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Comparison · dataset August 2026

Auto Mechanic vs Construction Laborer: which is more exposed to AI?

Auto Mechanic carries 14 points more AI exposure than Construction Laborer.

Auto Mechanic sits at 29% time-weighted AI exposure against 15% for Construction Laborer, a 14-point gap driven by the 0% of auto mechanic work time that current models can already substitute outright. Construction Laborer holds a larger human-critical core — 92% of the role's time sits in work like "use hand and power tools" that models score poorly on. Both roles sit inside Trades & Construction, so the exposure difference reflects task design rather than a change of field.

14PP GAP

Seven dimensions, side by side.

METRICAUTO MECHANICCONSTRUCTION LABORERDELTA
AI exposure29%15%14pp gap
Resilience score86/10093/1007pt gap
Substitutable work time0%0%Fully automatable today
Human-critical work time78%92%Models score poorly here
Median salary$49k$46k$3k apart
10-year growth3%4%Construction Laborer
US workforce782k1.6MBLS OEWS
Task level

What actually creates the gap.

Both roles hand a similar slice of the week to substitutable work — 0% for Auto Mechanics, 0% for Construction Laborers — but it is different work. Auto Mechanic exposure concentrates in "retrieve diagnostic codes and service info"; Construction Laborer exposure concentrates in "review safety briefings and site instructions". Two roles can share a score and face completely different disruption timelines.

Auto Mechanic
MOST EXPOSED TASKS
    HUMAN-CRITICAL CORE
    • Repair engines, brakes, and drivetrains6% · 24% time
    • Road test and validate repairs12% · 6% time
    • Inspect vehicles and diagnose faults18% · 24% time
    Construction Laborer
    MOST EXPOSED TASKS
      HUMAN-CRITICAL CORE
      • Use hand and power tools4% · 24% time
      • Move materials and prepare work areas6% · 28% time
      • Assist skilled trades on-site8% · 18% time
      What transfers

      Both roles lean on manual, procedural, judgement — that is the part of your experience that travels intact. The real divide is cognitive: Auto Mechanics score 56 there against 32 for Construction Laborers, a 24-point spread. That is the gap you would actually have to close.

      DIMENSIONAUTO MECHANICCONSTRUCTION LABORER
      Cognitive5632
      Switching between them
      LowDIFFICULTY

      Neither role lists the other as a mapped adjacent career, but the capability profiles are only 13 points apart on average and both sit in Trades & Construction. In practice that means a move is plausible without retraining from scratch — the constraint is credentials and hiring convention, not capability.

      Score your own exposure in 8 questions →

      Common questions.

      Is Auto Mechanic or Construction Laborer more at risk from AI?

      Auto Mechanic. It scores 29% time-weighted AI exposure against 15% for Construction Laborer — a 14-point gap. 0% of auto mechanic work time is already fully substitutable by current models, versus 0% for Construction Laborers.

      Which pays more, Auto Mechanic or Construction Laborer?

      Auto Mechanic, by roughly $3k at the median ($49k versus $46k). Note that the higher-paying role here is also the more AI-exposed one, which matters if you are weighing pay against durability.

      Can a auto mechanic switch to being a construction laborer?

      Neither role lists the other as a mapped adjacent career, but the capability profiles are only 13 points apart on average and both sit in Trades & Construction. In practice that means a move is plausible without retraining from scratch — the constraint is credentials and hiring convention, not capability.

      Which role is growing faster, Auto Mechanic or Construction Laborer?

      Construction Laborer, at 4% projected ten-year growth versus 3% — a 1-point difference. Growth and AI exposure are separate signals: a role can grow in headcount while the content of the work is substantially rewritten.

      Career families
      Trades & Construction
      Methodology
      Scores are time-weighted across each role's canonical O*NET tasks, graded against current frontier-model capability. How we score.