---
title: "Will AI Replace Tire Repairers and Changers?"
description: "BLS rates tire repairers and changers' exposure to AI as low. What that means, which parts of the work AI touches, and the 2025–2035 outlook (+3.4%…"
canonical: "https://nuecareer.com/careers/will-ai-replace-tire-repairers-and-changers"
last-updated: "2026-10-15T08:19:32.066Z"
---

# Will AI Replace Tire Repairers and Changers? (2026)

**Short answer:** Very unlikely. BLS rates tire repairers and changers among the occupations least exposed to AI, and most of the work is the kind current AI tools cannot do.

The Bureau of Labor Statistics places tire repairers and changers in its low AI exposure category, among the occupations least exposed to current AI. BLS projects employment to change by +3.4% over 2025–2035, against 3.5% for all occupations, with about 12,900 openings a year.

| Measure | Value | Source |
| --- | --- | --- |
| BLS relative AI exposure | Low | BLS Employment Projections, AI exposure categories |
| NueCareer AI-resilience score | 64/100 | NueCareer analysis of O\*NET 31.0 Database |
| Projected employment change | +3.4% | BLS EP 2025–2035 |
| Openings a year | 12,900 | BLS EP 2025–2035 |
| Median annual wage | $37,710 | BLS OEWS May 2025 |

## Exposure categories

| BLS category | Occupations |
| --- | --- |
| Low (this job) | 203 |
| Moderate | 194 |
| High | 190 |
| Very high | 199 |

Exposure means AI could be or has been used to assist with or complete some of the work. BLS says it does not imply job loss, productivity gains, automation probability or wage effects. Method: https://www.bls.gov/emp/publications/ai-exposure-categories.htm

## What holds up

- Face-to-face discussions: 4.6/5 (O\*NET work context)
- Hands-on work with tools and objects: 4.8/5 (O\*NET work context)
- Handling and moving objects: 4.2/5 (O\*NET work activity importance)
- Working outdoors in all weather: 4.4/5 (O\*NET work context)

## What AI reaches first

- Repetitive motions: 4.0/5 (O\*NET work context)
- Repeating the same tasks: 3.7/5 (O\*NET work context)
- Getting information: 3.8/5 (O\*NET work activity importance)
- Being exact or highly accurate: 4.3/5 (O\*NET work context)

## O\*NET tasks

- Unbolt and remove wheels from vehicles, using lug wrenches or other hand or power tools.
- Identify tire size and ply and inflate tires accordingly.
- Raise vehicles, using hydraulic jacks.
- Reassemble tires onto wheels.
- Remount wheels onto vehicles.
- Seal punctures in tubeless tires by inserting adhesive material and expanding rubber plugs into punctures, using hand tools.

## Related careers that are also low-exposure

- [Electrical Power-Line Installer and Repairer](https://nuecareer.com/careers/electrical-power-line-installer-and-repairer): BLS exposure Low, median $95,320; [Will AI replace linemen?](https://nuecareer.com/careers/will-ai-replace-linemen)
- [Mechanical Door Repairer](https://nuecareer.com/careers/mechanical-door-repairer): BLS exposure Low, median $55,720
- [Millwright](https://nuecareer.com/careers/millwright): BLS exposure Low, median $65,700
- [Motorcycle Mechanic](https://nuecareer.com/careers/motorcycle-mechanic): BLS exposure Low, median $48,580
- [Mobile Heavy Equipment Mechanic, Except Engines](https://nuecareer.com/careers/mobile-heavy-equipment-mechanic): BLS exposure Low, median $65,510; [Will AI replace mobile heavy equipment mechanics?](https://nuecareer.com/careers/will-ai-replace-mobile-heavy-equipment-mechanics)
- [Helpers--Installation, Maintenance, and Repair Worker](https://nuecareer.com/careers/helpers-installation-maintenance-and-repair-worker): BLS exposure Low, median $39,630

## FAQ

**Will AI replace tire repairers and changers?**

Very unlikely. BLS rates tire repairers and changers among the occupations least exposed to AI, and most of the work is the kind current AI tools cannot do. BLS defines exposure as AI being able to assist with or complete some of the work, and says it does not imply job loss, productivity gains or wage effects. BLS projects employment to change by +3.4% over 2025–2035, against 3.5% for all occupations, with about 12,900 openings a year.

**How exposed are tire repairers and changers to AI?**

BLS sorts 786 occupations into four relative categories: low, moderate, high and very high. Tire Repairers and Changers are in the low category, alongside 202 other occupations. The categories combine five public measures of where AI could be or already is used, and they compare occupations with each other rather than giving an absolute risk.

**What parts of a tire repairer and changer's job can AI do?**

In O\*NET's description of the work, the parts that overlap most with what AI handles well are repetitive motions, repeating the same tasks and getting information. The parts that hold up best are face-to-face discussions, hands-on work with tools and objects and handling and moving objects. These come from O\*NET ratings of how important each activity is to the job, read through NueCareer's AI-resilience method.

**Is being a tire repairer and changer a safe career from AI?**

On NueCareer's AI-resilience score, built from O\*NET work activities, tire repairers and changers score 64 out of 100, higher than 92% of the occupations we score. The job pays a median of $37,710 a year (BLS OEWS, May 2025). No job is fully safe from technological change, but the federal exposure category and the projected openings are the two numbers worth weighing.

**What careers similar to tire repairers and changers are less exposed to AI?**

Electrical Power-Line Installer and Repairer (low exposure, $95,320 median), Mechanical Door Repairer (low exposure, $55,720 median), Millwright (low exposure, $65,700 median), Motorcycle Mechanic (low exposure, $48,580 median). Each is also in the low category, and most are listed by O\*NET as related to the work.

Full profile: https://nuecareer.com/careers/tire-repairer-and-changer.

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This bank includes information from the O\*NET 31.0 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O\*NET® is a trademark of USDOL/ETA. NueCareer has transformed the data by joining it to BLS wage and projection data and deriving facet, personality-fit and AI-resilience scores. BLS and BEA data are public domain (17 U.S.C. §105).

O\*NET content is used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). How these figures are sourced and derived: https://nuecareer.com/careers/methodology