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needsahuman

Will AI replace electronic equipment installers and repairers, motor vehicles?

Nah.

This job scores 82 out of 100 on (higher is safer). Today people do 20% of the work with AI’s help, and 80% still needs a person.

Updated 3 October 2026O*NET-SOC 49-2096UK SOC 5245Release 2026-Q4
Installation, Maintenance, and RepairElectronic Equipment Installers and Repairers, Motor Vehicles49-2096 · 2026-Q4
0% AI does it20% AI helps80% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 80%AI helps 20%AI does it 0%
Each ridge is a slice of the job's task time.Needs a human 80%AI helps 20%AI does it 0%
The job’s mark

No two jobs leave the same print

Every job gets its own fingerprint, drawn from its code. The amber ridges are the share of task time that still needs a person. Below them, the same ridges are written out in ones and zeros: slate for the work AI helps with, white for the work AI can do.

Electronic Equipment Installers and Repairers, Motor Vehicles, O*NET-SOC 49-2096. 80% of the job’s task time still needs a human, so 80 of every 100 ridges are amber; slate is what AI helps with, white what AI can do.

What AI can and cannot do

The tasks that make up the job, from O*NET, and where AI stands on each today. 80% of the task time still needs a human.

Each block is one task; its height is its share of working time.Needs a human 80%AI helps 20%AI does it 0%
The job's task list: the parts AI can do are blacked out.Needs a human 80%AI helps 20%AI does it 0%
Estimate costs of repairs, based on parts and labor charges.AI helps
Install equipment and accessories, such as stereos, navigation equipment, communication equipment, and security systems.Needs a human
Inspect and test electrical or electronic systems to locate and diagnose malfunctions, using visual inspections and testing instruments, such as oscilloscopes and voltmeters.Needs a human
Diagnose or repair problems with electronic equipment, such as sound, navigation, communication, and security equipment, in motor vehicles.Needs a human
Confer with customers to determine the nature of malfunctions.Needs a human
Record results of diagnostic tests.AI helps
Splice wires with knives or cutting pliers, and solder connections to fixtures and equipment.Needs a human
Run new speaker and electrical cables.Needs a human
Remove seats, carpeting, and interiors of doors and add sound-absorbing material in empty spaces, reinstalling interior parts.Needs a human
Replace and clean electrical or electronic components.Needs a human
Cut openings and drill holes for fixtures and equipment, using electric drills and routers.Needs a human
Build fiberglass or wooden enclosures for sound components, and fit them to automobile dimensions.Needs a human

Is it better than a person? The evidence

No direct test against people in this job yet. Every study is graded A to D, and vendor studies are labelled as such.

When could it be replaced?

Could be largely automated no sooner than 2045

80% of scenarios after 2045. A range from our scenario model of capability, adoption and friction, not a forecast that the job ends.

The sand is the human working years left, measured in the same 40-year glass for every job, so a safe trade starts nearly full and an exposed job with a thin layer.

The sand is the human working years left, in the same 40-year glass for every job.Years still needing a humanYears run out

How this job could shift, year by year

Where the job could sit on our scale each year to 2060, across the ten scenarios behind its replacement range.

Today
Will AI replace this job?
Nah.
By 2045
20%
of our scenarios have AI largely doing this job by 2045 (Largely.)
10% still have it mostly needing a person (A little. or Nah.)
By 2060
90%
of our scenarios have AI largely doing this job by 2060 (Largely.)
10% still have it mostly needing a person (A little. or Nah.)

We run this job as ten scenarios spread across its replacement range. In each, the score moves towards the bottom band (Largely: AI could largely do the job) by the year that scenario reaches it, slowly at first and faster later, as adoption usually goes. Each bar splits the ten by the band they put the job in. The model stops at 2060. How the timeline works

Share of this job's scenarios in each verdict band, today to 20600%25%50%75%100%2026: 100.0% of scenarios: this job mostly needs a person (Nah.)100%Today2030: 20.0% of scenarios: this job mostly needs a person (Nah.)20%2030: 80.0% of scenarios: AI could do a little of this job (A little.)80%20302035: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2035: 60.0% of scenarios: AI could do a little of this job (A little.)60%2035: 30.0% of scenarios: AI could partly do this job (Partly.)30%20352040: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2040: 10.0% of scenarios: AI could do a little of this job (A little.)10%2040: 50.0% of scenarios: AI could partly do this job (Partly.)50%2040: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%20402045: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2045: 30.0% of scenarios: AI could partly do this job (Partly.)30%2045: 40.0% of scenarios: AI could mostly do this job (Mostly.)40%2045: 20.0% of scenarios: AI could largely do this job (Largely.)20%20452050: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2050: 40.0% of scenarios: AI could mostly do this job (Mostly.)40%2050: 50.0% of scenarios: AI could largely do this job (Largely.)50%20502055: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2055: 20.0% of scenarios: AI could mostly do this job (Mostly.)20%2055: 70.0% of scenarios: AI could largely do this job (Largely.)70%20552060: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2060: 90.0% of scenarios: AI could largely do this job (Largely.)90%2060
Will AI replace the job?Largely.Mostly.Partly.A little.Nah.
Share of this job's scenarios in each band, year by year. Updated with every release.
Show the data
YearLargelyMostlyPartlyA littleNah
Today (2026)0.0%0.0%0.0%0.0%100.0%
20300.0%0.0%0.0%80.0%20.0%
20350.0%0.0%30.0%60.0%10.0%
20400.0%30.0%50.0%10.0%10.0%
204520.0%40.0%30.0%0.0%10.0%
205050.0%40.0%0.0%0.0%10.0%
205570.0%20.0%0.0%0.0%10.0%
206090.0%0.0%0.0%0.0%10.0%

What’s stopping AI taking over?

The things that keep this work with people, strongest first. Each is scored 0 to 100 from O*NET work context, licensing and the evidence we have.

LiabilityMistakes are rated 3.4 out of 5 for consequence and decisions 3.8 out of 5 for impact; someone has to answer for them.
Physical work72% of the task time is physical; robots have been shown on 28% of that time.
Clients want a personFace-to-face contact is rated 4.3 and physical closeness 3.3 out of 5; caring for or serving people is 2.8 out of 5 in importance.
Evidence gapNo study yet compares AI with people doing this job, so employers have no proof it is good enough.
RegulationWorkers rate responsibility for others' health and safety 3.2 out of 5.
LicensingUsual entry requirement (BLS): high school diploma or equivalent, then moderate-term on-the-job training.

What would it cost to hand the work to AI?

The share of the year AI could handle (235 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$20–$2,350
A person’s wage for the same hours
$4,020–$7,930

AI cost covers model usage only: no integration, licences, oversight or the human time still needed to review the work. Human cost is the wage for the same hours, without benefits or overheads. As of 2026-10.

Robots and humanoids

AI software can only take the work at a screen. The rest needs a robot that can do it.

72%
of the task time is physical work
Dexterous humanoid
the kind of robot the physical work would need
Not commercial: no cited robot does most of this work; humanoids are at demonstration and pilot stage.

Source: Anthropic Economic Index, 'What work can robots do?' (30 September 2026); O*NET 31.0 task weights.

Which AI skills does this job lean on?

The job’s task time split by what an AI model would need to be good at, and where models stand today.

Each star is a task, grouped by the AI skill it leans on.Needs a human 80%AI helps 20%AI does it 0%
Writing · 8.6% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 11.5% of time
Strong
Reliable on structured data and rules; uneven on judgement calls with thin information.
Coding · 0% of time
Strong
Agents complete many routine software tasks end to end; larger systems still need people.
Vision and design · 0% of time
Good
Reads documents, images and layouts well; specialist imaging needs dedicated, approved tools.
Speech · 8% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 0% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 71.9% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 0% of time
Limited
Can script, coach and advise; trust, presence and accountability still need a person.
Amber matter holds its orbit, slate circles the inner disc, white falls in.Needs a human 80%AI helps 20%AI does it 0%
How exposed is it?

Still needs a human: 82/100↑ safer

The amber matter on the outside holds its orbit: that is the task time that still needs a person. The slate matter circling the inner disc is the work AI helps with. The white matter is the share AI can do; it spirals in and is gone over the edge.

The matter follows the job’s task split: 80% needs a human, 20% AI helps, 0% AI does it. Still needs a human: 82/100 ↑ safer. Will AI replace them? Nah.

What the AIs say

We asked four AI assistants the same question: will AI replace this job in the next 10 years? One word (Yes, Partly or No), then one sentence. Our own answer, from the data: Still needs a human: 82/100 ↑ safer. Will AI replace them? Nah.

ChatGPTPartly

AI may automate planning, diagnostics, and some setup tasks, but human installers will still be needed for on-site wiring, mounting, troubleshooting, and customer-specific work.

gpt-5.5-2026-04-23 · asked 2026-10-03
ClaudeNo

Electronic equipment installers perform hands-on physical tasks in varied, unpredictable environments that require manual dexterity, mobility, and real-world troubleshooting—capabilities current AI and robotics cannot reliably replicate at scale within a decade.

claude-sonnet-5 · asked 2026-10-03
GeminiPartly

While AI and robotics will automate diagnostic and planning tasks, the unpredictable physical environments and fine manual dexterity required for installation will keep human technicians essential over the next decade.

gemini-3.8-flash · asked 2026-10-03
PerplexityPartly

AI will automate some diagnostics and routine tasks, but physical installation, troubleshooting, and safety judgment will still require human electronic equipment installers.

sonar · asked 2026-10-03

Assistants answer from what they learned in training (Perplexity also searches the web), so they can be confidently wrong, and the same question can get a different answer tomorrow. Our score is built from task data and graded evidence. Answers collected through DataForSEO.

Cite this page

NeedsAHuman.com (2026). Will AI replace Electronic Equipment Installers and Repairers, Motor Vehicles? Nah. Still needs a human: 82/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/electronic-equipment-installers-and-repairers-motor-vehicles/ (accessed 3 October 2026).

Scores change with each , so cite the release. The data is open under : credit NeedsAHuman.com with a link. Open data · Press

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The badge updates itself with each release and links back to this page.

Sources

  • Tasks and work context: 31.0, ().
  • Jobs, pay and projections: US , and 2025–35.
  • How AI is used today: ; Microsoft Research, .
  • What AI can do: our task ratings ( r1) and the quality evidence register.
  • UK names and employment: coding index and .

How each score is built: methodology. Every figure on this page: open data. Release 2026-Q4.