US dataswitch to UK
Court Reporters and Simultaneous Captioners
recording verbatim proceedings of courts, taking notes in shorthand or using a stenotype or shorthand machine that prints letters on a paper tape and providing transcripts of proceedings upon request of judges. If that's your week, this page is about your job.
The honest answer
This job is splitting in two: providing transcripts of proceedings upon request of judges is work AI now does quickly and cheaply, and asking speakers to clarify inaudible statements 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
Use verbatim methods and equipment to capture, store, retrieve, and transcribe pretrial and trial proceedings or other information. Includes stenocaptioners who operate computerized stenographic captioning equipment to provide captions of live or prerecorded broadcasts for hearing-impaired viewers. The job title says “court reporters” or “simultaneous captioners”: officially one job, two names. The real job is the part underneath: asking speakers to clarify inaudible statements. 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 court reporters and simultaneous captioners is not one task. It is 14 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is asking speakers to clarify inaudible statements, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 38%
- changing shape
- 26%
- staying human
- 36%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 48 out of 100 (42–53 allowing for uncertainty): partial exposure, across 14 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 court reporters and simultaneous captioners is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
- 1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
Shifting to AI
5 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.
Providing transcripts of proceedings upon request of judges
This is reading one thing and writing another: transcripts of proceedings upon request of judges in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Provide transcripts of proceedings upon request of judges, lawyers, or the public.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (77–85 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: Fulfilling transcript orders is a records and delivery job software handles from start to finish.
The five ratings: output a model can produce 4/4 · 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.
Proofreading transcripts for correct spelling of words
This is reading one thing and writing another: transcripts in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Proofread transcripts for correct spelling of words.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (77–85 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: Checking spelling in a transcript is exactly the kind of proofreading software already does reliably.
The five ratings: output a model can produce 4/4 · 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.
Transcribing recorded proceedings in accordance with established formats
This is reading one thing and writing another: recorded proceedings in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Transcribe recorded proceedings in accordance with established formats.” (O*NET task statement)
How this row was scored
Exposure score: 72 out of 100 (68–76 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: Turning a recording into a formatted transcript is well-defined text work that automatic transcription does most of.
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 4/4.
Filing a legible transcript of records of a court case with the court clerk's office
This is reading one thing and writing another: a legible transcript of records of a court in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “File a legible transcript of records of a court case with the court clerk's office.” (O*NET task statement)
How this row was scored
Exposure score: 61 out of 100 (57–65 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: Filing a transcript with the clerk's office is a standard electronic submission.
The five ratings: output a model can produce 4/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · 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.
Recording verbatim proceedings of courts
The software now makes the first pass at verbatim proceedings of courts, 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: “Record verbatim proceedings of courts, legislative assemblies, committee meetings, and other proceedings, using computerized recording equipment, electronic stenograph machines, or stenomasks.” (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: Speech recognition now transcribes proceedings well, but an accredited reporter is still normally expected to make the official record.
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.
Verifying accuracy of transcripts by checking copies against original records of proceedings and accuracy of rulings by checking with judges
The software now makes the first pass at accuracy of transcripts, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · CoreSource: “Verify accuracy of transcripts by checking copies against original records of proceedings and accuracy of rulings by checking with judges.” (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; mistakes that are cheap to catch.
The rating behind it: Comparing a transcript against the record is automatic checking work, though confirming rulings means asking the judge.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Recording symbols on computer storage media and using computer aided transcription to translate and display them as text
The software now makes the first pass at symbols, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · SupplementalSource: “Record symbols on computer storage media and use computer aided transcription to translate and display them as text.” (O*NET task statement)
How this row was scored
Exposure score: 49 out of 100 (45–53 allowing for uncertainty): partial 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: Translating machine shorthand into readable text is what the transcription software is built to do.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Staying human
5 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.
Asking speakers to clarify inaudible statements
This work happens in the physical world: speakers, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Ask speakers to clarify inaudible statements.” (O*NET task statement)
How this row was scored
Exposure score: 9 out of 100 (2–16 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Asking a speaker to repeat something means interrupting a live proceeding from inside the room.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 1/4.
Filing and storing shorthand notes of court session
This work happens in the physical world: shorthand notes of court session, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “File and store shorthand notes of court session.” (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: Filing and storing notes is simple records work with a physical handling element.
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.
Responding to requests during court sessions to read portions of the proceedings already
This work happens in the physical world: requests during court sessions, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Respond to requests during court sessions to read portions of the proceedings already recorded.” (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 same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Searching the record is instant for software, but reading it back happens live in the courtroom.
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 1/4 · how much data exists 3/4.
Show the other 4 tasks
Typing court orders for judges
shifting to AIThis is reading one thing and writing another: court orders in, a record out. That is the shape today's tools are built for.
importance 5 · SupplementalSource: “Type court orders for judges.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (77–85 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: Typing a court order from a judge's direction is standard document production from a familiar template.
The five ratings: output a model can produce 4/4 · 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.
Recording depositions and other proceedings for attorneys
changing shapeThe software now makes the first pass at depositions, 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 4 · SupplementalSource: “Record depositions and other proceedings for attorneys.” (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: Depositions are often recorded remotely and automatic transcription is strong, but a certified reporter usually still produces the transcript.
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.
Logging and storing exhibits from court proceedings
staying humanThis work happens in the physical world: exhibits, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Log and store exhibits from court proceedings.” (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: Logging exhibits is straightforward record-keeping, but the exhibits themselves have to be physically handled and stored.
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.
Taking notes in shorthand or using a stenotype or shorthand machine that prints letters on a paper tape
staying humanThis work happens in the physical world: notes, in a real place. Software cannot follow it there.
importance 5 · SupplementalSource: “Take notes in shorthand or use a stenotype or shorthand machine that prints letters on a paper tape.” (O*NET task statement)
How this row was scored
Exposure score: 11 out of 100 (7–15 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Keying shorthand on a stenotype machine is a trained physical skill performed live in the room.
The five ratings: output a model can produce 2/4 · 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.
What this job pays, and how many people do it
- Median pay
- $72,420a 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
- 12,870in 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: transcripts of proceedings upon request of judges in, a record out. The rows above are exactly that shape: providing transcripts of proceedings upon request of judges and proofreading transcripts for correct spelling of words. What it cannot do is be there in the room, and that is still where speakers 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. Providing transcripts of proceedings upon request of judges is going; asking speakers to clarify inaudible statements is not.
So, given all that: 38% of this job's task weight sits in rows the software is already learning, 26% in rows that change shape rather than disappear, and 36% in rows it is nowhere near. That is the position, measured across 14 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 (asking speakers to clarify inaudible statements) 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 asking speakers to clarify inaudible statements, 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 court reporters and simultaneous captioners (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was bailiffs: only about 5% of its durable work is work you already do and it pays 21.8% less. Your own job splits about 38/62: 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 “ask speakers to clarify inaudible statements”, 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.
Bailiffs
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already log and store exhibits from court proceedings, and their equivalent is to screen, control, and handle evidence and exhibits during court proceedings. 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: $56,600 against your $72,420, 21.8% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Judges, Magistrate Judges, and Magistrates
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already type court orders for judges, and their equivalent is to supervise other judges, court officers, and the court's administrative staff. 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. The pay gap is the market pricing a barrier: $153,990 against your $72,420 is 2.13× (OEWS May 2025 (both)), and you would be crossing it holding about 5% of their durable work. A gap that size with an overlap that small is a wish, not a route.
Paralegals and Legal Assistants
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already file a legible transcript of records of a court case with the court…, and their equivalent is to file pleadings with court clerks. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $62,890 against your $72,420, 13.2% 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: 38% of its task weight, across 14 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 Company secretaries and administrators 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 Company secretaries and administrators and Personal assistants and other secretaries. 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 court reporters / simultaneous captioners, 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 38% 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 court reporters / simultaneous captioners. 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 court reporters / simultaneous captioners 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 Court Reporters and Simultaneous Captioners?
- Not as a job, but it is already doing parts of the work. Across the 14 official task statements scored for Court Reporters and Simultaneous Captioners (United States, SOC 27-3092), 38% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 48 out of 100 (range 42–53, 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 “Court Reporters and Simultaneous Captioners” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Provide transcripts of proceedings upon request of judges, lawyers, or the public” (81/100, very high); “Proofread transcripts for correct spelling of words” (81/100, very high); “Type court orders for judges” (81/100, very 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 “Court Reporters and Simultaneous Captioners” stay human?
- About 36% 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: “Ask speakers to clarify inaudible statements” (9/100, minimal); “Take notes in shorthand or use a stenotype or shorthand machine that prints letters on a paper tape” (11/100, minimal); “Respond to requests during court sessions to read portions of the proceedings already recorded” (28/100, 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 “Court Reporters and Simultaneous Captioners” do about AI?
- Start from the ledger rather than the headline: 38% of this job's weighted core work is exposed, and roughly 36% 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 Court Reporters and Simultaneous Captioners 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 14 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.
Where these numbers come from
Worth knowing about these figures
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
Using these figures?
Cite this
Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.
Plain text
Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).
BibTeX
@misc{collab365futureproof2026q41,
title = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
author = {{Collab365}},
year = {2026},
url = {https://futureproof.collab365.com/data/2026-q4.1},
note = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}Data as of release 2026-q4.1, published . Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.