Textile Bleaching and Dyeing Machine Operators and Tenders
In short: today's best AI models could do about 11% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 89% of the time, stays with people.
Operate or tend machines to bleach, shrink, wash, dye, or finish textiles or synthetic or glass fibers.
5,310 people do this job in the US. $38,180 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on4 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people36 h
Textile Bleaching and Dyeing Machine Operators and Tenders, now: of a 40-hour week, AI could take on 4 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 36 hours stay with people.
The largest pieces: Study guides, charts, and specification sheets, and confer with supervisors to determine machine setup requirements (about 2 h); Key in processing instructions to program electronic equipment (about 1 h); Record production information such as fabric yardage processed, temperature readings, fabric tensions, and machine speeds (about 1 h).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 11%
- 2%
- 87%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 2%. With Claude Mythos Preview (early), measured in April 2026, 11%. Today's estimate: 11%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 23 tasks showed up. Within each of Anthropic's methods, never across a change: 0.014% to 0.0039% (released February and March 2025); 0.032% to 0.0066% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.014% | 494 of 708 | 3 of 23 |
| Released March 2025 | 0.0039% | 604 of 703 | 2 of 23 |
| The week of Aug 4, 2025 (released September 2025) | 0.032% | 295 of 655 | 2 of 23 |
| The week of Nov 13, 2025 (released January 2026) | 0.016% | 418 of 672 | 1 of 23 |
| The week of Feb 5, 2026 (released March 2026) | 0.0066% | 545 of 677 | 1 of 23 |
| April 2026 (released June 2026) | none | n/a | 0 of 23 |
| May 2026 (released June 2026) | none | n/a | 0 of 23 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 68% of this job's working time as physical work. For 68% of the working time, a robot has been shown doing most of the task somewhere: 44% in a purpose-built cell, 23% in a structured facility. 0.91 of 3, the 172nd highest of the 923 jobs.
- Not physical 32%
- In a purpose-built cell 44%
- In a structured facility 23%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
The tasks
Sorted by . 23 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Prepare dyeing machines for production runs, and conduct test runs of machines to ensure their proper operation.Done daily by most who do it.Robots: in a purpose-built cell, Supercolor automatic powder dye weighing system (Lawer S.p.A.) (sold). Anthropic's rating. | 12% | 50 min17 min to 1.7 h | Stays with people | |
| Start and control machines and equipment to wash, bleach, dye, or otherwise process and finish fabric, yarn, thread, or other textile goods.Done daily by most who do it. Robots: in a structured facility, Sedomat 2000 / 3500 dye machine controllers with automatic dye kitchen link (sold). Anthropic's rating. | 11% | 25 min8 min to 1.3 h | Stays with people | |
| Remove dyed articles from tanks and machines for drying and further processing.Done hourly or more by most who do it.Robots: in a structured facility, THEN AIRFLOW Synergy 8 (XY plaiting device) (Fong's Industries / Then) (sold). Anthropic's rating. | 7% | 21 min8 min to 50 min | Stays with people | |
| Add dyes, water, detergents, or chemicals to tanks to dilute or strengthen solutions, according to established formulas and solution test results.Done hourly or more by most who do it. Robots: in a purpose-built cell, Color Service TRS / DLV / DAP automatic dosing and dissolving systems (sold). Anthropic's rating. | 7% | 17 min8 min to 33 min | Stays with people | |
| Examine and feel products to identify defects and variations from coloring and other processing standards.Done daily by most who do it. Robots: in a purpose-built cell, Uster EVS Fabriq Vision (sold). Anthropic's rating. | 6% | 17 min4 min to 50 min | Stays with people | |
| Mount rolls of cloth on machines, using hoists, or place textile goods in machines or pieces of equipment.Done daily by most who do it.Robots: in a purpose-built cell, E80 Unicorn LGV + ANT AGV with Gambini automatic unwinder (sold). Anthropic's rating. | 5% | 33 min13 min to 1.1 h | Stays with people | |
| Observe display screens, control panels, equipment, and cloth entering or exiting processes to determine if equipment is operating correctly.Done hourly or more by most who do it. | 5% | 13 min4 min to 33 min | Stays with people | |
| Thread ends of cloth or twine through specified sections of equipment prior to processing.Done daily by most who do it.Robots: in a purpose-built cell, JOIN-RAIL / JOIN-RAIL ELITE automatic joining rail (Comatex Textile Machinery) (sold). Anthropic's rating. | 4% | 21 min8 min to 50 min | Stays with people | |
| Adjust equipment controls to maintain specified heat, tension, and speed.Done daily by most who do it. Robots: in a structured facility, Sedomat machine controllers (1500/2000/2500/5000 series) (deployed). Anthropic's rating. | 4% | 13 min4 min to 33 min | Stays with people | |
| Inspect machinery to determine necessary adjustments and repairs.Done daily by most who do it. Robots: in a purpose-built cell, Spot (with Orbit / Autowalk, thermal and acoustic payloads) (Boston Dynamics / Michelin) (deployed). Anthropic's rating. | 4% | 25 min8 min to 1.1 h | Stays with people | |
| Study guides, charts, and specification sheets, and confer with supervisors to determine machine setup requirements.Done daily by most who do it. | 4% | 25 min8 min to 50 min | 100%Half by now | |
| Monitor factors such as temperatures and dye flow rates to ensure that they are within specified ranges.Done daily by most who do it. | 4% | 13 min4 min to 33 min | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders5% now, 5% by 2028
- Adhesive Bonding Machine Operators and Tenders9% now, 9% by 2028
- Machine Feeders and Offbearers5% now, 5% by 2028
- Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders10% now, 10% by 2028
- Extruding and Forming Machine Setters, Operators, and Tenders, Synthetic and Glass Fibers5% now, 5% by 2028
- Laundry and Dry-Cleaning Workers1% now, 1% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Textile Bleaching and Dyeing Machine Operators and Tenders is within reach of AI now?
- An estimated 11% of the working time is within reach of AI models now and 11% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Textile Bleaching and Dyeing Machine Operators and Tenders come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Study guides, charts, and specification sheets, and confer with supervisors to determine machine setup requirements (100% of the task's time now); Key in processing instructions to program electronic equipment (100% of the task's time now); and Record production information such as fabric yardage processed, temperature readings, fabric tensions, and machine speeds (100% of the task's time now).
- Which tasks of Textile Bleaching and Dyeing Machine Operators and Tenders stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Prepare dyeing machines for production runs, and conduct test runs of machines to ensure their proper operation; Start and control machines and equipment to wash, bleach, dye, or otherwise process and finish fabric, yarn, thread, or other textile goods; and Remove dyed articles from tanks and machines for drying and further processing. Together such tasks are about 89% of the working time.
- Do people already use AI for the work of Textile Bleaching and Dyeing Machine Operators and Tenders?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 2%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Textile Bleaching and Dyeing Machine Operators and Tenders?
- Anthropic's robot exposure rating (September 2026) finds 68% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 68% of the working time, 23% in a structured facility. Its index is 0.91 of 3. One example: Sedomat 2000 / 3500 dye machine controllers with automatic dye kitchen link for "start and control machines and equipment to wash, bleach, dye, or otherwise process and finish fabric, yarn, thread, or other textile goods". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 23 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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