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AI Automation Index
Will AI Replace Electronic Equipment Installers and Repairers, Motor Vehicles?
Task-level automation exposure for Electronic Equipment Installers and Repairers, Motor Vehicles: 12 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
27%
weighted task index
12 of 12 tasks scored
Median Salary
$48,420 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Low
8,550 people hold this job — size, not growth
Projected 2025–35
-14.5%
employment change
400 openings a year · BLS line item
Pay by state
BLS OEWS publishes 39 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$26,640 – $64,570
Highest medians
Kentucky $64,570
New York $60,220
Colorado $60,070
Georgia $59,550
Washington $59,010
Lowest medians
Pennsylvania $26,640
Kansas $33,380
Wisconsin $38,070
Mississippi $38,500
Alabama $38,520
State figures come from the 49-2096 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 27%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 63%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 0%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 9%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 24/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
12 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 19%
2 tasks
Medium exposure (≥ 35%) 8%
1 tasks
Low exposure (below 35%) 73%
9 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#13729 · Core · 70% automatable
Estimate costs of repairs, based on parts and labor charges.
data analysis — Labor/material cost estimation from rates
Estimate costs for labor or materials.
#13728 · Core · 8% automatable
Install equipment and accessories, such as stereos, navigation equipment, communication equipment, and security systems.
physical manipulation — Installing AV equipment requires hands-on wiring
Install audio or communications equipment.
#13727 · Core · 24% automatable
Inspect and test electrical or electronic systems to locate and diagnose malfunctions, using visual inspections and testing instruments, such as oscilloscopes and voltmeters.
data analysis — Electrical testing requires hands-on instrument use
Inspect electrical or electronic systems for defects. Test electrical equipment or systems to ensure proper functioning.
#13726 · Core · 18% automatable
Diagnose or repair problems with electronic equipment, such as sound, navigation, communication, and security equipment, in motor vehicles.
physical manipulation — Hands-on electronic equipment repair
Repair electronic equipment.
#13730 · Core · 45% automatable
Confer with customers to determine the nature of malfunctions.
interpersonal — Assessing customer problems needs live diagnostic dialogue
Confer with customers or users to assess problems.
#13735 · Core · 83% automatable
Record results of diagnostic tests.
text generation — Write test result reports from data
Document test results.
#13725 · Core · 10% automatable
Splice wires with knives or cutting pliers, and solder connections to fixtures and equipment.
physical manipulation — Connecting electrical components is manual work
Connect electrical components or equipment. Solder parts or connections between parts.
#13731 · Core · 10% automatable
Run new speaker and electrical cables.
physical manipulation — Laying cables requires physical routing work
Lay cables to connect equipment.
#13734 · Core · 5% automatable
Remove seats, carpeting, and interiors of doors and add sound-absorbing material in empty spaces, reinstalling interior parts.
physical manipulation — Removing vehicle parts requires hands-on mechanical work
Install insulation in equipment or structures. Install vehicle parts or accessories. Remove parts or components from vehicles.
#13733 · Core · 14% automatable
Replace and clean electrical or electronic components.
physical manipulation — Physical component-level repair work
Clean equipment, parts, or tools to repair or maintain them in good working order. Repair electrical components.
#13732 · Core · 12% automatable
Cut openings and drill holes for fixtures and equipment, using electric drills and routers.
physical manipulation — Drilling parts requires physical tool operation
Drill holes in parts, equipment, or materials.
#13736 · Supplemental · 10% automatable
Build fiberglass or wooden enclosures for sound components, and fit them to automobile dimensions.
physical manipulation — Part fabrication requires physical machining and handling
Fabricate parts or components.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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