Will AI replace laundry and dry-cleaning workers?

Unlikely, though parts of the work are changing. About 58m of an 8-hour shift goes to tasks touched by robots. The other 7h 3m (88%) stays with people. Separately, BLS expects about 4.3% more of these jobs by 2035 (all jobs: +3.5%).

None of this job's tasks show regular AI use yet. That can mean the work is hands-on or in person, or simply that it rarely comes up in AI usage data.

For some tasks, yes. Robots have done 3 of this job's tasks in workplaces like this one, about 58m of a typical shift. 12 more tasks have only been done in factory setups built around the machine, so they stay with people here. For 8 physical tasks, no robot has shown it can do the work yet.

• 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. (36m a shift; e.g. Kannegiesser SmartLaundry with PowerTrans batch washer and Process Control, in use)
• Mix and add detergents, dyes, bleaches, starches, and other solutions and chemicals to clean, color, dry, or stiffen articles. (14m a shift; e.g. Softrol Catalyst / C-series and T-series laundry chemical injection systems, in use)
• Mix bleaching agents with hot water in vats, and soak material until it is bleached. (7m a shift; e.g. Kannegiesser SmartLaundry / PowerTrans batch washer with monorail bag storage, in use)

7h 3m of a typical shift, or 88%, goes to tasks with no AI or robot evidence yet. No AI usage or robot deployment has shown up for these so far. The biggest:

• Sort and count articles removed from dryers, and fold, wrap, or hang them. (1h 19m a shift)
• Load articles into washers or dry-cleaning machines, or direct other workers to perform loading. (50m a shift)
• Remove items from washers or dry-cleaning machines, or direct other workers to do so. (43m a shift)
• Examine and sort into lots articles to be cleaned, according to color, fabric, dirt content, and cleaning technique required. (36m a shift)
• Receive and mark articles for laundry or dry cleaning with identifying code numbers or names, using hand or machine markers. (36m a shift)

Much of it comes down to where and how the work happens. In-person, hands-on and high-stakes work is where AI and robots have made the least headway so far. In the official O*NET survey of people in this job:

• 91% spend more than half the day on their feet
• 82% carry high or very high responsibility for other workers' safety
• 75% use their hands on tools, objects or controls more than half the time

We track 1 sourced company move that affects this job. Most recent:

• Oct 12, 2025: Tumble tests a folding robot in its San Francisco laundry (Pilot)

On Indeed, job postings in the Production & Manufacturing sector are at 124% of their February 2020 level (all U.S. postings: 104%), up 12.6% from a year earlier, as of Oct 9, 2026. BLS separately expects about 28,000 openings a year in this job through 2035. Across all U.S. postings, 7.3% now mention AI skills. Sector postings cover more than this one job and move for many reasons besides AI.

The median pay is about $34,890 a year ($16.78 an hour), 32% below the median for all U.S. jobs ($50,980). Most people in this job earn between $27,440 and $43,190 a year; that range covers the middle 80%. Pay figures are from BLS, May 2025, and vary a lot by state and employer. Pick a state to compare:

BLS projects growth of 4.3% from 2025 to 2035, compared with 3.5% growth for all jobs. That's about 214,000 jobs in 2035. It expects about 28,000 openings a year, mostly from people retiring or changing careers. These projections don't single out AI as a cause.

About 198,000 people in the U.S., roughly 0.13% of all workers (BLS, May 2025). That makes it the 173rd largest of the 796 jobs on this site. BLS expects about 214,000 in 2035.

The most common requirement is less than a high school diploma: about 65% of people in the job said so in the official O*NET survey. O*NET rates the job at level 1 of 5 for preparation, which usually means: little or no preparation. Requirements vary by state and employer, especially for licensed work.

These come from the job's official skill ratings and from the tasks that AI and robots touch least today. Building them keeps you strong in the parts of the work that still need a person:

• Skills that matter more here than in most jobs: Monitoring, Active Listening
• Get strong at the parts of the job that stay with people (listed above), which take 7h 3m of a typical shift
• Tools employers list: Microsoft Excel, Microsoft Office software, Microsoft Windows, Microsoft Word

These use similar skills. Matches come from 109 official ratings of skills, knowledge and work activities, and each needs the same or less preparation unless the official list relates the jobs directly:

• Dishwashers (3h 56m touched, $35k median pay)
• Sewing Machine Operators (19m touched, $37k median pay)
• Pressers, Textile, Garment, and Related Materials (40m touched, $35k median pay)
• Hand Cutters and Trimmers (37m touched, $38k median pay)
• Cleaners of Vehicles and Equipment (1h 11m touched, $36k median pay)

Each task carries its own evidence label. For this job: 3 with robots in real deployments, 20 with no AI or robot evidence found. The minutes per task are estimates, not measured hours, and "no evidence" doesn't prove a task is safe.