US dataswitch to UK
Aircraft Cargo Handling Supervisors
calculating load weights for different aircraft compartments, directing ground crews in the loading and training new employees in areas. If that's your week, this page is about your job.
The honest answer
AI is already taking a real slice of the routine work here: calculating load weights for different aircraft compartments. That is a slice of tasks, not of you.
That slice is not coming back; the core of the job, directing ground crews in the loading, stays yours. The tools change hands, the accountability doesn't.
Your week, as this page understands it
Supervise and coordinate the activities of ground crew in the loading, unloading, securing, and staging of aircraft cargo or baggage. May determine the quantity and orientation of cargo and compute aircraft center of gravity. May accompany aircraft as member of flight crew and monitor and handle cargo in flight, and assist and brief passengers on safety and emergency procedures. Includes loadmasters. The job title says “aircraft cargo handling supervisors”. The real job is the part underneath: directing ground crews in the loading. 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 aircraft cargo handling supervisors is not one task. It is 6 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is directing ground crews in the loading, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 16%
- changing shape
- 17%
- staying human
- 66%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 30 out of 100 (25–36 allowing for uncertainty): low exposure, across 6 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 aircraft cargo handling supervisors 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.
- 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.
Calculating load weights for different aircraft compartments
This is reading one thing and writing another: load weights in, a record out. That is the shape today's tools are built for.
importance 5 · SupplementalSource: “Calculate load weights for different aircraft compartments, using charts and computers.” (O*NET task statement)
How this row was scored
Exposure score: 69 out of 100 (65–73 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; someone qualified has to answer for it.
The rating behind it: Compartment weight calculations already come from charts and computers; a qualified person still signs the load sheet.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Changing shape
1 taskTasks 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.
Determining the quantity and orientation of cargo
The software now makes the first pass at the quantity, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Determine the quantity and orientation of cargo, and compute an aircraft's center of gravity.” (O*NET task statement)
How this row was scored
Exposure score: 42 out of 100 (35–49 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; someone qualified has to answer for it.
The rating behind it: Center-of-gravity figures come from load software, though a qualified person confirms them against the actual load.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Staying human
4 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.
Training new employees in areas
This work happens in the physical world: new employees, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Train new employees in areas such as safety procedures or equipment operation.” (O*NET task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Training content is easy to write, but showing new staff safe practice happens on the ramp.
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 2/4 · how much data exists 3/4.
Directing ground crews in the loading
This work happens in the physical world: ground crews, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Direct ground crews in the loading, unloading, securing, or staging of aircraft cargo or baggage.” (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: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Directing a loading crew on the ramp means being there with them.
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 3/4.
Distributing cargo to maximize use of space
This work happens in the physical world: cargo, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Distribute cargo to maximize use of space.” (O*NET task statement)
How this row was scored
Exposure score: 33 out of 100 (26–40 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: Fitting cargo into the hold efficiently is a packing calculation software does well, but loading happens by hand.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Accompanying aircraft as a member of the flight crew to monitor and handle cargo in flight
This work happens in the physical world: aircraft, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Accompany aircraft as a member of the flight crew to monitor and handle cargo in flight.” (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: Flying with the cargo to look after it in the air means being on the aircraft.
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
- $58,170a 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
- 9,760in 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: load weights in, a record out. The rows above are exactly that shape: calculating load weights for different aircraft compartments and determining the quantity and orientation of cargo. What it cannot do is be there in the room, and that is still where ground crews 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: directing ground crews in the loading is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 16% of this job's task weight sits in rows the software is already learning, 17% in rows that change shape rather than disappear, and 66% in rows it is nowhere near. That is the position, measured across 6 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. Calculating load weights for different aircraft compartments 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 load weights, 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 ground crews 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 determining the quantity and orientation of cargo. 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 aircraft cargo handling supervisors (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was commercial pilots: only about 11% of its durable work is work you already do and the 2.1× pay gap is the market pricing a barrier. And on the numbers you do not need one. This job scores 30/100 here, with only 16% of the task list in the top band, and “train new employees in areas” 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.
Commercial Pilots
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already direct ground crews in the loading, unloading, securing, or staging of aircraft cargo…, and their equivalent is to check baggage or cargo to ensure that it has been loaded correctly. 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. The pay gap is the market pricing a barrier: $123,220 against your $58,170 is 2.12× (OEWS May 2025 (both)), and you would be crossing it holding about 10% of their durable work. A gap that size with an overlap that small is a wish, not a route.
Airline Pilots, Copilots, and Flight Engineers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already accompany aircraft as a member of the flight crew to monitor and handle…, and their equivalent is to direct activities of aircraft crews during flights. Across both published task lists that is about 7% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 7% of the durable side of that job. That is a different job, not a next step. The pay gap is the market pricing a barrier: $232,140 against your $58,170 is 3.99× (OEWS May 2025 (both)), and you would be crossing it holding about 7% of their durable work. A gap that size with an overlap that small is a wish, not a route.
Reservation and Transportation Ticket Agents and Travel Clerks
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already direct ground crews in the loading, unloading, securing, or staging of aircraft cargo…, and their equivalent is to check baggage and cargo and direct passengers to designated locations for loading. 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: $44,390 against your $58,170, 23.7% 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: 16% of its task weight, across 6 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 directing ground crews in the loading 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.
If you run a team doing this job
If you run a team doing this job, the conversation you owe them is the one on this page, and sooner than feels comfortable. Show them the ledger rather than a reassurance: the rows moving toward the software are calculating load weights for different aircraft compartments, and the rows that are not are where you want your people visible. Ask each of them to do the this-week move and bring the list to your next one-to-one. It turns a rumour into a piece of work, and it tells you which parts of your team's week are actually at stake. And say the thing out loud that a team lead usually leaves unsaid: a shrinking team is your exposure too, so do the move yourself as well.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Air transport operatives 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 Air transport operatives, Warehouse operatives, Elementary storage occupations n.e.c., Delivery operatives and Elementary storage supervisors. 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
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Anywhere in the US:
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No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for aircraft cargo handling supervisors, 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 16% of the work on this page is already inside what they can do.
7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.
The AI Authority is a general community about working with AI, not a course for aircraft cargo handling supervisors. 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.
Noted, and thank you. We’ll email you if a Space for aircraft cargo handling supervisors 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 Aircraft Cargo Handling Supervisors?
- Not as a job, but it is already doing parts of the work. Across the 6 official task statements scored for Aircraft Cargo Handling Supervisors (United States, SOC 53-1041), 16% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 30 out of 100 (range 25–36, band: low). 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 “Aircraft Cargo Handling Supervisors” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Calculate load weights for different aircraft compartments, using charts and computers” (69/100, high); “Determine the quantity and orientation of cargo, and compute an aircraft's center of gravity” (42/100, partial); “Distribute cargo to maximize use of space” (33/100, 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 “Aircraft Cargo Handling Supervisors” stay human?
- About 66% 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: “Accompany aircraft as a member of the flight crew to monitor and handle cargo in flight” (0/100, minimal); “Direct ground crews in the loading, unloading, securing, or staging of aircraft cargo or baggage” (7/100, minimal); “Train new employees in areas such as safety procedures or equipment operation” (20/100, low). 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 “Aircraft Cargo Handling Supervisors” do about AI?
- Start from the ledger rather than the headline: 16% of this job's weighted core work is exposed, and roughly 66% 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 Aircraft Cargo Handling Supervisors 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 6 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 2026-08-05.
- 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.