Will AI replace Automotive Body and Related Repairers?
No single dataset says so — here is what the evidence actually measures.
There is no dataset that measures "replacement." What we can do is put three independent, published measurements next to each other for Automotive Body and Related Repairers and let them stand on their own: how much of the work overlaps with what AI can do, what people who use AI in this job actually do with it today, and what the labor market is projected to do. None of these is a forecast of the role disappearing.
1. How much of the work overlaps with AI
Published exposure research places Automotive Body and Related Repairers at a low exposure level (around the 26th percentile across all occupations). Exposure measures the share of tasks that overlap with current AI capabilities — it is not a measure of how many of those tasks will actually be automated, or on what timeline, or whether the role as a whole goes away. · AI assistant applicability (Microsoft)
A second, independent read agrees on the order of magnitude: the ILO's 2025 global study — scored on the international ISCO-08 system and bridged to Automotive Body and Related Repairers through the published (approximate) O*NET-SOC crosswalk — places this work around the 26th percentile of 427 occupations, with about 18% of its tasks exposed (up from 14% in 2023). See the gradient →
2. What people actually do with AI here today
No observed-AI-use sample is published for this occupation.
3. What the labor market is projected to do
The Bureau of Labor Statistics projects employment for this occupation as about average (+1.6% over 2024–34) , with roughly 14,600 openings projected per year (growth plus replacement). A projection is a model of the labor market, made before AI's full effect is known — but it is the closest thing we have to an official outlook. · BLS Employment Projections
The skills that travel either way
Whatever AI does to the tasks, these are the highest-importance capabilities this work runs on — the ones worth deepening because they transfer across how the job evolves.
The honest bottom line
No single dataset says so — here is what the evidence actually measures. Exposure is task overlap, not a verdict. Observed use is a sample, not the whole workforce. The employment projection is a model, not a promise. They measure different things and they do not have to agree. Read them together, see the full Automotive Body and Related Repairers profile for the underlying numbers, and draw your own conclusion.
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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.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Singulariki. "Will AI replace Automotive Body and Related 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/questions/will-ai-replace-automotive-body-and-related-repairers
Singulariki. (2026). Will AI replace Automotive Body and Related Repairers?. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/questions/will-ai-replace-automotive-body-and-related-repairers
@misc{singulariki-will-ai-replace-automotive-body-and-related-repairers,
title = {Will AI replace Automotive Body and Related 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/questions/will-ai-replace-automotive-body-and-related-repairers}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.