AI exposure by occupation, O*NET 51-6011.00
Will AI replace Laundry and Dry-Cleaning Workers?
Laundry and Dry-Cleaning Workers: AI can already handle 2 of 23 tasks; most of the work is hands-on, and the part AI can address mostly needs a standard-tier model.
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Every task, scored
The 23 tasks O*NET 30.3 lists for Laundry and Dry-Cleaning Workers, from most to least exposed. 2 reach 60 or more, the level at which AI already handles a task.
| Task | AI exposure | Evidence | Model tier |
|---|---|---|---|
| Sort and count articles removed from dryers, and fold, wrap, or hang them. | Estimated | Standard | |
| Examine and sort into lots articles to be cleaned, according to color, fabric, dirt content, and cleaning technique required. | Estimated | Standard | |
| Inspect soiled articles to determine sources of stains, to locate color imperfections, and to identify items requiring special treatment. | Estimated | Efficient | |
| Load articles into washers or dry-cleaning machines, or direct other workers to perform loading. | Estimated | No tier | |
| 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. | Estimated | No tier | |
| Apply bleaching powders to spots and spray them with steam to remove stains from fabrics that do not respond to other cleaning solvents. | Estimated | No tier | |
| Operate extractors and driers, or direct their operation. | Estimated | No tier | |
| Remove items from washers or dry-cleaning machines, or direct other workers to do so. | Estimated | No tier | |
| Clean machine filters, and lubricate equipment. | Estimated | No tier | |
| Determine spotting procedures and proper solvents, based on fabric and stain types. | Estimated | No tier | |
| Spray steam, water, or air over spots to flush out chemicals, dry material, raise naps, or brighten colors. | Estimated | No tier | |
| Pre-soak, sterilize, scrub, spot-clean, and dry contaminated or stained articles, using neutralizer solutions and portable machines. | Estimated | No tier | |
| Mix bleaching agents with hot water in vats, and soak material until it is bleached. | Estimated | No tier | |
| Mix and add detergents, dyes, bleaches, starches, and other solutions and chemicals to clean, color, dry, or stiffen articles. | Estimated | No tier | |
| Sprinkle chemical solvents over stains, and pat areas with brushes or sponges to remove stains. | Estimated | No tier | |
| Match sample colors, applying knowledge of bleaching agent and dye properties, and types, construction, conditions, and colors of articles. | Estimated | No tier | |
| Operate machines that comb, dry and polish furs, clean, sterilize and fluff feathers and blankets, or roll and package towels. | Estimated | No tier | |
| Iron or press articles, fabrics, and furs, using hand irons or pressing machines. | Estimated | No tier | |
| Hang curtains, drapes, blankets, pants, and other garments on stretch frames to dry. | Estimated | No tier | |
| Identify articles' fabrics and original dyes by sight and touch, or by testing samples with fire or chemical reagents. | Estimated | No tier | |
| Immerse articles in bleaching baths to strip colors. | Estimated | No tier | |
| Receive and mark articles for laundry or dry cleaning with identifying code numbers or names, using hand or machine markers. | Estimated | No tier | |
| Spread soiled articles on work tables, and position stained portions over vacuum heads or on marble slabs. | Estimated | No tier |
Observed: scored from AI use recorded in the Anthropic Economic Index (June 2026 release), 0 of 23 tasks. Estimated: scored from the task's O*NET 30.3 work activity, 23 of 23. Importance is O*NET's 1 to 5 rating of how central the task is. Model tier is the lowest tier that can do the task under the published rubric; "No tier" marks hands-on work.
The model tier this role needs
A standard-tier model or lower covers 13% of the role's importance-weighted task work. 13% of the work is something AI can address at some tier, and 87% is hands-on.
Efficient, standard and frontier tiers come from the JobRoute model tier reference. The recommended tier is the lowest one that covers 80% of the work AI can address. How the method works.
Wages, employment and outlook
- US employment
- 198,040
- Median annual wage
- $34,890
- Middle half of earners
- $30,360 to $37,560
- Projected change, 2024 to 2034
- +5.4%
Employment and wages: BLS Occupational Employment and Wage Statistics, May 2025, national. Projection: BLS Employment Projections 2024 to 2034.
Adjacent roles
The occupations that reuse the most of this role's skills, with the usual time to move. These are the first places to look when you plan to redeploy or retrain people in this role.
- Pressers, Textile, Garment, and Related Materials 69% skill overlap, about 11 months to move Exposure18
- Textile Bleaching and Dyeing Machine Operators and Tenders 68% skill overlap, about 11 months to move Exposure19
- Cleaners of Vehicles and Equipment 64% skill overlap, about 13 months to move Exposure15
- Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders 64% skill overlap, about 13 months to move Exposure20
- Janitors and Cleaners, Except Maids and Housekeeping Cleaners 61% skill overlap, about 14 months to move Exposure14
Skill overlap and transition time from the JobRoute role adjacency graph on O*NET 30.3 skills.
Questions about Laundry and Dry-Cleaning Workers and AI
Will AI replace Laundry and Dry-Cleaning Workers?
AI already handles 2 of the 23 tasks O*NET lists for this occupation, at a task exposure of 60 or more, and the role's importance-weighted exposure is 22 out of 100. JobRoute scores tasks, not whole jobs, so the score shows how much of the work changes rather than whether the job disappears. BLS projects employment to change by +5.4% from 2024 to 2034.
What is the AI exposure of Laundry and Dry-Cleaning Workers?
22 out of 100 on JobRoute's task exposure measure, the importance-weighted average of the role's O*NET task scores. Higher means more of the work is AI-doable today. 0 of the 23 task scores are observed in the Anthropic Economic Index (June 2026 release), and the other 23 are estimated from each task's O*NET work activity.
Which Laundry and Dry-Cleaning Workers tasks can AI already do?
The tasks with the highest exposure are: Sort and count articles removed from dryers, and fold, wrap, or hang them; Examine and sort into lots articles to be cleaned, according to color, fabric, dirt content, and cleaning technique required. They are the tasks that reach 60 or more.
What AI model tier does this role need?
A standard-tier model or lower covers 13% of the role's importance-weighted task work, and 87% is hands-on work that no model tier covers. JobRoute assigns each task the lowest tier that can do it under a published rubric and recommends the lowest tier that covers 80% of the work AI can address.
How many people work as Laundry and Dry-Cleaning Workers, and what do they earn?
198,040 people in the United States, with a median annual wage of $34,890 (BLS Occupational Employment and Wage Statistics, May 2025). BLS Employment Projections expect a change of +5.4% from 2024 to 2034.
How to cite
Data version 2026-11-02, JobRoute method v1.0.0. Download all occupations or this occupation as JSON. Methodology.
JobRoute (2026). AI exposure: Laundry and Dry-Cleaning Workers. Data version 2026-11-02, method v1.0.0. Built on O*NET 30.3, BLS OEWS May 2025 and the Anthropic Economic Index (June 2026). CC BY 4.0. https://www.jobroute.ai/jobs/laundry-and-dry-cleaning-workers
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