Will AI replace Home Appliance Repairers?

Not as a job, but it is already doing parts of the work. Across the 29 official task statements scored for Home Appliance Repairers (United States, SOC 49-9031), 3% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 16 out of 100 (range 13–21, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.

Which tasks in “Home Appliance Repairers” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Contact supervisors or offices to receive repair assignments” (64/100, high); “Record maintenance and repair work performed on appliances” (56/100, partial); “Bill customers for repair work, and collect payment” (48/100, partial). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.

Which tasks in “Home Appliance Repairers” stay human?

About 76% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Measure, cut, and thread pipe, and connect it to feeder lines and equipment or appliances, using rules and hand tools” (0/100, minimal); “Light and adjust pilot lights on gas stoves, and examine valves and burners for gas leakage and specified flame” (0/100, minimal); “Install appliances such as refrigerators, washing machines, and stoves” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.

What should someone working in “Home Appliance Repairers” do about AI?

Start from the ledger rather than the headline: 3% of this job's weighted core work is exposed, and roughly 76% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.

How is the AI exposure score for Home Appliance Repairers calculated?

Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 29 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

US dataswitch to UK

Home Appliance Repairers

billing customers for repair work, servicing and repairing domestic electrical or gas appliances and responding to emergency calls. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: disassembling appliances so that problems can be diagnosed and repairs can be made is work software can't reach.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 3%
changing shape: 20%
staying human: 76%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 16 out of 100 (13–21 allowing for uncertainty): minimal exposure, across 29 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.

How we know this

What is measured: Every published task statement for home appliance repairers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

What shifts is contacting supervisors or offices to receive repair assignments. This page scores what today's tools actually do, not headlines.

Your week, as this page understands it

Repair, adjust, or install all types of electric or gas household appliances, such as refrigerators, washers, dryers, and ovens. The job title says “home appliance repairers”. The real job is the part underneath: disassembling appliances so that problems can be diagnosed and repairs can be made. That is the thing someone has to be right about.

The exposed part of this job is specific, and we won’t pretend it is coming back. But home appliance repairers is not one task. It is 29 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is disassembling appliances so that problems can be diagnosed and repairs can be made, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 3%
changing shape: 20%
staying human: 76%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

Your job, task by task

These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.

6 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Shifting to AI

1 task

Tasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.

Contacting supervisors or offices to receive repair assignments
This is reading one thing and writing another: supervisors in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Contact supervisors or offices to receive repair assignments.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Picking up job assignments from the office is simple scheduling communication software already automates.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.

Changing shape

5 tasks

Tasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.

Talking to customers or referring to work orders to establish the nature of appliance malfunctions
The software now makes the first pass at customers, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Talk to customers or refer to work orders to establish the nature of appliance malfunctions.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Working out the likely fault from a customer’s description or a work order is well-documented question-and-answer work.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Billing customers for repair work
The software now makes the first pass at customers, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Bill customers for repair work, and collect payment.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (44–52 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Working out the bill and taking payment is standard billing admin that software already handles.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Instructing customers regarding operation and care of appliances
The software now makes the first pass at customers regarding operation, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Instruct customers regarding operation and care of appliances, and provide information such as emergency service numbers.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (44–52 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Explaining how to use and look after an appliance is well-documented advice software can give clearly.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Providing repair cost estimates and recommending whether appliance repair or replacement is a better choice
The software now makes the first pass at repair cost estimates, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Provide repair cost estimates, and recommend whether appliance repair or replacement is a better choice.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (44–52 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Pricing a repair and comparing it to replacement cost is a documented calculation software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Recording maintenance and repairing work performed on appliances
The software now makes the first pass at maintenance, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Record maintenance and repair work performed on appliances.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Writing up what was repaired is routine record-keeping that software does reliably.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Staying human

23 tasks

Tasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.

Observing and examining appliances during operation to detect specific malfunctions
This work happens in the physical world: appliances during operation, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Observe and examine appliances during operation to detect specific malfunctions such as loose parts or leaking fluid.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (1–15 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Spotting a fault by watching and listening to a running machine needs you standing in front of it.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Referring to schematic drawings, product manuals and troubleshooting guides to diagnose and repair problems
This work happens in the physical world: schematic drawings, product manuals and troubleshooting guides, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Refer to schematic drawings, product manuals, and troubleshooting guides to diagnose and repair problems.” (O*NET task statement)
How this row was scored
Exposure score: 29 out of 100 (22–36 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Manuals and fault guides are well suited to software, but the repair itself still happens with hands on the appliance.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Disassembling appliances so that problems can be diagnosed and repairs can be made
This work happens in the physical world: appliances, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Disassemble appliances so that problems can be diagnosed and repairs can be made.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Taking an appliance apart requires tools and hands on the machine.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Replacing worn and defective parts
This work happens in the physical world: worn, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Replace worn and defective parts such as switches, bearings, transmissions, belts, gears, circuit boards, or defective wiring.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Swapping worn parts is hands-on work inside the machine.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.

Show the other 19 tasks

Maintaining stocks of parts used in on-site installation
staying human
This work happens in the physical world: stocks of parts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Maintain stocks of parts used in on-site installation, maintenance, and repair of appliances.” (O*NET task statement)
How this row was scored
Exposure score: 29 out of 100 (22–36 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Software can track and reorder van stock, but loading and checking the parts is still done by hand.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Taking measurements to determine if appliances will fit in installation locations
staying human
This work happens in the physical world: measurements, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Take measurements to determine if appliances will fit in installation locations, performing minor carpentry work when necessary to ensure proper installation.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Comparing dimensions is easy for software, but measuring the space and cutting timber happens on site.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Tracing electrical circuits, following diagrams and conducting tests with circuit testers and other equipment to locate shorts and grounds
staying human
This work happens in the physical world: electrical circuits, following diagrams and conducting tests, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Trace electrical circuits, following diagrams, and conduct tests with circuit testers and other equipment to locate shorts and grounds.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (3–17 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Tracing circuits means putting a test probe on real terminals in the machine.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Testing and examining gas pipelines and equipment to locate leaks and faulty connections
staying human
This work happens in the physical world: gas pipelines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Test and examine gas pipelines and equipment to locate leaks and faulty connections, and to determine the pressure and flow of gas.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (1–15 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Finding a gas leak means being there with a detector on the pipework.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Servicing and repairing domestic electrical or gas appliances
staying human
This work happens in the physical world: domestic electrical or gas appliances, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Service and repair domestic electrical or gas appliances, such as clothes washers, refrigerators, stoves, and dryers.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Servicing a washer, fridge or stove is physical repair work at the appliance.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Reassembling units after repairs are made
staying human
This work happens in the physical world: units after repairs are made, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Reassemble units after repairs are made, making adjustments and cleaning and lubricating parts as needed.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Rebuilding the unit after repair is hands-on assembly.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Cleaning and reinstalling parts
staying human
This work happens in the physical world: parts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean and reinstall parts.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Cleaning parts and refitting them is manual repair work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Observing and testing operation of appliances following installation
staying human
This work happens in the physical world: operation of appliances following installation, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Observe and test operation of appliances following installation, and make any initial installation adjustments that are necessary.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Running the appliance after fitting and tweaking it is hands-on commissioning.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Assembling new or reconditioned appliances
staying human
This work happens in the physical world: new or reconditioned appliances, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Assemble new or reconditioned appliances.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Assembling appliances is physical build work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Cleaning lubricate and touch up minor defects on newly installed or repaired appliances
staying human
This work happens in the physical world: lubricate, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean, lubricate, and touch up minor defects on newly installed or repaired appliances.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Cleaning, greasing and touching up finish is hands-on finishing work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Conserving recover and recycle refrigerants used in cooling systems
staying human
This work happens in the physical world: recover, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Conserve, recover, and recycle refrigerants used in cooling systems.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Recovering refrigerant requires certified equipment connected to the appliance in person.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Leveling refrigerators, adjust doors and connecting water lines to water pipes for ice makers and water dispensers
staying human
This work happens in the physical world: refrigerators, adjust doors and connecting water lines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Level refrigerators, adjust doors, and connect water lines to water pipes for ice makers and water dispensers, using hand tools.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Leveling a fridge and plumbing in a water line is physical installation work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Setting appliance thermostats and checking to ensure that they are functioning properly
staying human
This work happens in the physical world: appliance thermostats, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Set appliance thermostats, and check to ensure that they are functioning properly.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Setting and checking a thermostat is done at the appliance itself.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Leveling washing machines and connecting hoses to water pipes
staying human
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Level washing machines and connect hoses to water pipes, using hand tools.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Leveling a washing machine and attaching hoses is physical installation work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Installing gas pipes and water lines to connect appliances to existing gas lines or plumbing
staying human
This work happens in the physical world: gas pipes, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Install gas pipes and water lines to connect appliances to existing gas lines or plumbing.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Running gas pipe and water lines is physical pipework in the property.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Responding to emergency calls
staying human
This work happens in the physical world: emergency calls, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Respond to emergency calls for problems such as gas leaks.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Turning out to a gas leak means physically attending the property.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Installing appliances, refrigerators, washing machines and stoves
staying human
This work happens in the physical world: appliances, refrigerators, washing machines and stoves, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Install appliances such as refrigerators, washing machines, and stoves.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Installing a large appliance means lifting and connecting it in the customer’s home.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Lighting and adjusting pilot lights on gas stoves
staying human
This work happens in the physical world: pilot lights, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Light and adjust pilot lights on gas stoves, and examine valves and burners for gas leakage and specified flame.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Lighting pilots and checking burner flames is hands-on work at the stove.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Measuring, cutting
staying human
This work happens in the physical world: thread pipe, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Measure, cut, and thread pipe, and connect it to feeder lines and equipment or appliances, using rules and hand tools.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Cutting and threading pipe to connect an appliance is tool work in the home.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.

What this job pays, and how many people do it

Median pay: $50,990a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
People doing this job: 32,150in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)

What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.

Why this is shifting

The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: supervisors in, a record out. The rows above are exactly that shape: contacting supervisors or offices to receive repair assignments and talking to customers or referring to work orders to establish the nature of appliance malfunctions. What it cannot do is be there in the room, and that is still where appliances get done. Which is why this page talks about your tasks changing, not your job ending.

Your move

Over a pint: what I’d tell you if you were my friend

Start with what does not change: disassembling appliances so that problems can be diagnosed and repairs can be made is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 3% of this job's task weight sits in rows the software is already learning, 20% in rows that change shape rather than disappear, and 76% in rows it is nowhere near. That is the position, measured across 29 scored tasks. It is not a forecast about you.

So the thing worth your attention is not the job going away. It is the layer around it. Contacting supervisors or offices to receive repair assignments is the part turning into software, and being the person who understands that layer is worth money.

This week: one thing

Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to supervisors, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.

What you end up holding: a straight answer about what is actually being rolled out, and when
How long it takes: ten minutes

If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether appliances during operation is in scope or not. Nothing to log into, no license needed.

Over the next 90 days

Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near talking to customers or referring to work orders to establish the nature of appliance malfunctions. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.

Over the next 12 months

On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.

The roads out of here, and why I am not sending you down them

I looked at the obvious moves out of this job, and here is what I found.

I checked the 12 nearest US occupations to home appliance repairers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was rail car repairers: only about 6% of its durable work is work you already do. And on the numbers you do not need one. This job scores 16/100 here, with only 3% of the task list in the top band, and “talk to customers or refer to work orders to establish the nature…” is not work that hands over cleanly. None of them beats deepening what you already have.

How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.

3 moves I checked and rejected

These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.

Rail Car Repairers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already replace worn and defective parts, and their equivalent is to repair or replace defective or worn parts. Across both published task lists that is about 6% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Electric Motor, Power Tool, and Related Repairers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already disassemble appliances so that problems can be diagnosed and repairs can be made, and their equivalent is to disassemble defective equipment. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Industrial Machinery Mechanics
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already disassemble appliances so that problems can be diagnosed and repairs can be made, and their equivalent is to disassemble machinery or equipment to remove parts and make repairs. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →

What I’d stop worrying about

A friend tells you what not to spend fear on. This is that list.

The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 3% of its task weight, across 29 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like disassembling appliances so that problems can be diagnosed and repairs can be made arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Electricians and electrical fitters is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United Kingdom page →partial match

The other groups this work is counted across:

In UK official statistics this job is counted as Electricians and electrical fitters, Electrical service and maintenance mechanics and repairers and Air-conditioning and refrigeration installers and repairers. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.

Your route through this

Where to go next, and what it costs

Free, and complete

The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.

Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

Why there is no community here

Collab365, who build this site, run paid Spaces for a small number of subjects, and none of them is built for this job. We are not going to point you at the nearest one and call it a fit.

So the free services listed on this page are the whole answer, and it is the same answer we would give a friend.

Noted, and thank you. We’ll email you if a Space for home appliance repairers launches. Nothing else.

That did not look like an email address, so nothing was saved. Have another go below.

We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.

No Space for home appliance repairers yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for home appliance repairers existed, with researched problems, courses and people in the same boat, would you want in?

Your email

We use your email address for one thing: to tell you if a Space for home appliance repairers launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.

Questions people ask about this job

Will AI replace Home Appliance Repairers?: Not as a job, but it is already doing parts of the work. Across the 29 official task statements scored for Home Appliance Repairers (United States, SOC 49-9031), 3% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 16 out of 100 (range 13–21, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
Which tasks in “Home Appliance Repairers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Contact supervisors or offices to receive repair assignments” (64/100, high); “Record maintenance and repair work performed on appliances” (56/100, partial); “Bill customers for repair work, and collect payment” (48/100, partial). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “Home Appliance Repairers” stay human?: About 76% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Measure, cut, and thread pipe, and connect it to feeder lines and equipment or appliances, using rules and hand tools” (0/100, minimal); “Light and adjust pilot lights on gas stoves, and examine valves and burners for gas leakage and specified flame” (0/100, minimal); “Install appliances such as refrigerators, washing machines, and stoves” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
What should someone working in “Home Appliance Repairers” do about AI?: Start from the ledger rather than the headline: 3% of this job's weighted core work is exposed, and roughly 76% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
How is the AI exposure score for Home Appliance Repairers calculated?: Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 29 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

Where these numbers come from

Worth knowing about these figures

The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
6 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Task statements: onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
Task weights: onet-db (im-rt)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
Pay and employment: bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))

Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.

The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.

The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.

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Using these figures?

Cite this

Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.

Plain text

Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).

BibTeX

@misc{collab365futureproof2026q41,
  title        = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
  author       = {{Collab365}},
  year         = {2026},
  url          = {https://futureproof.collab365.com/data/2026-q4.1},
  note         = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.