US dataswitch to UK
Aerospace Engineers
formulating mathematical models or other methods of computer analysis, diagnosing performance problems by reviewing reports or documentation from customers or field engineers or by inspecting malfunctioning or damaged products and directing or coordinating activities of engineering or technical personnel involved in designing. 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: maintaining records of performance reports for future reference. That is a slice of tasks, not of you.
That slice is not coming back; the core of the job, planning or conducting experimental, environmental, operational or stress tests on models or prototypes of aircraft or aerospace systems or equipment, stays yours. The tools change hands, the accountability doesn't.
Your week, as this page understands it
Perform engineering duties in designing, constructing, and testing aircraft, missiles, and spacecraft. May conduct basic and applied research to evaluate adaptability of materials and equipment to aircraft design and manufacture. May recommend improvements in testing equipment and techniques. The job title says “aerospace engineers”. The real job is the part underneath: planning or conducting experimental, environmental, operational or stress tests on models or prototypes of aircraft or aerospace systems or equipment. 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 aerospace engineers is not one task. It is 16 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is planning or conducting experimental, environmental, operational or stress tests on models or prototypes of aircraft or aerospace systems or equipment, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 28%
- changing shape
- 25%
- staying human
- 47%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 42 out of 100 (36–49 allowing for uncertainty): partial exposure, across 16 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 aerospace engineers 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.
- 2 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
4 tasksTasks 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.
Writing technical reports or other documentation
This is reading one thing and writing another: technical reports in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Write technical reports or other documentation, such as handbooks or bulletins, for use by engineering staff, management, or customers.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 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: Technical handbooks and bulletins can be drafted to a usable standard from the underlying engineering data.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Evaluating product data or designing from inspections or reports for conformance to engineering principles
This is reading one thing and writing another: product data in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Evaluate product data or design from inspections or reports for conformance to engineering principles, customer requirements, environmental regulations, or quality standards.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 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: Checking product data and designs against stated requirements and standards is comparison work software does reliably.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Maintaining records of performance reports for future reference
This is reading one thing and writing another: records of performance reports in, a record out. That is the shape today's tools are built for.
importance 3 · CoreSource: “Maintain records of performance reports for future reference.” (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: Keeping performance reports filed and retrievable is record-keeping that software does better than a person.
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.
Evaluating and approving selection of vendors by studying past performance or new advertisements
This is reading one thing and writing another: selection of vendors in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Evaluate and approve selection of vendors by studying past performance or new advertisements.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 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: Comparing suppliers on past performance and documentation is analysis and write-up 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 1/4 · how much data exists 3/4.
Changing shape
4 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.
Formulating mathematical models or other methods of computer analysis
The software now makes the first pass at mathematical models, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Formulate mathematical models or other methods of computer analysis to develop, evaluate, or modify design, according to customer engineering requirements.” (O*NET task statement)
How this row was scored
Exposure score: 50 out of 100 (43–57 allowing for uncertainty): partial 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: Software can set up standard analysis models, but choosing the right model for a specific aerospace design needs an engineer.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Analyzing project requests, proposals or engineering data to determine feasibility, productibility, cost or production time of aerospace or aeronautical products
The software now makes the first pass at project requests, proposals or engineering data, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · CoreSource: “Analyze project requests, proposals, or engineering data to determine feasibility, productibility, cost, or production time of aerospace or aeronautical products.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial 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: Feasibility and cost analysis can be largely automated, though the call on whether something can actually be built stays with an engineer.
The five ratings: output a model can produce 2/4 · 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.
Developing design criteria for aeronautical or aerospace products or systems
The software now makes the first pass at design criteria, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · CoreSource: “Develop design criteria for aeronautical or aerospace products or systems, including testing methods, production costs, quality standards, environmental standards, or completion dates.” (O*NET task statement)
How this row was scored
Exposure score: 50 out of 100 (43–57 allowing for uncertainty): partial 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: Design criteria can be drafted from precedent, but setting the right targets for a new product needs engineering judgment.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Staying human
8 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.
Planning or conducting experimental, environmental, operational or stress tests on models or prototypes of aircraft or aerospace systems or equipment
This work happens in the physical world: experimental, environmental, operational or stress tests, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Plan or conduct experimental, environmental, operational, or stress tests on models or prototypes of aircraft or aerospace systems or equipment.” (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: Running stress and environmental tests means putting real hardware into a real test rig.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Formulating conceptual design of aeronautical or aerospace products or systems to meet customer requirements or conform to environmental regulations
The ratings behind this row put conceptual design of aeronautical well outside what today's tools can do on their own.
importance 4 · CoreSource: “Formulate conceptual design of aeronautical or aerospace products or systems to meet customer requirements or conform to environmental regulations.” (O*NET task statement)
How this row was scored
Exposure score: 28 out of 100 (21–35 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the five ratings behind the score, with no single dominant reason.
The rating behind it: Original concept design draws on judgment and experience that software can prompt but not replace.
The five ratings: output a model can produce 1/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Directing or coordinating activities of engineering or technical personnel involved in designing
The value here is that a specific person handles activities and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Direct or coordinate activities of engineering or technical personnel involved in designing, fabricating, modifying, or testing of aircraft or aerospace products.” (O*NET task statement)
How this row was scored
Exposure score: 17 out of 100 (10–24 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Directing engineering and technical staff depends on knowing the people and the shop floor.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Show the other 6 tasks
Evaluating biofuel performance specifications to determine feasibility for aerospace applications
changing shapeThe software now makes the first pass at biofuel performance specifications, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Evaluate biofuel performance specifications to determine feasibility for aerospace applications.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial 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: Comparing biofuel specifications against aerospace requirements is analysis software can largely do from published data.
The five ratings: output a model can produce 2/4 · 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.
Designing new or modifying existing aerospace systems to reduce polluting emissions
staying humanThe ratings behind this row put new or modifying existing aerospace systems well outside what today's tools can do on their own.
importance 2 · SupplementalSource: “Design new or modify existing aerospace systems to reduce polluting emissions, such as nitrogen oxide, carbon monoxide, or smoke emissions.” (O*NET task statement)
How this row was scored
Exposure score: 28 out of 100 (21–35 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the five ratings behind the score, with no single dominant reason.
The rating behind it: Redesigning systems to cut emissions is original engineering work where software supplies ideas, not finished designs.
The five ratings: output a model can produce 1/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Designing or engineering filtration systems that reduce harmful emissions
staying humanThe ratings behind this row put filtration systems well outside what today's tools can do on their own.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Design or engineer filtration systems that reduce harmful emissions.” (O*NET task statement)
How this row was scored
Exposure score: 28 out of 100 (21–35 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the five ratings behind the score, with no single dominant reason.
The rating behind it: Designing a working filtration system is original engineering that needs a person to carry it through.
The five ratings: output a model can produce 1/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Planning or coordinating investigation and resolution of customers' reports of technical problems with aircraft or aerospace vehicles
staying humanThe value here is that a specific person handles investigation and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Plan or coordinate investigation and resolution of customers' reports of technical problems with aircraft or aerospace vehicles.” (O*NET task statement)
How this row was scored
Exposure score: 23 out of 100 (16–30 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Coordinating a technical investigation with a customer mixes analysis with keeping that customer confident while it runs.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Diagnosing performance problems by reviewing reports or documentation from customers or field engineers or by inspecting malfunctioning or damaged products
staying humanThis work happens in the physical world: performance problems, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Diagnose performance problems by reviewing reports or documentation from customers or field engineers or by inspecting malfunctioning or damaged products.” (O*NET task statement)
How this row was scored
Exposure score: 22 out of 100 (15–29 allowing for uncertainty): low 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: Some faults show up clearly in reports, but many need someone looking at the damaged hardware itself.
The five ratings: output a model can produce 2/4 · 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 2/4.
Directing aerospace research and development programs
staying humanThe value here is that a specific person handles aerospace research and stands behind it. That is earned, not computed.
importance 3 · SupplementalSource: “Direct aerospace research and development programs.” (O*NET task statement)
How this row was scored
Exposure score: 17 out of 100 (10–24 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Running a research programme is about setting direction and backing people, which needs a person in charge.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
What this job pays, and how many people do it
- Median pay
- $134,960a 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
- 67,710in 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 performance reports in, a record out. The rows above are exactly that shape: maintaining records of performance reports for future reference and writing technical reports or other documentation. What it cannot do is be there in the room, and that is still where experimental, environmental, operational or stress tests 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
Your week is splitting in two, and which half fills it is the whole question. Maintaining records of performance reports for future reference is going; planning or conducting experimental, environmental, operational or stress tests on models or prototypes of aircraft or aerospace systems or equipment is not.
So, given all that: 28% of this job's task weight sits in rows the software is already learning, 25% in rows that change shape rather than disappear, and 47% in rows it is nowhere near. That is the position, measured across 16 scored tasks. It is not a forecast about you.
The occupation is an average and you are not, so the first job below is finding out where your own week actually sits.
This week: one thing
Print the task ledger above and put your own hours next to each row. Roughly, in pen, in one sitting. Then look at which group your hours actually pile up in. Twenty minutes, this week.
- What you end up holding
- your own week, on one page, sorted into what is shifting and what is not
- How long it takes
- about twenty minutes
If printing it isn’t practical: Read the rows off this page and write the same list on the back of an envelope. Same twenty minutes, same page, and it works just as well said out loud to someone who knows the job. The point is your hours next to the rows, not the paper it is on.
Over the next 90 days
Volunteer toward the durable end, visibly. Over the next ninety days put your hand up for the work in the bottom group (planning or conducting experimental, environmental, operational or stress tests on models or prototypes of aircraft or aerospace systems or equipment) and let people see you doing it. Not a new project: the same job, with your mix deliberately tilted. The point is that when the rota or the reorganisation comes, the version of you people picture is the one doing the part that stays.
Over the next 12 months
Claim a specialism at the durable end and let the other end go. Over a year, deliberately become the person who handles planning or conducting experimental, environmental, operational or stress tests on models or prototypes of aircraft or aerospace systems or equipment, and deliberately stop being the first choice for the rows in the top group. That trade costs something, because the exposed work is often the comfortable work. Decide it on purpose rather than by drift. 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 aerospace engineers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was electrical engineers: only about 3% of its durable work is work you already do and it pays 10.6% less. Your own job splits about 28/72: that share of the list sits in the top exposure band and the rest does not. On this evidence the honest move is inside the job rather than out of it. Become the person who owns “plan or conduct experimental, environmental, operational, or stress tests on models or…”, and let the exposed end go.
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.
Electrical Engineers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already evaluate product data or design from inspections or reports for conformance to engineering…, and their equivalent is to inspect completed installations and observe operations to ensure conformance to design and equipment…. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $120,630 against your $134,960, 10.6% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Mechanical Engineers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already direct or coordinate activities of engineering or technical personnel involved in designing, fabricating…, and their equivalent is to provide technical direction to other engineers or engineering support personnel. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $104,110 against your $134,960, 22.9% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Engineers, All Other
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already plan or conduct experimental, environmental, operational, or stress tests on models or prototypes…, and their equivalent is to develop or test photonic prototypes or models. Across both published task lists that is about 1% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 1% of the durable side of that job. That is a different job, not a next step.
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: 28% of its task weight, across 16 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The whole-job doom story
Nothing on this page says this job ends. It says the mix inside it moves. Half the rows above are unchanged or changing shape, and the plan is about which half your week sits in. That is a very different problem, and a solvable one.
Panic-buying a course
Do the twenty-minute sorting exercise first. Most people who buy a course before they have done it buy the wrong one, and the free services listed below will tell you the same thing without charging for it.
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 Aerospace engineers 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 Aerospace engineers and Mechanical engineers (professional). 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:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for aerospace engineers, 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 28% 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 aerospace engineers. 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 aerospace engineers launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.
No 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 Aerospace Engineers?
- Not as a job, but it is already doing parts of the work. Across the 16 official task statements scored for Aerospace Engineers (United States, SOC 17-2011), 28% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 42 out of 100 (range 36–49, band: partial). 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 “Aerospace Engineers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Maintain records of performance reports for future reference” (93/100, very high); “Write technical reports or other documentation, such as handbooks or bulletins, for use by engineering staff, management, or customers” (66/100, high); “Evaluate product data or design from inspections or reports for conformance to engineering principles, customer requirements, environmental regulations, or q…” (66/100, high). 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 “Aerospace Engineers” stay human?
- About 47% 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: “Plan or conduct experimental, environmental, operational, or stress tests on models or prototypes of aircraft or aerospace systems or equipment” (7/100, minimal); “Direct aerospace research and development programs” (17/100, minimal); “Direct or coordinate activities of engineering or technical personnel involved in designing, fabricating, modifying, or testing of aircraft or aerospace prod…” (17/100, 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 “Aerospace Engineers” do about AI?
- Start from the ledger rather than the headline: 28% of this job's weighted core work is exposed, and roughly 47% 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 Aerospace Engineers 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 16 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.
- 2 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-with-imputed)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
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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.