US dataswitch to UK
Loading and Moving Machine Operators, Underground Mining
handling high voltage sources and hang electrical cables, driving machines into piles of material blasted from working faces and operating levers to move conveyor booms or shovels so that mine contents. If that's your week, this page is about your job.
The honest answer
AI changes the edges of this job, not the middle: driving loaded shuttle cars to ramps and moving controls to discharge loads into mine cars or onto conveyors is work software can't reach.
What shifts is maintaining records of materials: the paper around the work, not the work.
Your week, as this page understands it
Operate underground loading or moving machine to load or move coal, ore, or rock using shuttle or mine car or conveyors. Equipment may include power shovels, hoisting engines equipped with cable-drawn scraper or scoop, or machines equipped with gathering arms and conveyor. The job title says “loading”, “moving machine operators” or “underground mining”: officially one job, several names. The real job is the part underneath: driving loaded shuttle cars to ramps and moving controls to discharge loads into mine cars or onto conveyors. 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 loading and moving machine operators, underground mining is not one task. It is 25 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is driving loaded shuttle cars to ramps and moving controls to discharge loads into mine cars or onto conveyors, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 3%
- changing shape
- 0%
- staying human
- 97%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 6 out of 100 (4–10 allowing for uncertainty): minimal exposure, across 25 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 loading and moving machine operators, underground mining 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.
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.
- 1 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 taskTasks 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.
Maintaining records of materials
This is reading one thing and writing another: records of materials in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Maintain records of materials moved.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 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: Keeping records of what has been moved is ordinary data work software does well.
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 0/4 · how much data exists 3/4.
Changing shape
0 tasksTasks 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.
Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.
Staying human
24 tasksTasks 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.
Driving loaded shuttle cars to ramps and moving controls to discharge loads into mine cars or onto conveyors
This work happens in the physical world: loaded shuttle cars, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Drive loaded shuttle cars to ramps and move controls to discharge loads into mine cars or onto conveyors.” (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: Driving a loaded shuttle car and discharging it is done from 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.
Examining roadway and clearing obstructions from the path of travel
This work happens in the physical world: roadway, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Examine roadway and clear obstructions from the path of travel.” (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: Examining the roadway and clearing what is in the way is 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 1/4.
Observing hand signals, grade stakes or other markings when operating machines
This work happens in the physical world: hand signals, grade stakes or other markings, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Observe hand signals, grade stakes, or other markings when operating machines.” (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: Watching for hand signals and markings while operating a machine happens in the seat.
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.
Handling high voltage sources and hang electrical cables
This work happens in the physical world: high voltage sources, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Handle high voltage sources and hang electrical cables.” (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: Handling high voltage sources and hanging cables underground is 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 2/4.
Controlling conveyors that run the entire length of shuttle cars to distribute loads as loading progresses
This work happens in the physical world: conveyors, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Control conveyors that run the entire length of shuttle cars to distribute loads as loading progresses.” (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 car’s conveyor to spread the load is done at the controls underground.
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.
Prying off loose material from roofs and moving it into the paths of machines
This work happens in the physical world: loose material, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Pry off loose material from roofs and move it into the paths of machines, using crowbars.” (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: Prying loose material off the roof with a crowbar is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Driving machines into piles of material blasted from working faces
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Drive machines into piles of material blasted from working faces.” (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: Driving a machine into a blasted pile is done from the operator’s seat.
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 fuel, service and performing safety checks on all equipment and repairing and replacing parts
This work happens in the physical world: fuel, service and performing safety checks, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Clean, fuel, service, and perform safety checks on all equipment, and repair and replace parts as 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: Cleaning, fueling, servicing and repairing mining equipment is hands-on 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.
Operating levers to move conveyor booms or shovels so that mine contents
This work happens in the physical world: levers, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Operate levers to move conveyor booms or shovels so that mine contents such as coal, rock, and ore can be placed into cars or onto conveyors.” (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: Working the levers that swing booms and shovels is machine operation.
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 15 tasks
Observing and recording car numbers
staying humanThis work happens in the physical world: car numbers, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Observe and record car numbers, carriers, customers, tonnages, and grades and conditions of material.” (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: Noting car numbers, tonnages and material grades is straightforward record keeping that software handles well.
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.
Reading written instructions or conferring with supervisors about schedules and materials
staying humanThe ratings behind this row put written instructions well outside what today's tools can do on their own.
importance 4 · SupplementalSource: “Read written instructions or confer with supervisors about schedules and materials to be moved.” (O*NET task statement)
How this row was scored
Exposure score: 37 out of 100 (30–44 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.
The rating behind it: Reading instructions and checking schedules with a supervisor is mostly information handling, though the conversation stays useful.
The five ratings: output a model can produce 2/4 · 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.
Measuring, weighing or verifying levels of rock, gravel or other excavated material to prevent equipment overloads
staying humanThis work happens in the physical world: levels of rock, gravel or other excavated material, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Measure, weigh, or verify levels of rock, gravel, or other excavated material to prevent equipment overloads.” (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: Weighing or gauging excavated material to avoid overloads is largely instrument reading, though someone must be there.
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.
Monitoring loading processes to ensure that materials are loaded according to specifications
staying humanThis work happens in the physical world: processes, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Monitor loading processes to ensure that materials are loaded according to specifications.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Checking that loads meet specification is a judgment call, but it is made underground at the machine.
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 2/4.
Directing other workers to move stakes
staying humanThis work happens in the physical world: other workers, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Direct other workers to move stakes, place blocks, position anchors or cables, or move materials.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (3–11 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Telling other workers where to place blocks, anchors and cables happens on the spot underground.
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 1/4 · how much data exists 2/4.
Moving trailing electrical cables clear of obstructions
staying humanThis work happens in the physical world: electrical cables clear of obstructions, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Move trailing electrical cables clear of obstructions, using rubber safety gloves.” (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: Moving heavy trailing cables clear of obstructions is 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 1/4.
Cleaning hoppers and cleaning spillage from tracks, walks, driveways and conveyor decking
staying humanThis work happens in the physical world: hoppers, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Clean hoppers, and clean spillage from tracks, walks, driveways, and conveyor decking.” (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 hoppers and clearing spillage is 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 1/4.
Oiling lubricate and adjusting conveyors, crushers and other equipment, using hand tools and lubricating equipment
staying humanThis work happens in the physical world: lubricate, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Oil, lubricate, and adjust conveyors, crushers, and other equipment, using hand tools and lubricating 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: work that happens in the physical world.
The rating behind it: Oiling and adjusting conveyors and crushers is hands-on 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.
Replacing hydraulic hoses, headlight bulbs and gathering-arm teeth
staying humanThis work happens in the physical world: hydraulic hoses, headlight bulbs and gathering-arm teeth, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Replace hydraulic hoses, headlight bulbs, and gathering-arm teeth.” (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: Replacing hoses, bulbs and gathering-arm teeth is hands-on 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 2/4.
Stopping gathering arms when cars are full
staying humanThis work happens in the physical world: arms, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Stop gathering arms when cars are full.” (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: Stopping the gathering arms when a car fills is machine operation.
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.
Advancing machines to gather material and convey it into cars
staying humanThis work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Advance machines to gather material and convey it into cars.” (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: Advancing the machine to gather material is machine operation.
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.
Signaling workers to move loaded cars
staying humanThis work happens in the physical world: workers, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Signal workers to move loaded cars.” (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: Signaling workers to move loaded cars happens face to face underground.
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.
Guiding and stopping cars
staying humanThis work happens in the physical world: cars, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Guide and stop cars by switching, applying brakes, or placing scotches, or wooden wedges, between wheels and rails.” (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: Guiding and braking cars, and wedging wheels, is 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 1/4.
Moving mine cars into position for loading and unloading
staying humanThis work happens in the physical world: mine cars, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Move mine cars into position for loading and unloading, using pinchbars inserted under car wheels to position cars under loading spouts.” (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: Levering mine cars into loading position is 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 1/4.
Pushing or riding cars down slopes
staying humanThis work happens in the physical world: cars down slopes, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Push or ride cars down slopes, or hook cars to cables and control cable drum brakes, to ease cars down inclines.” (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: Riding or pushing cars down slopes and controlling drum brakes is 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 1/4.
What this job pays, and how many people do it
- Median pay
- $74,500a 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
- 5,930in 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: records of materials in, a record out. The rows above are exactly that shape: maintaining records of materials. What it cannot do is be there in the room, and that is still where loaded shuttle cars 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: driving loaded shuttle cars to ramps and moving controls to discharge loads into mine cars or onto conveyors 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, 0% in rows that change shape rather than disappear, and 97% in rows it is nowhere near. That is the position, measured across 25 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. Maintaining records of materials 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 records of materials, 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 loaded shuttle cars 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 driving loaded shuttle cars to ramps and moving controls to discharge loads into mine cars or onto conveyors. 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 loading and moving machine operators, underground mining (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was excavating and loading machine and dragline operators, surface mining: only about 10% of its durable work is work you already do and it pays 22.9% less. And on the numbers you do not need one. This job scores 6/100 here, with only 3% of the task list in the top band, and “drive loaded shuttle cars to ramps and move controls to discharge loads…” 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.
Excavating and Loading Machine and Dragline Operators, Surface Mining
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “observe hand signals, grade stakes, or other markings when operating machines”. Across the whole of both lists that adds up to about 10% of the work in that job the software is not taking.
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: $57,430 against your $74,500, 22.9% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Hoist and Winch Operators
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already monitor loading processes to ensure that materials are loaded according to specifications, and their equivalent is to select loads or materials according to weight and size specifications. Across both published task lists that is about 8% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 8% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $56,450 against your $74,500, 24.2% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Continuous Mining Machine Operators
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already drive machines into piles of material blasted from working faces, and their equivalent is to drive machines into position at working faces. 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. It is a pay cut, in those words: $61,810 against your $74,500, 17.0% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
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 25 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 driving loaded shuttle cars to ramps and moving controls to discharge loads into mine cars or onto conveyors 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 Train and tram drivers 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 Train and tram drivers and Mining and quarry workers and related operatives. 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
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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.
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Noted, and thank you. We’ll email you if a Space for loading / moving machine operators / underground mining launches. Nothing else.
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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 Loading and Moving Machine Operators, Underground Mining?
- Not as a job, but it is already doing parts of the work. Across the 25 official task statements scored for Loading and Moving Machine Operators, Underground Mining (United States, SOC 47-5044), 3% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 6 out of 100 (range 4–10, 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 “Loading and Moving Machine Operators, Underground Mining” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Maintain records of materials moved” (75/100, high); “Observe and record car numbers, carriers, customers, tonnages, and grades and conditions of material” (38/100, low); “Read written instructions or confer with supervisors about schedules and materials to be moved” (37/100, low). 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 “Loading and Moving Machine Operators, Underground Mining” stay human?
- About 97% 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: “Push or ride cars down slopes, or hook cars to cables and control cable drum brakes, to ease cars down inclines” (0/100, minimal); “Observe hand signals, grade stakes, or other markings when operating machines” (0/100, minimal); “Move mine cars into position for loading and unloading, using pinchbars inserted under car wheels to position cars under loading spouts” (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 “Loading and Moving Machine Operators, Underground Mining” do about AI?
- Start from the ledger rather than the headline: 3% of this job's weighted core work is exposed, and roughly 97% 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 Loading and Moving Machine Operators, Underground Mining 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 25 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.
- 1 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.
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}
}Data as of release 2026-q4.1, published . 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.