# Laundry and Dry-Cleaning Workers

> Operate or tend washing or dry-cleaning machines to wash or dry-clean industrial or household articles, such as cloth garments, suede, leather, furs, blankets, draperies, linens, rugs, and carpets. Includes spotters and dyers of these articles.

- **SOC code:** 51-6011.00
- **Canonical URL:** https://singulariki.com/roles/role-51-6011-00
- **Also known as:** Laundry Aide, Laundry Attendant, Laundry Housekeeper, Laundry Worker, Dry Cleaner, Laundry Assistant, Laundry Technician, Personal Clothing Laundry Aide
- **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):
- Load articles into washers or dry-cleaning machines, or direct other workers to perform loading.
- Start washers, dry cleaners, driers, or extractors, and turn valves or levers to regulate machine processes and the volume of soap, detergent, water, bleach, starch, and other additives.
- Apply bleaching powders to spots and spray them with steam to remove stains from fabrics that do not respond to other cleaning solvents.
- Operate extractors and driers, or direct their operation.
- Sort and count articles removed from dryers, and fold, wrap, or hang them.
- Remove items from washers or dry-cleaning machines, or direct other workers to do so.
- Clean machine filters, and lubricate equipment.
- Examine and sort into lots articles to be cleaned, according to color, fabric, dirt content, and cleaning technique required.
- Determine spotting procedures and proper solvents, based on fabric and stain types.
- Spray steam, water, or air over spots to flush out chemicals, dry material, raise naps, or brighten colors.
- Receive and mark articles for laundry or dry cleaning with identifying code numbers or names, using hand or machine markers.
- Pre-soak, sterilize, scrub, spot-clean, and dry contaminated or stained articles, using neutralizer solutions and portable machines.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Arm-Hand Steadiness _(ability)_
- Customer and Personal Service _(knowledge)_
- Production and Processing _(knowledge)_
- Active Listening _(essential_skill)_
- Monitoring _(essential_skill)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- Manual Dexterity _(ability)_
- Control Precision _(ability)_
- Near Vision _(ability)_
- Speech Recognition _(ability)_
- English Language _(knowledge)_

**Skills in demand:**
- Speech Recognition _(Specialized Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Windows _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Active Listening _(Common Skill)_
- English Language _(Common Skill)_
- Time Management _(Common Skill)_
- Social Perceptiveness _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Finger Dexterity _(Common Skill)_
- Mathematics _(Common Skill)_
- Reading Comprehension _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Windows _(hot technology)_
- Microsoft Word _(hot technology)_
- Cents
- Curbside Laundries Wash and Fold POS Software
- Email software
- Property management system PMS software
- Sales processing software
- Wash-Dry-Fold POS
- Web browser software

## AI exposure & outlook

- **AI task-overlap index:** 8th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 16th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 10th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 9th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 58th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 5.4% growth (About average); 31.9k annual openings; 202.6k → 213.5k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $33,800; 195,360 employed.

## 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/
- **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-51-6011-00_