US dataswitch to UK
Actors
collaborating with other actors as part of an ensemble, attending auditions and casting calls to audition for roles and sing or dancing during dramatic or comedic performances. If that's your week, this page is about your job.
The honest answer
AI changes the edges of this job, not the middle: portraying and interpreting roles, using speech, gestures and body movements, to entertain, inform or instructing radio, film, television or live audiences is work software can't reach.
What shifts is learning about characters in scripts and their relationships to each other to develop role interpretations: the overhead at the edges, not the middle you trained for.
Your week, as this page understands it
Play parts in stage, television, radio, video, or film productions, or other settings for entertainment, information, or instruction. Interpret serious or comic role by speech, gesture, and body movement to entertain or inform audience. May dance and sing. The job title says “actors”. The real job is the part underneath: portraying and interpreting roles, using speech, gestures and body movements, to entertain, inform or instructing radio, film, television or live audiences. 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 actors is not one task. It is 18 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is portraying and interpreting roles, using speech, gestures and body movements, to entertain, inform or instructing radio, film, television or live audiences, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 0%
- changing shape
- 11%
- staying human
- 89%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 10 out of 100 (7–15 allowing for uncertainty): minimal exposure, across 18 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 actors 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.
- 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.
- No median wage is published for this occupation in the OEWS release used here.
- 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
0 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.
Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.
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.
Learning about characters in scripts and their relationships to each other to develop role interpretations
The software now makes the first pass at characters, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Learn about characters in scripts and their relationships to each other to develop role interpretations.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Analyzing characters and their relationships is reading and writing about a text, which AI does capably as a starting point.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Writing original or adapted material
The software now makes the first pass at original, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · SupplementalSource: “Write original or adapted material for dramas, comedies, puppet shows, narration, or other performances.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Writing sketches, scripts and narration is text work where AI produces usable drafts that a writer then sharpens.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Staying human
16 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.
Portraying and interpreting roles, using speech, gestures and body movements, to entertain, inform or instructing radio, film, television or live audiences
This work happens in the physical world: roles, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Portray and interpret roles, using speech, gestures, and body movements, to entertain, inform, or instruct radio, film, television, or live audiences.” (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: Bringing a character to life through voice, gesture and movement needs a performer physically present.
The five ratings: output a model can produce 1/4 · 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 2/4.
Collaborating with other actors as part of an ensemble
This work happens in the physical world: other actors, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Collaborate with other actors as part of an ensemble.” (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: Ensemble work happens between people sharing a stage, so the other performers cannot be swapped for software.
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 4/4 · how much data exists 0/4.
Working closely with directors, other actors and playwrights to find the interpretation most suited to the role
This work happens in the physical world: directors, other actors and playwrights, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Work closely with directors, other actors, and playwrights to find the interpretation most suited to the role.” (O*NET task statement)
How this row was scored
Exposure score: 3 out of 100 (0–10 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: Finding the right reading of a role is worked out live with directors and writers in the room.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 1/4.
Studying and rehearsing roles from scripts
This work happens in the physical world: roles, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Study and rehearse roles from scripts to interpret, learn and memorize lines, stunts, and cues as directed.” (O*NET task statement)
How this row was scored
Exposure score: 7 out of 100 (0–14 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: AI can produce notes on a script, but learning lines and rehearsing moves is the actor's own physical work.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Performing humorous and serious interpretations of emotions
This work happens in the physical world: humorous, in a real place. Software cannot follow it there.
importance 5 · CoreSource: “Perform humorous and serious interpretations of emotions, actions, and situations, using body movements, facial expressions, and gestures.” (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: Conveying emotion through face and body is performance by a physical person, not something software supplies.
The five ratings: output a model can produce 1/4 · 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 2/4.
Attending auditions and casting calls to audition for roles
This work happens in the physical world: auditions, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Attend auditions and casting calls to audition for roles.” (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: Auditioning means presenting yourself, in person or on camera, for a casting decision about you.
The five ratings: output a model can produce 1/4 · 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 2/4.
Sing or dancing during dramatic or comedic performances
This work happens in the physical world: dramatic, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Sing or dance during dramatic or comedic performances.” (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: Singing and dancing in a performance is done by a body on a stage.
The five ratings: output a model can produce 1/4 · 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 2/4.
Working with other crew members responsible
This work happens in the physical world: other crew members responsible, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Work with other crew members responsible for lighting, costumes, make-up, and props.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (0–13 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: Costume fittings, makeup and prop handovers happen on set with the crew around you.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Show the other 8 tasks
Reading from scripts or books to narrate action or to inform or entertain audiences
staying humanThis work happens in the physical world: scripts, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Read from scripts or books to narrate action or to inform or entertain audiences, utilizing few or no stage props.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 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: Synthetic voices now narrate scripts convincingly, though live audience narration still calls for a person in the room.
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 1/4 · how much data exists 3/4.
Promoting productions using means, interviews about plays or movies
staying humanThis work happens in the physical world: productions, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Promote productions using means such as interviews about plays or movies.” (O*NET task statement)
How this row was scored
Exposure score: 11 out of 100 (4–18 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Publicity interviews work because audiences want the actor themselves; AI can only draft the talking points.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 3/4.
Preparing and performing action stunts for motion picture
staying humanThis work happens in the physical world: action stunts, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Prepare and perform action stunts for motion picture, television, or stage productions.” (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: Stunt work is physical action performed by a trained person on set.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Telling jokes, perform comic dances, songs and skits
staying humanThis work happens in the physical world: jokes, perform comic dances, songs and skits, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Tell jokes, perform comic dances, songs and skits, impersonate mannerisms and voices of others, contort face, and use other devices to amuse audiences.” (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: Comic timing in front of a live audience depends on a performer reading the room as they go.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 4/4 · how much data exists 2/4.
Introducing performances and performers to stimulate excitement and coordinating smooth transition of acts during events
staying humanThis work happens in the physical world: performances, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Introduce performances and performers to stimulate excitement and coordinate smooth transition of acts during events.” (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: Warming up a crowd and linking acts happens live on stage with the audience.
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.
Dressing in comical clown costumes and makeup
staying humanThis work happens in the physical world: comical clown costumes, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Dress in comical clown costumes and makeup, and perform comedy routines to entertain audiences.” (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: Wearing a costume and clowning for a crowd is entirely a physical, in-person performance.
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.
Performing original and stocking tricks of illusion to entertain and mystify audiences
staying humanThis work happens in the physical world: original, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Perform original and stock tricks of illusion to entertain and mystify audiences, occasionally including audience members as participants.” (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: Stage magic depends on a performer's hands and physical presence in front of the audience.
The five ratings: output a model can produce 1/4 · 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 2/4.
Constructing puppets and ventriloquist dummies
staying humanThis work happens in the physical world: puppets, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Construct puppets and ventriloquist dummies, and sew accessory clothing, using hand tools and machines.” (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: Building puppets and sewing costumes is handwork with tools and materials.
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 0/4 · how much data exists 1/4.
What this job pays, and how many people do it
- Median pay
- No median pay figure is published for this exact group, so there is none here. We would rather show you the gap than a number borrowed from somewhere else.No median pay figure is published for this exact occupation, so none is shown here.
- People doing this job
- 55,000in 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 the same call made over and over on characters, where the right answer is already known. The rows above are exactly that shape: learning about characters in scripts and their relationships to each other to develop role interpretations. What it cannot do is be there in the room, and that is still where roles 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
Start with what does not change: portraying and interpreting roles, using speech, gestures and body movements, to entertain, inform or instructing radio, film, television or live audiences is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 0% of this job's task weight sits in rows the software is already learning, 11% in rows that change shape rather than disappear, and 89% in rows it is nowhere near. That is the position, measured across 18 scored tasks. It is not a forecast about you.
So the thing worth your attention is not the job going away. It is the layer around it. Learning about characters in scripts and their relationships to each other to develop role interpretations is the part turning into software, and being the person who understands that layer is worth money.
This week: one thing
Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to characters, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.
- What you end up holding
- a straight answer about what is actually being rolled out, and when
- How long it takes
- ten minutes
If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether other actors are in scope or not. Nothing to log into, no license needed.
Over the next 90 days
Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near learning about characters in scripts and their relationships to each other to develop role interpretations. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.
Over the next 12 months
On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. 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 actors (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was dancers: only about 3% of its durable work is work you already do and there are far fewer of those jobs than of yours. And on the numbers you do not need one. This job scores 10/100 here, with only 0% of the task list in the top band, and “portray and interpret roles, using speech, gestures, and body movements, to entertain…” 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.
Dancers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already attend auditions and casting calls to audition for roles, and their equivalent is to audition for dance roles or for membership in dance companies. 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. This release publishes no median pay for that job, so I cannot show you what the move costs or pays. I do not recommend a move I cannot price. And it is a narrow door: about 8,130 of those jobs against 55,000 of yours (OEWS May 2025), 15% as many seats.
Camera Operators, Television, Video, and Film
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already prepare and perform action stunts for motion picture, television, or stage productions, and their equivalent is to operate television or motion picture cameras to record scenes for television broadcasts, advertising…. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% of the durable side of that job. That is a different job, not a next step. This release publishes no median pay for that job, so I cannot show you what the move costs or pays. I do not recommend a move I cannot price.
Music Directors and Composers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already learn about characters in scripts and their relationships to each other to develop…, and their equivalent is to study scores to learn the music in detail, and to develop interpretations. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% of the durable side of that job. That is a different job, not a next step. This release publishes no median pay for that job, so I cannot show you what the move costs or pays. I do not recommend a move I cannot price. And it is a narrow door: about 12,540 of those jobs against 55,000 of yours (OEWS May 2025), 23% as many seats.
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: 0% of its task weight, across 18 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like portraying and interpreting roles, using speech, gestures and body movements, to entertain, inform or instructing radio, film, television or live audiences arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
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 Actors, entertainers and presenters 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 Actors, entertainers and presenters. 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
Why there is no community here
Collab365, who build this site, run paid Spaces for a small number of subjects, and none of them is built for this job. We are not going to point you at the nearest one and call it a fit.
So the free services listed on this page are the whole answer, and it is the same answer we would give a friend.
Noted, and thank you. We’ll email you if a Space for actors 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 Actors?
- Not as a job, but it is already doing parts of the work. Across the 18 official task statements scored for Actors (United States, SOC 27-2011), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 10 out of 100 (range 7–15, band: minimal). 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 “Actors” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Learn about characters in scripts and their relationships to each other to develop role interpretations” (58/100, partial); “Write original or adapted material for dramas, comedies, puppet shows, narration, or other performances” (58/100, partial); “Read from scripts or books to narrate action or to inform or entertain audiences, utilizing few or no stage props” (32/100, low). 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 “Actors” stay human?
- About 89% 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: “Construct puppets and ventriloquist dummies, and sew accessory clothing, using hand tools and machines” (0/100, minimal); “Perform original and stock tricks of illusion to entertain and mystify audiences, occasionally including audience members as participants” (0/100, minimal); “Dress in comical clown costumes and makeup, and perform comedy routines to entertain audiences” (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 “Actors” do about AI?
- Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 89% 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 Actors 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 18 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
- No median pay figure is published for this exact occupation, so none is shown here.
- 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.
- No median wage is published for this occupation in the OEWS release used here.
- 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
- no pay figure published for this groupbls-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.