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Paralegals and Legal Assistants

preparing affidavits or other documents, meeting with clients and other professionals to discuss details of cases and gathering and analyzing research data. If that's your week, this page is about your job.

The honest answer

This job is splitting in two: preparing, editing or reviewing legal documents, including legislation, briefs, pleadings, appeals, wills, contracts and real estate closing statements is work AI now does quickly and cheaply, and meeting with clients and other professionals to discuss details of cases is work it can't touch.

Your move: what you can actually do about this ↓

Which half fills your week decides your exposure. That is more in your control than it sounds.

Your week, as this page understands it

Assist lawyers by investigating facts, preparing legal documents, or researching legal precedent. Conduct research to support a legal proceeding, to formulate a defense, or to initiate legal action. The job title says “paralegals” or “legal assistants”: officially one job, two names. The real job is the part underneath: meeting with clients and other professionals to discuss details of cases. 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 paralegals and legal assistants 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 meeting with clients and other professionals to discuss details of cases, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI
49%
changing shape
8%
staying human
42%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 47 out of 100 (41–53 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 paralegals and legal assistants 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 2026-08-04. 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.

Shifting to AI

4 tasks

Tasks 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.

  • Preparing affidavits or other documents

    This is reading one thing and writing another: affidavits in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Prepare affidavits or other documents, such as legal correspondence, and organize and maintain documents in paper or electronic filing system.” (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: Affidavits and legal letters follow set formats, and document systems already generate and index them for a supervising lawyer.

    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.

  • Preparing, editing or reviewing legal documents, including legislation, briefs, pleadings, appeals, wills, contracts and real estate closing statements

    This is reading one thing and writing another: legal documents, including legislation, briefs, pleadings, appeals, wills in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Prepare, edit, or review legal documents, including legislation, briefs, pleadings, appeals, wills, contracts, and real estate closing statements.” (O*NET task statement)
    How this row was scored

    Exposure score: 72 out of 100 (65–79 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: Legal drafting from precedents produces solid first versions, though a lawyer still checks and signs off the result.

    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.

  • Gathering and analyzing research data

    This is reading one thing and writing another: research data in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Gather and analyze research data, such as statutes, decisions, and legal articles, codes, and documents.” (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: Statutes, judgments and legal commentary are published in bulk, making this the kind of research AI does fastest.

    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.

  • Investigating facts and law of cases and searching pertinent sources

    This is reading one thing and writing another: facts in, a record out. That is the shape today's tools are built for.

    importance 4 · Core
    Source: “Investigate facts and law of cases and search pertinent sources, such as public records and internet sources, to determine causes of action and to prepare cases.” (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: Case facts and law are searched in online records and databases, which is where AI research tools are strongest.

    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.

Changing shape

1 task

Tasks 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.

  • Filing pleadings with court clerks

    The software now makes the first pass at pleadings, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.

    importance 4 · Supplemental
    Source: “File pleadings with court clerks.” (O*NET task statement)
    How this row was scored

    Exposure score: 49 out of 100 (42–56 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: Court filing is mostly done through electronic systems, though deadlines and clerk requirements still catch people out.

    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

7 tasks

Tasks 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.

  • Preparing for trial by performing tasks

    This work happens in the physical world: trial, in a real place. Software cannot follow it there.

    importance 4 · Core
    Source: “Prepare for trial by performing tasks such as organizing exhibits.” (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: Exhibit lists can be assembled on screen, but getting a trial bundle ready involves physical materials and 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 0/4 · how much data exists 3/4.

  • Meeting with clients and other professionals to discuss details of cases

    The value here is that a specific person handles clients and stands behind it. That is earned, not computed.

    importance 4 · Core
    Source: “Meet with clients and other professionals to discuss details of cases.” (O*NET task statement)
    How this row was scored

    Exposure score: 12 out of 100 (8–16 allowing for uncertainty): minimal exposure, high confidence.

    Why it sits in this group: the value is that a specific person does it.

    The rating behind it: Case meetings work because a client trusts the person sitting with them and shares things they would not otherwise.

    The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.

  • Directing and coordinating law office activity

    This work happens in the physical world: law office activity, in a real place. Software cannot follow it there.

    importance 3 · Supplemental
    Source: “Direct and coordinate law office activity, including delivery of subpoenas.” (O*NET task statement)
    How this row was scored

    Exposure score: 19 out of 100 (12–26 allowing for uncertainty): minimal exposure, medium confidence.

    Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.

    The rating behind it: Running an office diary is easy to support, but serving subpoenas means someone travelling to hand documents over.

    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 1/4 · how much data exists 2/4.

  • Calling upon witnesses to testify at hearings

    The value here is that a specific person handles witnesses and stands behind it. That is earned, not computed.

    importance 3 · Supplemental
    Source: “Call upon witnesses to testify at hearings.” (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: Arranging witnesses involves persuading nervous people to turn up, which depends on personal contact rather than the scheduling.

    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.

  • Arbitrating disputes between parties and assisting in the real estate closing process

    The rules require a named, qualified person to answer for disputes, and that person cannot be a piece of software.

    importance 3 · Supplemental
    Source: “Arbitrate disputes between parties and assist in the real estate closing process, such as by reviewing title searches.” (O*NET task statement)
    How this row was scored

    Exposure score: 20 out of 100 (13–27 allowing for uncertainty): low exposure, medium confidence.

    Why it sits in this group: someone qualified has to answer for it; the value is that a specific person does it.

    The rating behind it: Settling a dispute and closing a property sale rely on qualified people taking responsibility and on trust between parties.

    The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 2/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.

Show the other 2 tasks

  • Keeping and monitoring legal volumes to ensure that the law library is up-to-date

    staying human

    This work happens in the physical world: legal volumes, in a real place. Software cannot follow it there.

    importance 3 · Supplemental
    Source: “Keep and monitor legal volumes to ensure that the law library is up-to-date.” (O*NET task statement)
    How this row was scored

    Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.

    Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.

    The rating behind it: Legal materials are increasingly online and updated automatically, though a physical library still needs someone tending the shelves.

    The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

  • Appraising and inventorying real and personal property for estate planning

    staying human

    This work happens in the physical world: real, in a real place. Software cannot follow it there.

    importance 3 · Supplemental
    Source: “Appraise and inventory real and personal property for estate planning.” (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: Listing assets is paperwork, but valuing property usually means someone going to look at it.

    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.

What this job pays, and how many people do it

Median pay
$62,890a 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
392,880in 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: legal documents, including legislation, briefs, pleadings, appeals, wills in, a record out. The rows above are exactly that shape: preparing, editing or reviewing legal documents and preparing affidavits or other documents. What it cannot do is be trusted in person, which is what clients run on: someone specific doing it and standing behind it. 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: preparing, editing or reviewing legal documents, including legislation, briefs, pleadings, appeals, wills, contracts and real estate closing statements is work today's tools do quickly and cheaply, and that is not coming back.

So, given all that: 49% of this job's task weight sits in rows the software is already learning, 8% in rows that change shape rather than disappear, and 42% 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 meeting with clients and other professionals to discuss details of cases, 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 legal documents, including legislation, briefs, pleadings, appeals, wills 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 legal documents, including legislation, briefs, pleadings, appeals, wills, 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 preparing, editing or reviewing legal documents, including legislation, briefs, pleadings, appeals, wills, contracts and real estate closing statements” 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 meeting with clients and other professionals to discuss details of cases 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 paralegals and legal assistants (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was customer service representatives: it is under the same pressure this job is and it pays 28.8% less. Your own job splits about 49/51: 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 “prepare for trial by performing tasks”, 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.

  • Customer Service Representatives

    Why it looked obvious: The reverse of the surviving CSR->paralegal route; tested for symmetry because the coverage score is deliberately directional.

    Why I am not recommending it: It fails: customer service reps -5.5% 2024-2034 (BLS EP). It is a pay cut: 44,770 against 62,890 is -18,120, a 28.8% cut. Demonstrates that the coverage score being directional is doing real work - a route that is honest one way is dishonest the other.

    Look at that job’s page anyway →

  • Real Estate Brokers

    Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already appraise and inventory real and personal property for estate planning, and their equivalent is to sell, for a fee, real estate owned by others. 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. And it is a narrow door: about 46,100 of those jobs against 392,880 of yours (OEWS May 2025), 12% as many seats.

    Look at that job’s page anyway →

  • Private Detectives and Investigators

    Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already call upon witnesses to testify at hearings, and their equivalent is to testify at hearings or court trials to present evidence. Across both published task lists that is about 3% of the durable work in that job.

    Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $51,220 against your $62,890, 18.6% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice. And it is a narrow door: about 35,580 of those jobs against 392,880 of yours (OEWS May 2025), 9% as many seats.

    Look at that job’s page anyway →

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: 49% 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: meeting with clients and other professionals to discuss details of cases 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.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Legal associate professionals 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 Legal associate professionals. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.

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.

No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for paralegal, and we are not going to point you at the nearest one and call it a fit.

The working behind that
RE-REVIEWED in routes.v3 against The AI Authority's actual published Problems; decline STANDS, and the reason is now content rather than the cap. Its Problems and its one course cover business documents, team workflow standards, client-data handling and approval gates. None of them addresses legal document review, privilege, citation checking or the consequences of getting a legal filing wrong. and §7.1 both flagged this mapping as the slice's most likely overreach and reading the Space confirms it. Kept in heldEntries with its evidence so the call stays inspectable.

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 49% of the work on this page is already inside what they can do.

Try The AI Authority free →

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 paralegal. 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 paralegals and legal assistants launches. Nothing else.

That did not look like an email address, so nothing was saved. Have another go below.

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No Space for paralegals and legal assistants yet. Should there be one?

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.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for paralegals and legal assistants existed, with researched problems, courses and people in the same boat, would you want in?

We use your email address for one thing: to tell you if a Space for paralegals and legal assistants launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

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 Paralegals and Legal Assistants?
Not as a job, but it is already doing parts of the work. Across the 12 official task statements scored for Paralegals and Legal Assistants (United States, SOC 23-2011), 49% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 47 out of 100 (range 41–53, 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 “Paralegals and Legal Assistants” can AI already do?
The highest-scoring tasks in release 2026-q4.1 are: “Gather and analyze research data, such as statutes, decisions, and legal articles, codes, and documents” (72/100, high); “Prepare, edit, or review legal documents, including legislation, briefs, pleadings, appeals, wills, contracts, and real estate closing statements” (72/100, high); “Investigate facts and law of cases and search pertinent sources, such as public records and internet sources, to determine causes of action and to prepare cases” (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 “Paralegals and Legal Assistants” stay human?
About 42% 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: “Meet with clients and other professionals to discuss details of cases” (12/100, minimal); “Direct and coordinate law office activity, including delivery of subpoenas” (19/100, minimal); “Arbitrate disputes between parties and assist in the real estate closing process, such as by reviewing title searches” (20/100, low). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
What should someone working in “Paralegals and Legal Assistants” do about AI?
Start from the ledger rather than the headline: 49% of this job's weighted core work is exposed, and roughly 42% 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 Paralegals and Legal Assistants 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.

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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}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

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.