Will AI replace Electric Motor, Power Tool, and Related Repairers?

This score cannot predict whether this occupation or any individual job will be replaced. It shows which tasks current and near-term AI can perform or accelerate, which tasks remain more durable, and where a worker can adapt. Employer decisions, demand, regulation, and how the role changes are outside the score.

What does a score of 22 mean for a Electric Motor, Power Tool, and Related Repairers?

It means that, weighted across the 20 tasks we analyzed for this role, the task mix sits at 22 on a 0–100 exposure scale — in the least-exposed quarter of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.

Which tasks in this role are most exposed to AI?

The highest-exposure tasks are: Record repairs required, parts used, and labor time. Exposure comes from the published, rubric-scored data release rather than being generated when you open this page.

Which parts of this job are most durable?

The most durable responsibilities are: Repair and rebuild defective mechanical parts in electric motors, generators, and related equipment, using hand tools and power tools; Lift units or parts such as motors or generators, using cranes or chain hoists, or signal crane operators to lift heavy parts or subassemblies; Disassemble defective equipment so that repairs can be made, using hand tools. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.

Is this score personalized to me?

No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.

Electric Motor, Power Tool, and Related Repairers

Repair, maintain, or install electric motors, wiring, or switches.

Also known as: Calibrator · Battery Charger · Battery Mechanic · Battery Repairer · Armature Rewinder · Battery Inspector

AI Task Exposure Score

Low exposure

More exposed than 20% of 968 occupations · Rank #749 (1 = most exposed)

This score estimates how exposed the tasks in a role are to current and near-term AI capabilities. It does not predict whether a specific person will lose a job.

Your free role snapshot

Start with the work, not the headline

This occupation baseline already contains different kinds of work. These are the two ends of its current task range and one useful action you can take now.

Most exposed task

Record repairs required, parts used, and labor time.

Automatable 65/100 exposure

Most durable task

Steam-clean polishing and buffing wheels to remove abrasives and bonding materials, and spray, brush, or recoat surfaces as necessary.

Durable 10/100 exposure

Useful next step

Make one change to the task mix

Protect the durable core of the role, then use AI to compress the routine work around it before that becomes a mandate.

Want this mapped to your actual week? Know what to strengthen, what to delegate to AI with review, and what to do over the next 7, 30, and 90 days.

Build my 7/30/90-day action plan — $9

Most exposed tasks

Highest structured exposure values in this role’s task mix — the work AI systems can already do most of.

Record repairs required, parts used, and labor time.65

Augmentable tasks

Work where AI assists rather than replaces — the productivity frontier of this role.

Read service guides to find information needed to perform repairs.45
Maintain stocks of parts.45
Set machinery for proper performance, using computers.40

Most durable tasks

Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.

Repair and rebuild defective mechanical parts in electric motors, generators, and related equipment, using hand tools and power tools.10
Lift units or parts such as motors or generators, using cranes or chain hoists, or signal crane operators to lift heavy parts or subassemblies.10
Disassemble defective equipment so that repairs can be made, using hand tools.10

Task exposure values and classifications are published, versioned estimates audited against the anchored rubric. This page reads them from the data release rather than generating them at request time. Bars show exposure contribution relative to this role’s task mix.

What this means

A score of 22 puts Electric Motor, Power Tool, and Related Repairers in the least-exposed quarter of analyzed occupations. In practice, exposure this level is about the mix: 1 of 20 analyzed tasks lean automatable, 3 augmentable, and 16 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.

Lower-exposure adjacent roles

No adjacent role in the current data release is at least 10 points lower with ≥50% skill overlap — we don’t label anything “safer” unless the data supports it.

Labor-market context

$56,210median wage
14,450employed
1,700annual openings
+3.5%projected growth

Context only — labor statistics are not inputs to the exposure score. See methodology.

Turn your actual week into a plan

Know which work to strengthen, what to delegate to AI with review, and what to do over the next 7, 30, and 90 days. Your $9 plan includes a confidence-rated personal score, task matrix, human moat, and only genuinely lower-exposure adjacent roles.

Build my 7/30/90-day action plan — $9

Related roles

Adjacent by skills or family — no exposure claim implied.

How this score was calculated

The score is the plain average of the AI-exposure values of this role’s 20 analyzed tasks (equal task weights in this release — no hidden factors):

Automatable 1 task, averaging 65/100 exposure
Augmentable 3 tasks, averaging 43/100 exposure
Durable 16 tasks, averaging 16/100 exposure

score = (1×65 + 3×43 + 16×16) ÷ 20 ≈ 22

Every task’s exposure value was scored against a published anchored rubric that scores tasks as actually performed — physical, in-person, and accountability requirements included (data release 2026.07.12-r2). The band (Low) is a corpus quartile; the percentile is tie-aware across all 968 occupations.

FAQ — Electric Motor, Power Tool, and Related Repairers

Will AI replace Electric Motor, Power Tool, and Related Repairers?: This score cannot predict whether this occupation or any individual job will be replaced. It shows which tasks current and near-term AI can perform or accelerate, which tasks remain more durable, and where a worker can adapt. Employer decisions, demand, regulation, and how the role changes are outside the score.
What does a score of 22 mean for a Electric Motor, Power Tool, and Related Repairers?: It means that, weighted across the 20 tasks we analyzed for this role, the task mix sits at 22 on a 0–100 exposure scale — in the least-exposed quarter of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.
Which tasks in this role are most exposed to AI?: The highest-exposure tasks are: Record repairs required, parts used, and labor time. Exposure comes from the published, rubric-scored data release rather than being generated when you open this page.
Which parts of this job are most durable?: The most durable responsibilities are: Repair and rebuild defective mechanical parts in electric motors, generators, and related equipment, using hand tools and power tools; Lift units or parts such as motors or generators, using cranes or chain hoists, or signal crane operators to lift heavy parts or subassemblies; Disassemble defective equipment so that repairs can be made, using hand tools. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.
Is this score personalized to me?: No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.

Score version jr-v1 · data release 2026.07.12-r2 · updated 2026-07-13 · baseline mapping: 20 of 20 tasks carry source-level provenance · methodology