Will AI replace Mobile Heavy Equipment Mechanics, Except Engines?

Not as a job, but it is already doing parts of the work. Across the 20 official task statements scored for Mobile Heavy Equipment Mechanics, Except Engines (United States, SOC 49-3042), 10% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 14 out of 100 (range 11–18, 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 “Mobile Heavy Equipment Mechanics, Except Engines” stay human?

About 86% 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: “Fabricate needed parts or items from sheet metal” (0/100, minimal); “Adjust and maintain industrial machinery, using control and regulating devices” (0/100, minimal); “Adjust, maintain, and repair or replace subassemblies, such as transmissions and crawler heads, using hand tools, jacks, and cranes” (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 “Mobile Heavy Equipment Mechanics, Except Engines” do about AI?

Start from the ledger rather than the headline: 10% of this job's weighted core work is exposed, and roughly 86% 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 Mobile Heavy Equipment Mechanics, Except Engines 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 20 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

Mobile Heavy Equipment Mechanics, Except Engines

repairing and replacing damaged or worn parts, adjusting, maintaining and repairing rewire and troubleshooting electrical systems. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: repairing and replacing damaged or worn parts 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: 10%
changing shape: 4%
staying human: 86%

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

Whole-job exposure score 14 out of 100 (11–18 allowing for uncertainty): minimal exposure, across 20 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 mobile heavy equipment mechanics, except engines 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 2026-08-04. Read the full method.

What shifts is scheduling maintenance for industrial machines and equipment: the overhead at the edges, not the middle you trained for.

Your week, as this page understands it

Diagnose, adjust, repair, or overhaul mobile mechanical, hydraulic, and pneumatic equipment, such as cranes, bulldozers, graders, and conveyors, used in construction, logging, and mining. The job title says “mobile heavy equipment mechanics” or “except engines”: officially one job, two names. The real job is the part underneath: repairing and replacing damaged or worn parts. 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 mobile heavy equipment mechanics, except engines is not one task. It is 20 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is repairing and replacing damaged or worn parts, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 10%
changing shape: 4%
staying human: 86%

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 2026-08-04. 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.

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

2 tasks

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.

Reading and understanding operating manuals
This is reading one thing and writing another: manuals in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Read and understand operating manuals, blueprints, and technical drawings.” (O*NET task statement)
How this row was scored
Exposure score: 62 out of 100 (55–69 allowing for uncertainty): high 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: Manuals and drawings are text and diagrams, which software reads and explains very 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 0/4 · how much data exists 4/4.
Scheduling maintenance for industrial machines and equipment
This is reading one thing and writing another: maintenance in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Schedule maintenance for industrial machines and equipment, and keep equipment service records.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very 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: Maintenance scheduling and service records are what maintenance software already runs.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Changing shape

1 task

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.

Researching, ordering and maintaining parts inventory for services and repairs
The software now makes the first pass at parts inventory, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Research, order, and maintain parts inventory for services and repairs.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 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: Parts lookup and ordering are catalog work, though the shelves are still counted by hand.
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

17 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.

Repairing and replacing damaged or worn parts
This work happens in the physical world: damaged, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Repair and replace damaged or worn 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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Replacing a worn part is hands-on work 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 3/4.
Testing mechanical products and equipment after repair or assembly to ensure proper performance and compliance with manufacturers' specifications
This work happens in the physical world: mechanical products, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Test mechanical products and equipment after repair or assembly to ensure proper performance and compliance with manufacturers' specifications.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (6–14 allowing for uncertainty): minimal exposure, high 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: Running the machine to check the repair means being at the controls.
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.
Operating and inspecting machines or heavy equipment to diagnose defects
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Operate and inspect machines or heavy equipment to diagnose defects.” (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: Diagnostic software helps, but you have to run and inspect the machine to find the fault.
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.
Adjusting, maintaining and repairing or replacing subassemblies
This work happens in the physical world: subassemblies, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Adjust, maintain, and repair or replace subassemblies, such as transmissions and crawler heads, using hand tools, jacks, and cranes.” (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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Transmissions and crawler heads are lifted and fitted by people.
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 3/4.
Repairing rewire and troubleshooting electrical systems
This work happens in the physical world: rewire, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Repair, rewire, and troubleshoot electrical systems.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (6–14 allowing for uncertainty): minimal exposure, high 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 and rewiring a fault happens at the machine with test gear in hand.
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.
Overhauling and testing machines or equipment to ensure operating efficiency
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Overhaul and test machines or equipment to ensure operating efficiency.” (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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: An overhaul is done with hands 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 3/4.
Dismantling and reassembling heavy equipment using hoists and hand tools
This work happens in the physical world: heavy equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Dismantle and reassemble heavy equipment using hoists 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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Stripping down heavy equipment is physical work with tools.
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 3/4.

Show the other 10 tasks

Diagnosing faults or malfunctions to determine required repairs
staying human
This work happens in the physical world: faults, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Diagnose faults or malfunctions to determine required repairs, using engine diagnostic equipment such as computerized test equipment and calibration devices.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 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: Fault codes and test data are read well by software; hooking up the tools is the on-site part.
The five ratings: output a model can produce 3/4 · 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.
Directing workers who are assembling or disassembling equipment or cleaning parts
staying human
This work happens in the physical world: workers, in a real place. Software cannot follow it there.
importance 3 · Core
Source: “Direct workers who are assembling or disassembling equipment or cleaning parts.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (0–13 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Directing a crew on the shop floor means being on the shop floor.
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 2/4 · how much data exists 2/4.
Cleaning lubricate and performing other routine maintenance work on equipment and vehicles
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 perform other routine maintenance work on equipment and vehicles.” (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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Greasing and cleaning machinery is manual 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 3/4.
Examining parts for damage or excessive wear
staying human
This work happens in the physical world: parts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Examine parts for damage or excessive wear, using micrometers and gauges.” (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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Measuring wear on a part means holding both the part and the gauge.
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 3/4.
Assembling gear systems and align frames and gears
staying human
This work happens in the physical world: gear systems, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Assemble gear systems, and align frames and gears.” (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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Aligning gears and frames is done by hand and eye at 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 3/4.
Fitting bearings to adjust, repair or overhaul mobile mechanical, hydraulic and pneumatic equipment
staying human
This work happens in the physical world: bearings, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Fit bearings to adjust, repair, or overhaul mobile mechanical, hydraulic, and pneumatic equipment.” (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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Fitting bearings is precise physical 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 3/4.
Welding or soldering broken parts and structural members
staying human
This work happens in the physical world: broken parts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Weld or solder broken parts and structural members, using electric or gas welders and soldering 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: Welding is done with a torch in your hands.
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 parts by spraying them with grease solvent or immersing them in tanks of solvent
staying human
This work happens in the physical world: parts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean parts by spraying them with grease solvent or immersing them in tanks of solvent.” (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: Parts are sprayed and dipped by hand.
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.
Adjusting and maintaining industrial machinery
staying human
This work happens in the physical world: industrial machinery, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Adjust and maintain industrial machinery, using control and regulating devices.” (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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Adjusting machinery means working its controls 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 3/4.
Fabricating needed parts or items from sheet metal
staying human
This work happens in the physical world: needed parts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Fabricate needed parts or items from sheet metal.” (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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Cutting and forming sheet metal is workshop 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 3/4.

What this job pays, and how many people do it

Median pay: $65,510a 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: 176,600in 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: parts inventory in, a record out. The rows above are exactly that shape: scheduling maintenance for industrial machines and equipment and reading and understanding operating manuals. What it cannot do is be there in the room, and that is still where damaged gets 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: repairing and replacing damaged or worn parts is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 10% of this job's task weight sits in rows the software is already learning, 4% in rows that change shape rather than disappear, and 86% in rows it is nowhere near. That is the position, measured across 20 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. Scheduling maintenance for industrial machines and equipment 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 parts inventory, 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 mechanical products are 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 researching, ordering and maintaining parts inventory for services and repairs. 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 mobile heavy equipment mechanics, except engines (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was industrial machinery mechanics: only about 15% of its durable work is work you already do. And on the numbers you do not need one. This job scores 14/100 here, with only 10% of the task list in the top band, and “repair and replace damaged or worn parts” 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.

Industrial Machinery Mechanics
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already examine parts for damage or excessive wear, using micrometers and gauges, and their equivalent is to examine parts for defects. Across both published task lists that is about 15% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 15% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Farm Equipment Mechanics and Service Technicians
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already clean, lubricate, and perform other routine maintenance work on equipment and vehicles, and their equivalent is to clean and lubricate parts. Across both published task lists that is about 10% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 10% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. It is a pay cut, in those words: $56,550 against your $65,510, 13.7% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice. And it is a narrow door: about 37,870 of those jobs against 176,600 of yours (OEWS May 2025), 21% as many seats.
Look at that job’s page anyway →
Automotive Service Technicians and Mechanics
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already test mechanical products and equipment after repair or assembly to ensure proper performance…, and their equivalent is to test and adjust repaired systems to meet manufacturers' performance specifications. Across both published task lists that is about 9% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 9% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $50,620 against your $65,510, 22.7% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
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: 10% of its task weight, across 20 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 repairing and replacing damaged or worn parts 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 Rail and rolling stock builders and repairers 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:

Metal working production and maintenance fitters and technicians

In UK official statistics this job is counted as Rail and rolling stock builders and repairers and Metal working production and maintenance fitters and technicians. 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

No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for mobile heavy equipment mechanics / except engines, and we are not going to point you at the nearest one and call it a fit.

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 10% of the work on this page is already inside what they can do.

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The AI Authority is a general community about working with AI, not a course for mobile heavy equipment mechanics / except engines. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

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No Space for mobile heavy equipment mechanics / except engines 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.

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Collab365 launches new communities where the need is real. If one for mobile heavy equipment mechanics / except engines existed, with researched problems, courses and people in the same boat, would you want in?

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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 Mobile Heavy Equipment Mechanics, Except Engines?: Not as a job, but it is already doing parts of the work. Across the 20 official task statements scored for Mobile Heavy Equipment Mechanics, Except Engines (United States, SOC 49-3042), 10% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 14 out of 100 (range 11–18, 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 “Mobile Heavy Equipment Mechanics, Except Engines” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Schedule maintenance for industrial machines and equipment, and keep equipment service records” (93/100, very high); “Read and understand operating manuals, blueprints, and technical drawings” (62/100, high); “Research, order, and maintain parts inventory for services and repairs” (56/100, 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 “Mobile Heavy Equipment Mechanics, Except Engines” stay human?: About 86% 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: “Fabricate needed parts or items from sheet metal” (0/100, minimal); “Adjust and maintain industrial machinery, using control and regulating devices” (0/100, minimal); “Adjust, maintain, and repair or replace subassemblies, such as transmissions and crawler heads, using hand tools, jacks, and cranes” (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 “Mobile Heavy Equipment Mechanics, Except Engines” do about AI?: Start from the ledger rather than the headline: 10% of this job's weighted core work is exposed, and roughly 86% 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 Mobile Heavy Equipment Mechanics, Except Engines 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 20 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.
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 2026-08-04.
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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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.