SOC 49-3093

Tire Repairers and Changers AI displacement risk

Tire repairers and changers mount, balance, and repair tires at volume. Balancing machines and TPMS diagnostics automate the measurement, but every wheel still gets unbolted, mounted, torqued, and road-tested by a person — often on the roadside for commercial fleets.

Exposure24

Share and intensity of work current AI systems can materially affect.

Automation9%

Likely potential for exposed tasks to move to software after workflow integration.

Risk bandLow

The work is physically repetitive but stubbornly manual: no robot handles the variety of wheels, vehicles, and roadside conditions a tire tech sees in a day. TPMS and EV-specific tire requirements add diagnostic steps rather than remove them.

Distribution

Where Tire Repairers and Changers sits across 620 tracked roles

Tire Repairers and Changers · 14050100

Displacement pressure 14 — higher than 8% of the 620 occupations tracked on displacement.ai.

Score version

This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.

25 O*NET task statements matched to SOC 49-3093. The displayed task profile combines these official task statements with the current public score model.

Median wage context: $37,710 (May 2025, US national). The latest BLS row matched SOC 49-3093.

Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.

2030 economic stress test

How Anthropic's scenarios classify Tire Repairers and Changers

SOC 49-3093 places this role in the paper's all-other occupation group. These group-level outcomes do not change the 14/100 role score and are not an occupation forecast.

Modest change

+1.1% group wage

Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.

Economy-wide: +1.6% GDP and 3.9% unemployment.

Substantial change

+5.9% group wage

Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.

Economy-wide: +8.3% GDP and 4.6% unemployment.

Extreme change

+33.6% group wage

Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.

Economy-wide: +32.4% GDP and 11.9% unemployment.

Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.

Official task evidence

O*NET task matches for Tire Repairers and Changers

The current evidence import matched 25 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.

Dataset31.0 (August 2026)
Matched tasks25
SOC49-3093
  • Core task / ID 20654

    Unbolt and remove wheels from vehicles, using lug wrenches or other hand or power tools.

  • Core task / ID 8363

    Place wheels on balancing machines to determine counterweights required to balance wheels.

  • Core task / ID 20655

    Identify tire size and ply and inflate tires accordingly.

  • Core task / ID 8364

    Raise vehicles, using hydraulic jacks.

  • Core task / ID 8368

    Reassemble tires onto wheels.

  • Core task / ID 8374

    Glue tire patches over ruptures in tire casings, using rubber cement.

Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.

Task profile

Where AI changes the work

physical

Unbolt and remove wheels from vehicles

Exposure 16, automation 6%, augmentation 28%.

O*NET evidence: Unbolt and remove wheels from vehicles, using lug wrenches or other hand or power tools. (ID 20654)

technical

Balance wheels using balancing machines

Exposure 30, automation 15%, augmentation 40%.

O*NET evidence: Place wheels on balancing machines to determine counterweights required to balance wheels. (ID 8363)

physical

Replace valve stems and repair punctures

Exposure 20, automation 8%, augmentation 36%.

O*NET evidence: Replace valve stems and remove puncturing objects. (ID 8369)

physical

Remount wheels onto vehicles

Exposure 16, automation 6%, augmentation 28%.

O*NET evidence: Remount wheels onto vehicles. (ID 8365)

TaskExposureAutomationAugmentation
Unbolt and remove wheels from vehicles166%28%
Balance wheels using balancing machines3015%40%
Replace valve stems and repair punctures208%36%
Remount wheels onto vehicles166%28%

Transition pathways

Adjacent moves that preserve existing skills

credentialed transition

Automotive Service Technician

Training horizon: 12-24 months. Skill overlap 58. Wage preservation signal 124.

  • Broaden into general service
  • Earn ASE certifications
  • Join a service department
Low
role redesign

Commercial Tire Account Lead

Training horizon: 6-12 months. Skill overlap 62. Wage preservation signal 116.

  • Serve fleet accounts
  • Run roadside dispatch
  • Own retread programs
Low

Comparison guides

Compare the next move before you commit

What the AI risk score means for Tire Repairers and Changers

The displacement pressure score for Tire Repairers and Changers is 14. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.

For this role, the clearest risk pattern is visible at the task level. Balance wheels using balancing machines carries 15% automation pressure, while Balance wheels using balancing machines carries 40% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.

Labor-market context and wage risk

Median wage: $37,710 (May 2025, US national). Employment context: High-volume vehicle service with balancing-machine assists. Typical education: High school plus on-the-job training.

Wage vulnerability is 58, while transition feasibility is 58. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.

  • Low displacement pressure
  • Machines measure, hands mount
  • EV tires add service steps

Upskilling priorities

Skills that make this role more resilient

The safest upskilling plan starts with skills already close to the work. For Tire Repairers and Changers, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.

Priority 1

Vehicle tire service

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

Priority 2

Balancing machine operation

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

Priority 3

TPMS diagnostics

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

Priority 4

Roadside service

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

90-day transition plan

The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.

  1. In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
  2. By 60 days, complete one small project connected to Automotive Service Technician, such as broaden into general service.
  3. By 90 days, compare internal openings and external postings for Automotive Service Technician or Commercial Tire Account Lead and update your resume around measurable workflow outcomes.

FAQ

Questions about AI and Tire Repairers and Changers

Will AI replace Tire Repairers and Changers?

Tire repairers and changers mount, balance, and repair tires at volume. Balancing machines and TPMS diagnostics automate the measurement, but every wheel still gets unbolted, mounted, torqued, and road-tested by a person — often on the roadside for commercial fleets. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.

Which parts of Tire Repairers and Changers work are most exposed to AI?

Balance wheels using balancing machines and Replace valve stems and repair punctures show the strongest automation pressure in this model. Balance wheels using balancing machines and Replace valve stems and repair punctures are better treated as AI-augmented work.

What should Tire Repairers and Changers learn next?

Start with Vehicle tire service, Balancing machine operation, TPMS diagnostics. The most practical adjacent paths in this model are Automotive Service Technician and Commercial Tire Account Lead.

How should this score be used?

Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.

Sources

Evidence trail