

Transferable skills

Installation 3.1
Equipment Selection 3.0
Social Perceptiveness 2.9
Service Orientation 2.9
Time Management 2.9
Coordination 2.8
Complex Problem Solving 2.8
Operations Monitoring 2.8
Operation and Control 2.8
Quality Control Analysis 2.8
Judgment and Decision Making 2.8

Essential skills

Speaking 3.0
Active Listening 2.9
Critical Thinking 2.9
Monitoring 2.9

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 Windows Operating system software Hot technology
Workday software Enterprise resource planning ERP software Hot technology
Estimating software Project management software
Recordkeeping software Data base user interface and query 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.

Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 5.0
Face-to-Face Discussions with Individuals and Within Teams 4.9
Telephone Conversations 4.8
Outdoors, Exposed to All Weather Conditions 4.8
In an Enclosed Vehicle or Operate Enclosed Equipment 4.6
Contact With Others 4.5
Time Pressure 4.4
Indoors, Not Environmentally Controlled 4.1
Importance of Being Exact or Accurate 4.1
Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 4.1
Spend Time Standing 3.9
Outdoors, Under Cover 3.9
Exposed to Very Hot or Cold Temperatures 3.9
Deal With External Customers or the Public in General 3.8
Exposed to Minor Burns, Cuts, Bites, or Stings 3.7
Work With or Contribute to a Work Group or Team 3.6
Frequency of Decision Making 3.6
Exposed to Extremely Bright or Inadequate Lighting Conditions 3.5
Spend Time Making Repetitive Motions 3.5
Exposed to Cramped Work Space, Awkward Positions 3.5
Freedom to Make Decisions 3.4
Impact of Decisions on Co-workers or Company Results 3.4
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 3.4
Exposed to Hazardous Equipment 3.3
Spend Time Bending or Twisting Your Body 3.2
Importance of Repeating Same Tasks 3.2
Determine Tasks, Priorities and Goals 3.1
Consequence of Error 3.0
Physical Proximity 3.0
Health and Safety of Other Workers 2.9
Indoors, Environmentally Controlled 2.9
Spend Time Walking or Running 2.7
Work Outcomes and Results of Other Workers 2.7
Written Letters and Memos 2.6
Exposed to Contaminants 2.6
Level of Competition 2.6
Dealing With Unpleasant, Angry, or Discourteous People 2.5
Conflict Situations 2.5
E-Mail 2.5
Coordinate or Lead Others in Accomplishing Work Activities 2.5

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: Mechanic and Repair Technologies/Technicians . 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 89.5%
Less than a High School Diploma 9.1%
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 3.7
Investigative 2.2
Enterprising 1.4
Social 1.3

Interest areas

Physical/Manual Labor 5.8
Mechanics/Electronics 4.9
Engineering 2.0
Construction/Woodwork 1.9
Transportation/Machine Operation 1.9
Personal Service 1.4
Sales 1.2
Accounting 1.1

Work styles

Attention to Detail 2.4
Dependability 2.2
Cautiousness 2.0

Wages & employment

U.S. · annual wages (BLS OEWS)

$35k10th$40k25th$47kMedian$58k75th$67k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
20k202421k2034 (proj.)+3.6% · About average
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $35,080
25th percentile $39,990
Median (50th) $47,260
75th percentile $58,160
90th percentile $67,480
People employed 18,940

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
Other Services (except Public Administration) · Sector 16,410 $47,440
Retail Trade · Sector 1,120 $43,680
Wholesale Trade · Sector 720 $46,410
Construction · Sector 620 $50,340
Transportation and Warehousing · Sector 30 $46,780

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
Other Services (except Public Administration) · Sector 30.18× 16,410
Wholesale Trade · Sector 0.97× 720
Construction · Sector 0.62× 620
Retail Trade · Sector 0.58× 1,120

Part of the Supply Chain & Transportation career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Automotive Glass Installers and Repairers sits at the 3rd percentile of AI task-overlap and the 26th percentile of median pay, placed here against 12 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Automotive Glass Installers and Repairers Cleaners of Vehicles and Equipment Rail Car Repairers Glaziers Insulation Workers, Floor, Ceiling, and Wall Furniture Finishers Molders, Shapers, and Casters, Except Metal and Plastic Automotive Body and Related Repairers Insulation Workers, Mechanical AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

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 Automotive Glass Installers and Repairers — 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.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 26th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Automotive Glass Installers and Repairers show 3rd-percentile AI task overlap — and about 1,400 annual U.S. openings

  • Automotive Glass Installers and Repairers 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 1,400 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 (+3.6%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $47,260, across about 18,940 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Automotive Glass Installers and Repairers show 3rd-percentile AI task overlap — and about 1,400 annual U.S. openings

• Automotive Glass Installers and Repairers 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 1,400 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 (+3.6%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $47,260, across about 18,940 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Automotive Glass Installers and Repairers". https://singulariki.com/roles/role-49-3022-00
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.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Automotive Glass Installers and Repairers." 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-49-3022-00

APA

Singulariki. (2026). Automotive Glass Installers and Repairers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-49-3022-00

BibTeX
@misc{singulariki-role-49-3022-00,
  title  = {Automotive Glass Installers and Repairers},
  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-49-3022-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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