As of July 2026, Automotive Glass Installers and Repairers has an AI-exposure score of 33/100 (Low exposure) on the AI-Safe Careers index. This is an estimate of task exposure, not a prediction of job loss.
Score inputs for this role: This role starts from O*NET 29.1 occupational descriptors and is empirically grounded by Penn/OpenAI GPTs are GPTs study, Anthropic Economic Index (June 26, 2026), Felten, Raj and Seamans AIOE index. BLS labor-market figures are separate context, not score inputs.

AI Exposure Score for

Automotive Glass Installers and Repairers

33/100
Low exposure
LowModerateElevatedHighVery High

More exposed than 2% of the roles we track. Median pay ~US$47,630. About 1,400 projected openings a year (BLS 2024–34 - growth plus replacement).

Pay & demand figures are US medians (BLS, in USD) - your local figures will differ. Your exposure score applies broadly.

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Data sources, not endorsements: O*NET and curated role data; empirical AI signals where matched; BLS employment, pay, and demand as separate context.Methodology Data sources
Role snapshot

What this role usually involves

O*NET 29.1 exact occupation

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

Common titles
Automotive Glass Installer (Auto Glass Installer)Automotive Glass Technician (Auto Glass Technician)Glass Installer TechnicianGlass TechnicianAutomotive Glazier (Auto Glazier)Glass Installer
O*NET job-zone preparation
Job Zone 2 · Some Preparation Needed These occupations usually require a high school diploma. Some previous work-related skill, knowledge, or experience is usually needed.

Broad guidance for this preparation level; exact requirements vary by role and employer.

Skills and knowledge
SpeakingCritical ThinkingMonitoringSocial PerceptivenessCustomer and Personal ServiceMechanical
Tools and technology
Microsoft WindowsWorkday softwareAccounting softwareEstimating softwareRecordkeeping softwareAir compressors
Work context
Face-to-face discussionsTelephoneFrequent contact with othersExternal customersDecision latitude

Source: O*NET 29.1 exact occupation - Automotive Glass Installers and Repairers, SOC 49-3022.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.

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Automotive Glass Installers and Repairers tasks, by AI exposure

Automatable

No automatable tasks identified for this role - its real, individually-assessed tasks consistently read as durable (100%).

Augmentable

No augmentable tasks identified for this role - its real, individually-assessed tasks consistently read as durable (100%).

Durable
  • Cool or warm glass in the event of temperature extremes.
  • Select appropriate tools, safety equipment, and parts, according to job requirements.
16 more durable tasks locked in the report.

We analyzed all 18 Automotive Glass Installers and Repairers tasks - 18 durable. The full task map - every task with exactly what to do about each - is in your Career Report.

Your report unlocks three concrete artifacts

Full task map

Every task scored with what to automate, augment, or protect.

Adjacent path comparison

Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.

30/60/90 plan + PDF

A keepable roadmap plus resume and LinkedIn repositioning.

Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.

Adjacent career paths

This role is already among lower-exposure work. The adjacent paths below are shown for opportunity and skill transfer, not as lower-exposure alternatives.

Glaziers
80% skills overlap; 5 points higher - similar exposure within the 5-point model resolution; Low band; ~US$57,080
View path
38
7 more adjacent paths with exposure deltas, salary, demand, and reachability in your Career Report.

Your AI-Safe Career Report

Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.

Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026

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Important: This is an estimate of AI exposure, not a prediction that your job will disappear. It is designed to help you understand how your role may change and improve your career resilience.