Will AI replace Costume Attendants?
Most of the work in Costume Attendants still leans on things AI struggles with — research rates its theoretical AI reach at only ~26%, and real-world use lower still.
O*NET-SOC 39-3092
How your 15 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a relatively low share of this job's tasks (~26%). By late 2025, real-world AI use had reached about 0% of its task activity (still rare). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~26%), real-world use (~0%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 15 tasks, ratedBased on real task-level AI scores — click to collapse
- Create worksheets for dressing lists, show notes, or costume checks.
- Distribute costumes or related equipment and keep records of item status.
- Examine costume fit on cast members and sketch or write notes for alterations.
- Check the appearance of costumes on stage or under lights to determine whether desired effects are being achieved.
- Study books, pictures, or examples of period clothing to determine styles worn during specific periods in history.
- Review scripts or other production information to determine a story's locale or period, as well as the number of characters and required costumes.
- Inventory stock to determine types or conditions of available costuming.
- Provide dressing assistance to cast members or assign cast dressers to assist specific cast members with costume changes.
- Arrange costumes in order of use to facilitate quick-change procedures for performances.
- Design or construct costumes or send them to tailors for construction, major repairs, or alterations.
- Clean and press costumes before and after performances and perform any minor repairs.
- Collaborate with production designers, costume designers, or other production staff to discuss and execute costume design details.
- Monitor, maintain, or secure inventories of costumes, wigs, or makeup, providing keys or access to assigned directors, costume designers, or wardrobe mistresses/masters.
- Purchase, rent, or requisition costumes or other wardrobe necessities.
- Return borrowed or rented items when productions are complete and return other items to storage.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.