Installation, Maintenance, and Repair · United States (national)
Tire Repairers and Changers
How exposed this work is to automation, shown as ranges with the reasoning and sources.
The short version: this role is highly exposed to automation, and the bigger shift looks near-term.
It is a sourced range, not a verdict, and the detail is below.
Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown.
Data snapshot SNAPSHOT-2026-11-06. How it works
AI / softwarerange 0.0 to 12.0
Physical / roboticsrange 56.8 to 80.8
When the change is likely
Near-term, highlocal demand declining
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Act within the next 1 to 2 years
Displacement for this role is near-term. Start a concrete reskilling plan now, while you still have income and leverage.
2
Move up from the task to the system
Robotics targets the physical work. Shift toward supervising, maintaining, or programming the automation instead of competing with it.
3
Pivot toward Bicycle Repairers
It is skill-adjacent and less exposed (52.3 vs 69). A lateral move now beats a forced one later.
4
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
5
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.
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Which of my tasks are exposed
Raise vehicles, using hydraulic jacks.
68.8
Remount wheels onto vehicles.
68.8
Unbolt and remove wheels from vehicles, using lug wrenches or other hand or power tools.
68.8
Place wheels on balancing machines to determine counterweights required to balance wheels.
68.8
Identify tire size and ply and inflate tires accordingly.
68.8
Replace valve stems and remove puncturing objects.
68.8
Hammer required counterweights onto rims of wheels.
68.8
Reassemble tires onto wheels.
68.8
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Local demand is declining
Task: Raise vehicles, using hydraulic jacks.
Task: Remount wheels onto vehicles.
Lower-risk adjacent roles
Bicycle Repairers
52.3
Automotive Service Technicians and Mechanics
61.0
Automotive Body and Related Repairers
66.3
Motorcycle Mechanics
67.5
Rail Car Repairers
67.5
A full, ranked mitigation plan is part of the paid tiers.
How this score is calculated
Map Tire Repairers and Changers to its standard O*NET task list (8 core tasks).
Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
The two axis scores are the task averages: AI 0.0, robotics 68.8.
The timeline comes from the higher axis (68.8), shifted for local demand (declining), and seniority. It is read against your remaining working years.
Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.
Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS.
Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.