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Will AI replace Tire Repairers and Changers?

Most of the work in Tire Repairers and Changers still leans on things AI struggles with — research rates its theoretical AI reach at only ~0%, and real-world use lower still.

The Human Moat Work that's hard for AI to cross — for now.

O*NET-SOC 49-3093

How your 20 core tasks split

0% within AI's reach
0 AI can do this now
0 AI speeds this up
20 Still on you
AI could do · GPT-4 study
0%
0-pt gap
AI actually does · 2026 report
0%

Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.

⚡ The short answer

Back in 2023, GPT-4 judged AI could, in theory, assist with a relatively low share of this job's tasks (~0%). By late 2025, real-world AI use had caught up to about 0% of its task activity (still rare). The gap between that 2023 forecast and today is the real story.

Where this job sits among 738 jobs

Being automatedTicking (can, but unused)Relatively safeQuietly happeningYOU0%50%100%0%40%75% → How much AI could do (theory) → How much AI is actually used (late 2025)

Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.

Stableconfidence

The signals here line up

Theoretical reach (~0%), real-world use (~0%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.

See all 20 tasks, ratedBased on real task-level AI scores — click to collapse
AI can already do this0 of 20
  • None — AI cannot fully do any core task alone yet.
AI speeds this up0 of 20
  • No tasks in this middle tier.
Still on you20 of 20
  • Raise vehicles, using hydraulic jacks.
  • Remount wheels onto vehicles.
  • Unbolt and remove wheels from vehicles, using lug wrenches or other hand or power tools.
  • Place wheels on balancing machines to determine counterweights required to balance wheels.
  • Identify tire size and ply and inflate tires accordingly.
  • Replace valve stems and remove puncturing objects.
  • Hammer required counterweights onto rims of wheels.
  • Reassemble tires onto wheels.
  • Seal punctures in tubeless tires by inserting adhesive material and expanding rubber plugs into punctures, using hand tools.
  • Inspect tire casings for defects, such as holes or tears.
  • Locate punctures in tubeless tires by visual inspection or by immersing inflated tires in water baths and observing air bubbles.
  • Glue tire patches over ruptures in tire casings, using rubber cement.
  • Assist mechanics and perform various mechanical duties, such as changing oil or checking and replacing batteries.
  • Rotate tires to different positions on vehicles, using hand tools.
  • Clean and tidy up the shop.
  • Buff defective areas of inner tubes, using scrapers.
  • Order replacements for tires or tubes.
  • Separate tubed tires from wheels, using rubber mallets and metal bars or mechanical tire changers.
  • Inflate inner tubes and immerse them in water to locate leaks.
  • Clean sides of whitewall tires.

My job is a Human Moat 😌

Turns out being human is still the hard part to copy.

Theoretical estimate · not a prediction · gistgarden.com

How we measured this — and how fresh it is

AI's theoretical reach data: 2023

From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.

Real-world AI use 2026 report

From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).

Task list & ratings O*NET 30.3

Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.

Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.

This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.