EXPOSED
This catch-all covers mascots, magicians, circus and variety acts, stunt performers, puppeteers, impersonators, live hosts and similar gig performers — work that happens in a body, in a room, in front of people, which current robotics cannot touch. The real exposure is not the act itself but the market around it: promo copy, poster design, backing tracks, social clips and character voices are already being generated cheaply, and corporate or event budgets that once bought a live performer increasingly buy synthetic content or licensed digital likenesses instead. Modal worker here is a freelancer with no license, no union protection, and income that depends on bookings rather than task output.
Headcount grew steadily across the period.
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.
BLS projection, 2024–2034
+6%
Percentage only. The projection counts a different population from the 16,550 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Growing, and only partly exposed
The BLS expects +6% more of these jobs by 2034, and at 58/100 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.
~4,400 openings a year on average, including replacing people who leave.
ClownComicFreakCowboyMascotMediumOratorPenmanAcrobatJugglerPalmistShowmanTumblerComedianMagicianPrompterSkydiverStuntmanAerialistHypnotistMesmeristPerformerPuppeteerShow Girl
The BLS uses Entertainers and Performers, Sports and Related Workers, All Other for work that doesn't fit any named occupation, so it covers roles that have little in common with each other. Two consequences worth knowing before you read anything below:
Holding it up: embodiment . Weakest point: liability shield .
Tasks largely resist digitisation A mascot working a stadium crowd, a magician doing close-up table work, an escape act or a stunt fall on a wire — the deliverable is a live body improvising against a real audience in real time, and nothing in a generative model performs a rope trick at a wedding reception, which is why this sits at 16 rather than lower; the trim comes from the pre-recorded and voiced-character corner of the code, where synthetic audio and video already substitute.
Hands-on in uncontrolled environments Fifty pounds of costume in July heat, harness rigging, fire and blade props, aerial apparatus, hotel ballrooms and parade routes and school gymnasiums you've never seen until load-in — uncontrolled venues with unknown floors and sightlines put this near the top of the band, short of 20 only because a share of the code works seated stages and controlled studio sets.
No licence, no signature requirement No state licence gates calling yourself a magician, mascot performer, or puppeteer; the only paperwork between you and a booking is a venue insurance certificate and sometimes a pyro or animal permit held by the producer, not you, so there is no credential a client is legally obliged to hire.
Meaningful discretion You read a room and adjust pacing, handle a heckler, cut a bit that isn't landing — real discretion inside a rehearsed act, but the running order, script, and safety choreography are usually fixed by a producer or stunt coordinator before you arrive, so the ambiguous high-stakes calls are not yours to own.
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 (16/20 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 (15/20) is whether buyers specifically pay for a person. Judgment and accountability (8/20) 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 25 of this occupation's 58 points (43%).
Embodiment (17/20) 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 73/100 — SAFE.
Venue and event-contract norms that explicitly price 'live human performer' as a distinct line item — e.g. buyer-side rules like the ones state fairs and school districts already use requiring a named performer on site, plus 'no AI likeness or synthetic performance' riders spreading from SAG-AFTRA's 2023 TV/Theatrical and 2024 Interactive Media agreements into non-union event and corporate booking templates via agencies and insurers
Insurer and venue requirements that stunt, aerial, fire, and animal acts be performed by a credentialed person carrying personal liability — e.g. state fire-marshal permits for pyro/fire performance, and event-cancellation underwriters demanding named certified riggers or stunt coordinators on the certificate of insurance
Task-mix shift as the promo tier collapses: if generated posters, backing tracks, social clips and voice work leave only the unrepeatable live-in-body tier, the residual job is more resistant even though total bookings fall — this dimension can rise while the occupation shrinks
State-level digital replica statutes (Tennessee ELVIS Act 2024, California AB 1836/2602, NY S7676B) extended to require documented, individually negotiated consent and named-agent representation before an event producer may use a performer's likeness or voice — making a signed human authorization a procedural prerequisite for the synthetic substitute rather than a free option
Child-safety and crowd-control duties formalized into the role: mandated-reporter designation or background-check-plus-training regimes for mascots and character performers at venues and schools, making the performer the accountable adult in the room rather than decoration
The limit. Embodiment is already near ceiling and task_resistance has little headroom; the score is high and the occupation is still exposed because the risk is demand-side, not capability-side. No lever here addresses bookings disappearing. Modal worker is a non-union freelancer, so union-derived AI riders and state replica statutes only help those with agents or named-talent contracts; mascots, hobbyist magicians and puppeteers are largely outside every mechanism listed.
| Los Angeles-Long Beach-Anaheim, CA | 3,120 | — |
| Orlando-Kissimmee-Sanford, FL | 1,890 | — |
| Las Vegas-Henderson-North Las Vegas, NV | 1,610 | — |
| New Orleans-Metairie, LA | 560 | — |
| Atlanta-Sandy Springs-Roswell, GA | 490 | — |
| North Port-Bradenton-Sarasota, FL | 490 | — |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 490 | — |
| San Diego-Chula Vista-Carlsbad, CA | 400 | — |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 58. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
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.