# Locker Room, Coatroom, and Dressing Room Attendants

> Provide personal items to patrons or customers in locker rooms, dressing rooms, or coatrooms.

- **SOC code:** 39-3093.00
- **Canonical URL:** https://singulariki.com/roles/role-39-3093-00
- **Also known as:** Athletic Equipment Manager, Ladies Locker Room Attendant, Locker Room Attendant, Spa Attendant, Coat Check Attendant, Coat Checker, Coat Room Attendant, Fitting Room Attendant
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Clean and polish footwear, using brushes, sponges, cleaning fluid, polishes, waxes, liquid or sole dressing, and daubers.
- Provide towels and sheets to clients in public baths, steam rooms, and restrooms.
- Activate emergency action plans and administer first aid, as necessary.
- Assign dressing room facilities, locker space, or clothing containers to patrons of athletic or bathing establishments.
- Check supplies to ensure adequate availability, and order new supplies when necessary.
- Monitor patrons' facility use to ensure that rules and regulations are followed, and safety and order are maintained.
- Clean facilities such as floors or locker rooms.
- Procure beverages, food, and other items as requested.
- Collect soiled linen or clothing for laundering.
- Answer customer inquiries or explain cost, availability, policies, and procedures of facilities.
- Refer guest problems or complaints to supervisors.
- Store personal possessions for patrons, issue claim checks for articles stored, and return articles on receipt of checks.

**Emerging tasks** (O*NET):
- Maintain or repair athletic equipment.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Customer and Personal Service _(knowledge)_
- Speaking _(essential_skill)_
- Active Listening _(essential_skill)_
- Service Orientation _(transferable_skill)_
- Speech Recognition _(ability)_
- English Language _(knowledge)_
- Oral Comprehension _(ability)_
- Speech Clarity _(ability)_
- Oral Expression _(ability)_
- Social Perceptiveness _(transferable_skill)_
- Problem Sensitivity _(ability)_
- Trunk Strength _(ability)_

**Skills in demand:**
- Speech Recognition _(Specialized Skill)_
- Active Listening _(Common Skill)_
- English Language _(Common Skill)_
- Social Perceptiveness _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Facebook _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Negotiation _(Common Skill)_

**Tools & technology:**
- Facebook _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Word _(hot technology)_
- IBM Lotus 1-2-3
- IntelliTrack DMS Check In-Out
- Inventory tracking software
- SportSoft Equipment Manager
- Web browser software

## AI exposure & outlook

- **AI task-overlap index:** 35th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 39th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 9th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 63rd percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 45th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 6.4% growth (About average); 4.2k annual openings; 15.6k → 16.6k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $34,800; 14,960 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 42% automation, — augmentation (usage-weighted).
- **Autonomy median:** 3.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Answer customer inquiries or explain cost, availability, policies, and procedures of facilities. _(0.4% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me answer customer inquiries or explain cost, availability, policies, and procedures of facilities.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-39-3093-00_