US dataswitch to UK
Training and Development Managers
analyzing training needs to develop new training programs or modify and improve existing programs, conducting orientation sessions and arranging on-the-job training for new hires and training instructors and supervisors in techniques and skills for training and dealing with employees. If that's your week, this page is about your job.
The honest answer
This job is splitting in two: developing and organizing training manuals is work AI now does quickly and cheaply, and conducting orientation sessions and arranging on-the-job training for new hires is work it can't touch.
Which half fills your week decides your exposure. The ledger below shows which rows you can move toward.
Your week, as this page understands it
Plan, direct, or coordinate the training and development activities and staff of an organization. The job title says “training” or “development managers”: officially one job, two names. The real job is the part underneath: conducting orientation sessions and arranging on-the-job training for new hires. 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 training and development managers is not one task. It is 12 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is conducting orientation sessions and arranging on-the-job training for new hires, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 51%
- changing shape
- 27%
- staying human
- 22%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 51 out of 100 (46–56 allowing for uncertainty): partial exposure, across 12 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 training and development managers 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
6 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.
Analyzing training needs to develop new training programs or modify and improve existing programs
This is reading one thing and writing another: needs in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Analyze training needs to develop new training programs or modify and improve existing programs.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Spotting skill gaps from company data and drafting a program plan is work AI does well from existing records.
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.
Evaluating instructor performance and the effectiveness of training programs
This is reading one thing and writing another: instructor performance in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Evaluate instructor performance and the effectiveness of training programs, providing recommendations for improvement.” (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: Feedback scores and course results are easy for software to crunch, though watching an instructor still means being in the room.
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.
Developing and organizing training manuals
This is reading one thing and writing another: manuals in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Develop and organize training manuals, multimedia visual aids, and other educational materials.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Writing manuals and building slide decks is exactly the kind of production current tools do quickly and competently.
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 4/4.
Preparing training budget for department or organization
This is reading one thing and writing another: budget in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Prepare training budget for department or organization.” (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: Budget building follows a repeatable method on numbers already sitting in company systems.
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
3 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.
Planning, developing and providing training and staff development programs
The software now makes the first pass at staff development programs, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Plan, develop, and provide training and staff development programs, using knowledge of the effectiveness of methods such as classroom training, demonstrations, on-the-job training, meetings, conferences, and workshops.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (36–44 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Designing the program is largely automatable, but standing up and actually delivering the training still needs a person present.
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 2/4 · how much data exists 3/4.
Conferring with management and conducting surveys to identify training needs based on projected production processes
The software now makes the first pass at management, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Confer with management and conduct surveys to identify training needs based on projected production processes, changes, and other factors.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (36–44 allowing for uncertainty): partial exposure, high confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Survey design and analysis are automatable; the part where you sit with managers and read the room is not.
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 2/4 · how much data exists 3/4.
Conducting or arranging for ongoing technical training and personal development classes for staff members
The software now makes the first pass at ongoing technical training and personal development classes, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Conduct or arrange for ongoing technical training and personal development classes for staff members.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Arranging classes is administrative, but running technical and development sessions still means a person in front of a group.
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 2/4 · how much data exists 3/4.
Staying human
3 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.
Conducting orientation sessions and arranging on-the-job training for new hires
This work happens in the physical world: orientation sessions, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Conduct orientation sessions and arrange on-the-job training for new hires.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (10–18 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: Orientation is a live session with new starters, so software can prepare it but not run it.
The five ratings: output a model can produce 1/4 · 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.
Training instructors and supervisors in techniques and skills for training and dealing with employees
This work happens in the physical world: instructors, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Train instructors and supervisors in techniques and skills for training and dealing with employees.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (10–18 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: Coaching people on how to handle employees depends on watching them practise and giving live feedback.
The five ratings: output a model can produce 1/4 · 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.
Coordinating established courses with technical and professional courses provided by community schools
The value here is that a specific person handles established courses and stands behind it. That is earned, not computed.
importance 3 · SupplementalSource: “Coordinate established courses with technical and professional courses provided by community schools, and designate training procedures.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 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: Lining up courses with local colleges depends on relationships and local knowledge that is not written down anywhere.
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 2/4 · how much data exists 2/4.
Show the other 2 tasks
Developing testing and evaluation procedures
shifting to AIThis is reading one thing and writing another: evaluation procedures in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Develop testing and evaluation procedures.” (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: Designing tests and assessment rules follows well-known patterns that software can draft from the course content.
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.
Reviewing and evaluating training and apprenticeship programs for compliance with government standards
shifting to AIThis is reading one thing and writing another: apprenticeship programs in, a record out. That is the shape today's tools are built for.
importance 3 · CoreSource: “Review and evaluate training and apprenticeship programs for compliance with government standards.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 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: Checking a program against written government standards is document comparison, with a person signing off afterwards.
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.
What this job pays, and how many people do it
- Median pay
- $133,000a 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
- 48,050in 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: instructor performance in, a record out. The rows above are exactly that shape: developing and organizing training manuals and analyzing training needs to develop new training programs or modify and improve existing programs. What it cannot do is be there in the room, and that is still where orientation sessions 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
The exposed part of your job is the biggest part, and I am not going to dress that up: developing and organizing training manuals is work today's tools do quickly and cheaply, and that is not coming back.
So, given all that: 51% of this job's task weight sits in rows the software is already learning, 27% in rows that change shape rather than disappear, and 22% in rows it is nowhere near. That is the position, measured across 12 scored tasks. It is not a forecast about you.
What you have that the software does not is conducting orientation sessions and arranging on-the-job training for new hires, plus the years of knowing when something looks wrong before you can say why. That is the raw material for everything below.
This week: one thing
Sit on the machine's side of the desk. Pick one real piece of instructor performance you would normally do yourself, let whatever software you already have take the first pass at it, and then go through what it produced and write down every single thing it got wrong. One evening this week. Do not fix anything yet. Just catch it.
- What you end up holding
- a written list of the machine’s mistakes, in your handwriting
- How long it takes
- an evening, or an hour if you pick one job rather than one client
If you can’t run software on your employer’s or your clients’ data: Do the same hunt on paper. Take one printed piece of instructor performance, work through it the way you always do, and mark every point where you made a call rather than followed a rule. Same evening, same list, nothing to log into and nobody to ask permission from. That list is the same artifact: it is the judgment written down.
Over the next 90 days
Change one sentence about what you do. Not on a CV. Out loud, to whoever pays you. From “my job is developing and organizing training manuals” to “I check what the software does and tell you what it means.” Your error list from this week is what makes that sentence true instead of a claim, so use it: show it once, to one person, inside the next ninety days. Same skills, priced as judgment rather than as typing.
Over the next 12 months
Walk toward the end of this job that answers for things, and get it recognised. Pick the one part of conducting orientation sessions and arranging on-the-job training for new hires you are already best at, and spend the year making it formal: a qualification, a named responsibility, a specialism people ask for by name. Price it honestly: that is evenings, it is months rather than weeks, and the seats are competitive because everyone in your position is looking at the same door. 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 training and development managers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was training and development specialists: only about 11% of its durable work is work you already do, it is under the same pressure this job is and it pays 47.9% less. Your own job splits about 51/49: 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, develop, and provide training and staff development programs, using knowledge of…”, 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.
Training and Development Specialists
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already analyze training needs to develop new training programs or modify and improve existing…, and their equivalent is to attend meetings or seminars to obtain information for use in training programs or…. Across both published task lists that is about 11% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 11% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. I will not move you off one melting floe onto another: 52% of its own task list already scores in the top exposure band (61/100 in this release), so the same software is eating it. It is a pay cut, in those words: $69,280 against your $133,000, 47.9% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Administrative Services Managers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already prepare training budget for department or organization, and their equivalent is to direct or coordinate the supportive services department of a business, agency, or organization. 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: $114,130 against your $133,000, 14.2% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Health Education Specialists
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already plan, develop, and provide training and staff development programs, using knowledge of the…, and their equivalent is to develop and present health education and promotion programs. 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. It is a pay cut, in those words: $64,070 against your $133,000, 51.8% 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: 51% of its task weight, across 12 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
“It’s too late for me to become something else”
You are not starting from zero, and the page shows why: conducting orientation sessions and arranging on-the-job training for new hires is work the software cannot do and you already do it. The move above is a repricing of what you know, not a new career. Nobody who has just left college has that.
“I should learn to code”
Almost certainly not. The value in your job is moving toward checking, deciding and answering for the output, not toward writing the software. A weekend of Python will not change your position; the error list from this week will.
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 developing and organizing training manuals, 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 Human resource managers and directors 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
In UK official statistics this job is counted as Human resource managers and directors. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.
Your route through this
Two honest options, and no deadline on either
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
A nearby route
There's no Space built for training and development managers yet.
Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.
The closest match is Microsoft Copilot Adopters, a community for the people who have to make Microsoft 365 Copilot actually useful in Word, Excel, Outlook and Teams. It overlaps with the part of your job that is growing: running Copilot adoption as a programme rather than a licence purchase, including how AI-assisted work gets reviewed. It only applies where your employer has Copilot. If that overlap isn't you, the free route below covers the same ground.
- Problem: “Our Copilot rollout stalled and we need an adoption plan we can afford”
- Problem: “I don’t know which work is worth doing in Copilot”
Try Microsoft Copilot Adopters free →
7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.
After the trial it is a paid community, and you get identical data either way. If the overlap above is not your job, the moves above cost nothing and stand on their own.
Noted, and thank you. We’ll email you if a Space for training and development managers 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 Training and Development Managers?
- Not as a job, but it is already doing parts of the work. Across the 12 official task statements scored for Training and Development Managers (United States, SOC 11-3131), 51% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 51 out of 100 (range 46–56, 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 “Training and Development Managers” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Develop and organize training manuals, multimedia visual aids, and other educational materials” (83/100, very high); “Develop testing and evaluation procedures” (75/100, high); “Prepare training budget for department or organization” (75/100, 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 “Training and Development Managers” stay human?
- About 22% 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: “Train instructors and supervisors in techniques and skills for training and dealing with employees” (14/100, minimal); “Conduct orientation sessions and arrange on-the-job training for new hires” (14/100, minimal); “Coordinate established courses with technical and professional courses provided by community schools, and designate training procedures” (35/100, 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 “Training and Development Managers” do about AI?
- Start from the ledger rather than the headline: 51% of this job's weighted core work is exposed, and roughly 22% 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 Training and Development Managers 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 12 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.