US dataswitch to UK
Private Detectives and Investigators
writing reports or case summaries to document investigations, exposing fraudulent insurance claims or stolen funds and obtaining and analyzing information on suspects. If that's your week, this page is about your job.
The honest answer
AI is already taking a real slice of the routine work here: writing reports or case summaries to document investigations. That is a slice of tasks, not of you.
That slice is not coming back; the core of the job, testifying at hearings or court trials to present evidence, stays yours. The tools change hands, the accountability doesn't.
Your week, as this page understands it
Gather, analyze, compile, and report information regarding individuals or organizations to clients, or detect occurrences of unlawful acts or infractions of rules in private establishment. The job title says “private detectives” or “investigators”: officially one job, two names. The real job is the part underneath: testifying at hearings or court trials to present evidence. 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 private detectives and investigators 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 testifying at hearings or court trials to present evidence, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 25%
- changing shape
- 17%
- staying human
- 58%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 32 out of 100 (27–38 allowing for uncertainty): low 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 private detectives and investigators 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.
- One task scored differently between repeat runs, so its range on this page is wider. We would rather show the wobble than hide it.
- 3 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
3 tasksTasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.
Writing reports or case summaries to document investigations
This is reading one thing and writing another: reports in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Write reports or case summaries to document investigations.” (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: Turning case notes and evidence into a clear written report is something AI drafts well, with the investigator checking it.
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.
Searching computer databases, credit reports, public records
This is reading one thing and writing another: computer databases, credit reports, public records in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Search computer databases, credit reports, public records, tax or legal filings, or other resources to locate persons or to compile information for investigations.” (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: Searching records and pulling a profile together is desk work, though matching the right person takes care.
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.
Investigating companies' financial standings or locating funds stolen by embezzlers, using accounting skills
This is reading one thing and writing another: companies' financial standings in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Investigate companies' financial standings, or locate funds stolen by embezzlers, using accounting skills.” (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: Tracing money through accounts and filings is document analysis that software handles well.
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
2 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.
Conducting personal background investigations, such as pre-employment checks
The software now makes the first pass at personal background investigations, 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 · CoreSource: “Conduct personal background investigations, such as pre-employment checks, to obtain information about an individual's character, financial status, or personal history.” (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: Background checks are mostly records work, but strict rules govern who may compile and use them.
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.
Obtaining and analyzing information on suspects
The software now makes the first pass at information, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Obtain and analyze information on suspects, crimes, or disturbances to solve cases, to identify criminal activity, or to gather information for court cases.” (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: Pulling together and making sense of information about a case is strong computer work, with some legwork attached.
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
9 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.
Testifying at hearings or court trials to present evidence
This work happens in the physical world: hearings, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Testify at hearings or court trials to present evidence.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Only the human witness can appear and give evidence under oath.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 4/4 · needs to be trusted in the moment 2/4 · how much data exists 1/4.
Conducting private investigations on a paid basis
This work happens in the physical world: private investigations, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Conduct private investigations on a paid basis.” (O*NET task statement)
How this row was scored
Exposure score: 9 out of 100 (0–19 allowing for uncertainty): minimal exposure, medium confidence, and it moved between repeat runs, so the range is widened.
Why it sits in this group: work that happens in the physical world; someone qualified has to answer for it.
The rating behind it: Running investigations for hire needs a state license, and much of the work happens out in the field.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 3/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Exposing fraudulent insurance claims or stolen funds
This work happens in the physical world: fraudulent insurance claims, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Expose fraudulent insurance claims or stolen funds.” (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: Spotting suspicious claim patterns is doable on data, but proving fraud usually needs field evidence.
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.
Observing and documenting activities of individuals to detect unlawful acts or to obtain evidence
This work happens in the physical world: activities of individuals, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Observe and document activities of individuals to detect unlawful acts or to obtain evidence for cases, using binoculars and still or video cameras.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Following someone with binoculars and a camera is done from a car or a doorway.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Questioning persons to obtain evidence for cases of divorce
This work happens in the physical world: persons, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Question persons to obtain evidence for cases of divorce, child custody, or missing persons or information about individuals' character or financial status.” (O*NET task statement)
How this row was scored
Exposure score: 4 out of 100 (0–11 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Getting people to open up depends on reading them face to face and earning their trust.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Show the other 4 tasks
Counting cash and reviewing transactions
staying humanThis work happens in the physical world: cash, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Count cash and review transactions, sales checks, or register tapes to verify amounts or to identify shortages.” (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: Reviewing till records and sales data is easy computer work, but counting the cash itself is hands-on.
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.
Conferring with establishment officials, security departments, police or postal officials to identify problems, provide information or receive instructions
staying humanThe value here is that a specific person handles establishment officials, security departments, police or postal officials and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Confer with establishment officials, security departments, police, or postal officials to identify problems, provide information, or receive instructions.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 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: Working relationships with police and company officials are built person to person over time.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Alerting appropriate personnel to suspects' locations
staying humanThis work happens in the physical world: appropriate personnel, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Alert appropriate personnel to suspects' locations.” (O*NET task statement)
How this row was scored
Exposure score: 25 out of 100 (18–32 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: Sending the alert is trivial; knowing where the subject actually is comes from being in the field.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Performing undercover operations
staying humanThis work happens in the physical world: undercover operations, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Perform undercover operations, such as evaluating the performance or honesty of employees by posing as customers or employees.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Posing as a customer or employee requires a real person on site.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 1/4.
What this job pays, and how many people do it
- Median pay
- $51,220a 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
- 35,580in 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: computer databases, credit reports, public records in, a record out. The rows above are exactly that shape: writing reports or case summaries to document investigations and searching computer databases, credit reports, public records. What it cannot do is be answerable: hearings need a named person the rules will accept, and software cannot be that person. 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. Writing reports or case summaries to document investigations is going; testifying at hearings or court trials to present evidence is not.
So, given all that: 25% of this job's task weight sits in rows the software is already learning, 17% in rows that change shape rather than disappear, and 58% 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 (testifying at hearings or court trials to present evidence) 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 testifying at hearings or court trials to present evidence, 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 private detectives and investigators (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was financial specialists, all other: only about 5% of its durable work is work you already do. And on the numbers you do not need one. This job scores 32/100 here, with only 25% of the task list in the top band, and “conduct personal background investigations” is not work that hands over cleanly. None of them beats deepening what you already have.
How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.
3 moves I checked and rejected
These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.
Financial Specialists, All Other
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already testify at hearings or court trials to present evidence, and their equivalent is to testify in court regarding investigation findings. 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.
Detectives and Criminal Investigators
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already testify at hearings or court trials to present evidence, and their equivalent is to testify in court and 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.
First-Line Supervisors of Police and Detectives
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already testify at hearings or court trials to present evidence, and their equivalent is to cooperate with court personnel and officials from other law enforcement agencies and testify…. 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. The pay gap is the market pricing a barrier: $106,040 against your $51,220 is 2.07× (OEWS May 2025 (both)), and you would be crossing it holding about 3% of their durable work. A gap that size with an overlap that small is a wish, not a route.
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: 25% 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 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.
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 private detectives / investigators, 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 25% 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 private detectives / investigators. 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 private detectives / investigators 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 Private Detectives and Investigators?
- Not as a job, but it is already doing parts of the work. Across the 14 official task statements scored for Private Detectives and Investigators (United States, SOC 33-9021), 25% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 32 out of 100 (range 27–38, band: low). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “Private Detectives and Investigators” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Write reports or case summaries to document investigations” (75/100, high); “Search computer databases, credit reports, public records, tax or legal filings, or other resources to locate persons or to compile information for investiga…” (66/100, high); “Investigate companies' financial standings, or locate funds stolen by embezzlers, using accounting skills” (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 “Private Detectives and Investigators” stay human?
- About 58% 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: “Perform undercover operations, such as evaluating the performance or honesty of employees by posing as customers or employees” (0/100, minimal); “Observe and document activities of individuals to detect unlawful acts or to obtain evidence for cases, using binoculars and still or video cameras” (0/100, minimal); “Testify at hearings or court trials to present evidence” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
- What should someone working in “Private Detectives and Investigators” do about AI?
- Start from the ledger rather than the headline: 25% of this job's weighted core work is exposed, and roughly 58% 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 Private Detectives and Investigators 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
About the data on this page
- One task scored differently between repeat runs, so its range on this page is wider. We would rather show the wobble than hide it.
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 3 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.