Will AI replace Automotive Glass Installers and Repairers?
Estimated risk score: 9 out of 100
Very low replacement risk
Estimate from published task research, not reviewed by a person · how we estimate
Within about 19 points for 4 in 5 of the jobs we checked (0 to 28).
For the occupation as a whole, from ratings of its 18 O*NET tasks published in 2023 and calibrated to our hand scores. A specialty inside it can sit higher or lower.
O*NET-SOC 49-3022.00 · Installation, Maintenance, and Repair
Tasks rated in 2023 as ones AI could do or speed up
Tasks a GPT-4-class model could do, or do in half the time or less: 0 of its 18 rated tasks. In O*NET’s words.
None of its rated tasks.
Tasks rated in 2023 as not sped up by AI
Tasks such a model was rated as not speeding up or taking over: 18 of its 18 rated tasks; the first 6 are shown. In O*NET’s words.
- 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.
- Check for and remove moisture or contamination in damaged areas and keep areas dry until repairs are complete.
- Cool or warm glass in the event of temperature extremes.
- Install new foam dams on pinchwelds, if required.
- Install replacement glass in vehicles.
- Install rubber channeling strips around edges of glass or frames to weatherproof windows or to prevent rattling.
What the job is
Replace or repair broken windshields and window glass in motor vehicles.
Also called: Glass Technician, Glass Installer Technician, Automotive Glass Installer (Auto Glass Installer), Automotive Glass Technician (Auto Glass Technician), Auto Glazier, Direct Installer, Automotive Tinter, Auto Glass Mechanic.
Source. This site includes information from the O*NET 30.1 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. USDOL/ETA has not approved, endorsed, or tested these modifications. (O*NET, CC BY 4.0.) Task ratings: Eloundou, Manning, Mishkin and Rock (2023), “GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models”, data used under the MIT licence (licence texts). Our change: we averaged the ratings over this occupation’s tasks and calibrated them to our 0–100 scale. It is not a prediction about any one person and not career advice. Disagree? Write to hello@yourstopwashit.com. How we estimate