Share and intensity of work current AI systems can materially affect.
SOC 39-3092
Costume Attendants AI displacement risk
Costume attendants dress cast members, choreograph quick changes, and keep costumes performance-ready. Inventory software tracks garments digitally, but the thirty-second quick change, the emergency repair minutes before curtain, and the nightly care of fragile garments are backstage physical work.
Likely potential for exposed tasks to move to software after workflow integration.
Live performance is the moat: costumes fail in real time and are fixed in real time by a person who is there. Digital tracking helps organize the workflow without touching its hands-on core.
Distribution
Where Costume Attendants sits across 620 tracked roles
Displacement pressure 20 — higher than 23% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
21 O*NET task statements matched to SOC 39-3092. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $50,400 (May 2025, US national). The latest BLS row matched SOC 39-3092.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Costume Attendants
SOC 39-3092 places this role in the paper's all-other occupation group. These group-level outcomes do not change the 20/100 role score and are not an occupation forecast.
+1.1% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +1.6% GDP and 3.9% unemployment.
+5.9% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +8.3% GDP and 4.6% unemployment.
+33.6% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Costume Attendants
The current evidence import matched 21 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks21
SOC39-3092
- Core task / ID 9627
Create worksheets for dressing lists, show notes, or costume checks.
- Core task / ID 20898
Provide dressing assistance to cast members or assign cast dressers to assist specific cast members with costume changes.
- Core task / ID 9616
Arrange costumes in order of use to facilitate quick-change procedures for performances.
- Core task / ID 9621
Design or construct costumes or send them to tailors for construction, major repairs, or alterations.
- Core task / ID 9629
Examine costume fit on cast members and sketch or write notes for alterations.
- Core task / ID 9615
Distribute costumes or related equipment and keep records of item status.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Provide dressing assistance for quick changes
Exposure 14, automation 4%, augmentation 30%.
O*NET evidence: Provide dressing assistance to cast members or assign cast dressers to assist specific ... (ID 20898)
Arrange costumes in order of use
Exposure 24, automation 10%, augmentation 36%.
O*NET evidence: Arrange costumes in order of use to facilitate quick-change procedures for performances. (ID 9616)
Examine costume fit and note alterations
Exposure 26, automation 10%, augmentation 44%.
O*NET evidence: Examine costume fit on cast members and sketch or write notes for alterations. (ID 9629)
Clean, press, and repair costumes
Exposure 16, automation 6%, augmentation 32%.
O*NET evidence: Clean and press costumes before and after performances and perform any minor repairs. (ID 9618)
TaskExposureAutomationAugmentation
Provide dressing assistance for quick changes144%30%
Arrange costumes in order of use2410%36%
Examine costume fit and note alterations2610%44%
Clean, press, and repair costumes166%32%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
LowWardrobe Supervisor
Training horizon: 6-12 months. Skill overlap 66. Wage preservation signal 116.
- Lead dressing crews
- Own costume inventories
- Coordinate with designers
credentialed transition
LowCostume Shop Technician
Training horizon: 12-24 months. Skill overlap 58. Wage preservation signal 110.
- Master construction and alteration
- Learn period garment techniques
- Build a shop portfolio
Comparison guides
Compare the next move before you commit
6-12 months
Costume Attendants to Wardrobe Supervisor
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Costume Attendants into Wardrobe Supervisor.
12-24 months
Costume Attendants to Costume Shop Technician
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Costume Attendants into Costume Shop Technician.
What the AI risk score means for Costume Attendants
The displacement pressure score for Costume Attendants is 20. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Arrange costumes in order of use carries 10% automation pressure, while Examine costume fit and note alterations carries 44% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $50,400 (May 2025, US national). Employment context: Wardrobe logistics role behind live performance. Typical education: High school plus theater experience; sewing skills valued.
Wage vulnerability is 56, while transition feasibility is 60. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Low displacement pressure
- Software tracks garment inventory
- Quick changes are live physical work
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Costume Attendants, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Wardrobe coordination
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Garment repair
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Quick-change precision
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Production documentation
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Wardrobe Supervisor, such as lead dressing crews.
- By 90 days, compare internal openings and external postings for Wardrobe Supervisor or Costume Shop Technician and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Costume Attendants
Will AI replace Costume Attendants?
Costume attendants dress cast members, choreograph quick changes, and keep costumes performance-ready. Inventory software tracks garments digitally, but the thirty-second quick change, the emergency repair minutes before curtain, and the nightly care of fragile garments are backstage physical work. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Costume Attendants work are most exposed to AI?
Arrange costumes in order of use and Examine costume fit and note alterations show the strongest automation pressure in this model. Examine costume fit and note alterations and Arrange costumes in order of use are better treated as AI-augmented work.
What should Costume Attendants learn next?
Start with Wardrobe coordination, Garment repair, Quick-change precision. The most practical adjacent paths in this model are Wardrobe Supervisor and Costume Shop Technician.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
OECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics