Mostly Resilient
Last Update: 5/19/2026
AI Resilience Score for Auto Glass Installer/Repair:
57.6%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
High
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Low
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
Limited data sources are available, or existing sources show notable disagreement on the outlook for this occupation.
Contributing sources
AI Resilience Report forAutomotive Glass Installers and Repairers
$47,260 median salary•1,400 annual openings•SOC Code: 49-3022.00
Automotive Glass Installers and Repairers are somewhat more resilient to AI impacts than most occupations, according to our analysis of 5 sources.
Auto glass installation is holding up really well against AI because the hands-on physical work — removing old glass, applying primer, and setting a new windshield in place — still requires a real person who can adapt to every different car, parking spot, and set of moldings on the fly. What *is* changing is that modern windshields now carry cameras and sensors for safety systems, so technicians are learning to use AI-powered calibration tools to make sure those systems work correctly after a glass swap.
Learn more about how you can thrive in this position
Learn more about how you can thrive in this position
This role is mostly resilient
Auto glass installation is holding up really well against AI because the hands-on physical work — removing old glass, applying primer, and setting a new windshield in place — still requires a real person who can adapt to every different car, parking spot, and set of moldings on the fly. What *is* changing is that modern windshields now carry cameras and sensors for safety systems, so technicians are learning to use AI-powered calibration tools to make sure those systems work correctly after a glass swap.
Read full analysisAnalysis of Current AI Resilience
Auto Glass Installer/Repair
Updated Quarterly

How is AI changing Auto Glass Installer/Repair jobs?
If you're worried that a robot might take over auto glass work tomorrow, take a deep breath — that's not what's happening. The physical work of removing windshields, prepping pinchwelds with primer, and laying urethane beads is still done by human hands, because every car is parked in a slightly different spot, and every windshield has its own curve, clips, and moldings. What AI is changing is the technology inside the glass.
A modern windshield is often a mounting surface for forward-facing cameras, rain and light sensors, and brackets that hold them in a precise position, and even tiny differences in glass thickness, curvature, or bracket placement can move a camera's view enough to affect how advanced driver assistance systems interpret the road. That means after a glass swap, technicians now use AI-powered calibration tools — both static calibration with targets and dynamic calibration on the road [1] — to teach the car's cameras to "see" correctly again. The Auto Glass Safety Council is rolling out a new ADAS certification [2] so technicians learn how these systems work and when to calibrate.
So the job is being augmented, not replaced.
Sources

How fast is AI adoption growing for Auto Glass Installer/Repair?
Adoption is moving fast on the diagnostic side because insurers report calibration is contributing to higher claim costs [3] and shops that can do it in-house win more business. Trade groups like NGA are even teaching members how to implement AI for everyday work [4]. But adoption of physical automation is slow: equipment can cost $20,000 or more per bay [1], and BLS still projects 16,000 yearly openings through 2034 at a median wage of $47,260 [5] — labor is cheap enough, and the work mobile enough, that robots can't compete.
New laws like California's SB 988, which would require shops to disclose ADAS calibration results [6], actually increase demand for trained human techs who can document the job. Bottom line: AI is becoming a power tool in your kit, not a replacement for you.
Sources

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More Career Info
Career: Automotive Glass Installers and Repairers
They fix and replace car windows and windshields to keep vehicles safe and protect drivers from weather and road debris.
Parent Careers
Employment & Wage Data
Median Wage
$47,260
Jobs (2024)
20,400
Growth (2024-34)
+3.6%
Annual Openings
1,400
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
Apply a bead of urethane around the perimeter of each pinchweld and dress the remaining urethane on the pinchwelds so that it is of uniform level and thickness.
2
Check for and remove moisture or contamination in damaged areas and keep areas dry until repairs are complete.
3
Install rubber channeling strips around edges of glass or frames to weatherproof windows or to prevent rattling.
4
Cool or warm glass in the event of temperature extremes.
5
Remove all dirt, foreign matter, and loose glass from damaged areas, apply primer along windshield or window edges, and allow primer to dry.
6
Remove moldings, clips, windshield wipers, screws, bolts, and inside A-pillar moldings and lower headliners in preparation for installation or repair work.
7
Replace or adjust motorized or manual window-raising mechanisms.
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.
