Laundry and Dry-Cleaning Workers

Laundry work is still mostly manual, though some parts are getting machines. For example, large laundries already use special feeders and folders for towels and sheets. Recently, companies have begun adding robot arms with cameras to pick up towels and place them into folding machines ^[1]. (These robots can “see” corners of a towel and spread it flat.) At CES 2026, LG even showed a home robot (CLOiD) folding laundry on its own ^{[2] [2]}.

These are prototypes, but they show how AI-vision can help with heavy, repetitive tasks. By contrast, we didn’t find any examples of AI “marking” or labeling clothes – in practice laundries use simple barcodes or RFID to track items instead of hand-drawing tags. Starting washers and setting cycles is usually done by a worker, since machines have built-in programs but no independent AI.

In short, industrial machines and simple automation handle bulk loads, but people still do most sorting, stain-treating, custom folds, and quality checks. As one industry report notes, even with new tech “nothing works without people” – humans still sort, feed machines, iron, and pack laundry by hand ^[1].

Whether laundries use AI or robots depends on costs and needs. Big laundry plants face labor shortages and rising wages, so they look at automation more. In an industry survey, 90% of managers said they’ve considered more automation because labor is hard to find or expensive ^[3].

For instance, one plant manager in New York noted wage increases of 10–15% per year, making automation more attractive ^[3]. On the other hand, these machines are costly. Some plants can’t afford things like RFID tags or robot systems ^[3].

Laundry profit margins are slim, so many small laundries upgrade only where it clearly saves money or solves a staffing problem. Overall, adoption has been careful and gradual: owners want machines to improve speed and safety, but customers still trust human hands for delicate garments. Technicians who can run and maintain new machines will still be needed.

This means workers’ skills in managing machines, detecting stains, and ensuring quality remain valuable even as some tasks get help from AI ^{[1] [3]}.