EXPOSED
Acting is embodied performance, which generative text models can't do — but generative video and voice cloning attack exactly the commercial base that pays most working actors: background and stand-in work, corporate and industrial narration, ADR and dubbing, animated and game voice roles, and low-budget spot commercials. What survives is presence audiences knowingly pay for: live theater, stage and improv, on-camera roles where a recognizable human face carries the project, and motion-capture/performance-capture work that still needs a body. There is no license, so the only structural protection is SAG-AFTRA consent-and-compensation language on digital replicas, which is contractual rather than regulatory.
Roughly flat across the period, with year-to-year wobble.
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
+0.3% 57,000 → 57,100 on the projections basis
Growing, and only partly exposed
The BLS expects +0.3% more of these jobs by 2034, and at 48/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~6,300 openings a year on average, including replacing people who leave.
MimeActorComicExtraDoubleActressComedianMinstrelNarratorStand-InPerformerPuppeteerShow GirlSoubretteMonologistMovie StarTour ActorEntertainerIllusionistMovie ActorMovie ExtraRole PlayerScare ActorStunt Woman
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier A 12 reflects the split inside the actual job: cold reads, on-set adjustments to a director's note, eight-shows-a-week stage runs and mocap suit work still require a live performer, while the voiceover booth session, the dub pass, the background crowd tile and the industrial explainer read are already being generated or synthesized — so roughly half the paid task volume is under direct attack, not the craft ceiling.
Hands-on in uncontrolled environments At 14 the work happens on soundstages, location shoots in weather, fight and dance choreography, wire and harness work, and repertory stage floors where blocking, sightlines and a physical audience are the medium — it stops short of 18-20 only because a large share of credited work is captured in controlled studio or booth conditions rather than genuinely unpredictable field environments.
No licence, no signature requirement A 2 is the floor plus nothing: there is no state license, no board exam, no continuing education, and no legal barrier to a producer casting an untrained person or a synthetic performer — SAG-AFTRA membership and the 2023 digital-replica consent terms are bargained contract language enforceable only where the production is signatory, which non-union and AI-native shops simply avoid.
Meaningful discretion 7 sits at the bottom of real discretion: the actor owns interpretive choices — objective, tempo, where the emotional turn lands — but works inside a script, a director's final call, and a producer's approval, so no one else bears financial or safety consequences for the performer's judgment the way they would for a surgeon's or an engineer's.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (12/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (2/20) is whether the law requires a licensed human to sign. Trust premium (13/20) is whether buyers specifically pay for a person. Judgment and accountability (7/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 22 of this occupation's 48 points (46%).
Embodiment (14/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 66/100, still EXPOSED.
Right-of-publicity statutes with statutory damages and a consent-verification step — Tennessee ELVIS Act (2024), California AB 1836 (deceased personalities), and the federal NO FAKES Act as drafted — combined with E&O insurers requiring documented signed consent from an identified human performer for any digital replica. That makes a real, named human's executed release a condition of distribution, functionally a signature requirement even without a license.
Task-mix shift: acting genuinely has two tiers. If background, ADR, dubbing, and industrial narration are absorbed by synthesis, the residual occupation is on-camera lead work, live stage, and performance-capture where directorial collaboration and physical improvisation happen in the room. The measured resistance of the remaining job rises even as headcount falls — this is a composition effect, not protection for the same number of workers.
Mandatory synthetic-performer disclosure at point of sale — e.g. an FTC rule or state analogue requiring on-screen/AV labeling of AI-generated performers, plus platform-level 'human-performed' tagging (already partially in motion via the EU AI Act Art. 50 transparency duties and California AB 2602/1836). If audiences and brand advertisers can see which credits are human, the willingness to pay specifically for human casting becomes visible and priceable rather than invisible.
Contractual consolidation of the actor as a named creative principal — SAG-AFTRA successor agreements extending approval rights over replica use, dubbing likeness, and game performance to the individual performer, making the actor the party who authorizes or refuses specific downstream uses. If the performer holds a per-use veto rather than a blanket buyout, the role owns a consequential call.
Growth in live and location-bound formats that cannot be synthesized for a co-present audience — immersive theater, themed-entertainment live shows, arena and touring productions — plus continued studio reliance on physical performance capture for volumetric work. No policy lever; this rises only if consumer spend shifts toward co-presence.
The limit. Absent licensure, the ceiling is low: right-of-publicity law protects the likeness of people who already have a marketable name, not the median working actor whose income came from background, dubbing, and industrial narration. Disclosure and consent regimes govern replicas of specific performers; they do nothing about wholly synthetic performers with no underlying human, which is where the displacement of the commercial base actually happens. Realistic ceiling around 60-65, concentrated on recognizable and stage performers.
| Los Angeles-Long Beach-Anaheim, CA | 24,800 | — |
| New York-Newark-Jersey City, NY-NJ | 5,430 | — |
| Orlando-Kissimmee-Sanford, FL | 4,240 | — |
| Las Vegas-Henderson-North Las Vegas, NV | 680 | — |
| San Francisco-Oakland-Fremont, CA | 680 | — |
| Chicago-Naperville-Elgin, IL-IN | 610 | — |
| Atlanta-Sandy Springs-Roswell, GA | 570 | — |
| Boston-Cambridge-Newton, MA-NH | 510 | — |
Nikkei reports that an AI-generated actor has been cast in a lead role in a feature film, prompting opposition from Hollywood industry figures concerned about job losses.
Red Shark News reports SAG-AFTRA members ratified a new agreement containing AI provisions covering performers, with some members expressing dissent.
LAmag reports SAG-AFTRA members voted to approve a contract with the AMPTP that includes expanded AI protections for performers.
Variety reports SAG-AFTRA members voted to ratify a four-year contract that includes AI provisions and a pension plan merger.
France 24 reports that Hollywood studios and the actors' union reached an agreement including protections governing the use of AI in film and television production.
TheWrap reports on new AI provisions in SAG-AFTRA agreements governing the use of digital replicas and synthetic performers in relation to human actors.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.