Sewing Machine Operators
In short: today's best AI models could do about 2% 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 conversations, in-person and hands-on work, about 98% of the time, stays with people.
Operate or tend sewing machines to join, reinforce, decorate, or perform related sewing operations in the manufacture of garment or nongarment products.
104,880 people do this job in the US. $36,670 a year.
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on1 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people39 h
Sewing Machine Operators, now: of a 40-hour week, AI could take on 1 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 39 hours stay with people.
The largest pieces: Record quantities processed (under an hour).
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.
- 0%
- 2%
- 0%
- 0%
- 98%
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.
What handing it over would take, now
The 2% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
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, 2%. Today's estimate: 2%.
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
None of this job's 26 tasks showed up in the Claude.ai conversations Anthropic sampled in any of its 7 releases, from February 2025 to May 2026.
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 92% of this job's working time as physical work. For 84% of the working time, a robot has been shown doing most of the task somewhere: 80% in a purpose-built cell, 4% in a structured facility. 0.88 of 3, the 190th highest of the 923 jobs.
- Not physical 8%
- No robot shown 8%
- In a purpose-built cell 80%
- In a structured facility 4%
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.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
98% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Measure finished articles, the hands-on work, 8%
- Repair and alter items, the hands-on work, 8%
- Match cloth pieces, the hands-on work, 8%
- Watch for stitching faults, the hands-on work, 6%
- Guide parts under the needle, the hands-on work, 6%
- Thread the machine, the hands-on work, 5%
What becomes checking the machine
No desk work within reach by then in tasks where a mistake costs something. Another 2% is desk work that is small if wrong, which can be handed over with lighter checks.
What to learn
- The hands-on craft. About 98% of the time is hands-on work, which no model here does; robots are rated separately on this page.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 26 tasks from .
| Task | ||||
|---|---|---|---|---|
| Examine and measure finished articles to verify conformance to standards, using rulers.Articles checked with rulers.Done hourly or more by most who do it. Robots: in a purpose-built cell, Yunji Zhihui garment visual inspection and measurement machine (Dongguan Yunji Zhihui Technology Co., Ltd.) (sold). Anthropic's rating. | 8% | 7 min3 min to 13 min | Hands-on 100% | Stays with people |
| Repair or alter items by adding replacement parts or missing stitches.Parts and stitches added by hand.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 8% | 13 min4 min to 25 min | Hands-on 100% | Stays with people |
| Match cloth pieces in correct sequences prior to sewing them, and verify that dye lots and patterns match.Pieces matched in sequence and by dye lot.Done hourly or more by most who do it. Robots: in a purpose-built cell, Zünd Cut Center Pick&Place Interface Option (with cobot/robot arm) (sold). Anthropic's rating. | 8% | 7 min3 min to 13 min | Hands-on 100% | Stays with people |
| Monitor machine operation to detect problems such as defective stitching, breaks in thread, or machine malfunctions.Watching the machine run.Done hourly or more by most who do it. | 6% | 4 min2 min to 13 min | Hands-on 100% | Stays with people |
| Guide garments or garment parts under machine needles and presser feet to sew parts together.Pieces sewn together by hand guidance.Done hourly or more by most who do it. Robots: in a purpose-built cell, RoQom 6000 sewing cell (Yaskawa Motoman GP7) (KMF Maschinenbau / Yaskawa) (sold). Anthropic's rating. | 6% | 3 min2 min to 13 min | Hands-on 100% | Stays with people |
| Place spools of thread, cord, or other materials on spindles, insert bobbins, and thread ends through machine guides and components.Spools, bobbins and guides threaded.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 5% | 3 min2 min to 8 min | Hands-on 100% | Stays with people |
| Inspect garments, and examine repair tags and markings on garments to locate defects or damage, and mark errors as necessary.Garments and repair tags examined.Done daily by most who do it.Robots: in a purpose-built cell, Kannegiesser Quantex scan (Herbert Kannegiesser GmbH) (sold). Anthropic's rating. | 4% | 7 min3 min to 13 min | Hands-on 100% | Stays with people |
| Select supplies such as fasteners and thread, according to job requirements.Supplies chosen for the job.Done daily by most who do it. Robots: in a structured facility, Brightpick Autopicker (2.0) (sold). Anthropic's rating. | 4% | 4 min2 min to 13 min | Hands-on 100% | Stays with people |
| Start and operate or tend machines, such as single or double needle serging and flat-bed felling machines, to automatically join, reinforce, or decorate material or articles.Serging and felling machines tended.Done daily by most who do it. Robots: in a purpose-built cell, LOWRY SEWBOT (SoftWear Automation) (sold). Anthropic's rating. | 4% | 4 min2 min to 17 min | Hands-on 100% | Stays with people |
| Perform equipment maintenance tasks such as replacing needles, sanding rough areas of needles, or cleaning and oiling sewing machines.Needles replaced, machine cleaned and oiled.Done daily by most who do it. Robots: in a purpose-built cell, Autonomous mobile robotic screwdriving system (Manyar, Patel, Gupta / USC) (University of Southern California) (demonstrated). Anthropic's rating. | 4% | 10 min4 min to 25 min | Hands-on 100% | Stays with people |
| Cut materials according to specifications, using blades, scissors, or electric knives.Blades, scissors and electric knives on the material.Done hourly or more by most who do it.Robots: in a purpose-built cell, Lectra Vector Fashion (Vector iQ/iX2/Q2) automatic fabric cutter (sold). Anthropic's rating. | 4% | 4 min2 min to 17 min | Hands-on 100% | Stays with people |
| Fold or stretch edges or lengths of items while sewing to facilitate forming specified sections.Edges shaped as the seam runs.Done daily by most who do it. Robots: in a purpose-built cell, Sahl International BSA 920 SA automatic circular hemmer / Atlanta Attachment 211M / Sicama SAS hemming workstations (sold). Anthropic's rating. | 4% | 3 min2 min to 7 min | Hands-on 100% | 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. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% 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.
- Shoe Machine Operators and Tenders6% now, 6% by 2028
- Sewers, Hand0% now, 0% by 2028
- Pressers, Textile, Garment, and Related Materials2% now, 2% by 2028
- Cutters and Trimmers, Hand5% now, 5% by 2028
- Cutting and Slicing Machine Setters, Operators, and Tenders7% now, 7% by 2028
- Textile Knitting and Weaving Machine Setters, Operators, and Tenders10% now, 10% 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 Sewing Machine Operators is within reach of AI now?
- An estimated 2% of the working time is within reach of AI models now and 2% 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 Sewing Machine Operators 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: Record quantities processed (100% of the task's time now).
- Which tasks of Sewing Machine Operators stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Measure finished articles; Repair and alter items; and Match cloth pieces. Together such tasks are about 98% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Sewing Machine Operators learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the hands-on craft. By the end of 2028 on the long-run pace at four in five, about 98% of the working time stays with people, 0% becomes checking a model's work and 2% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Sewing Machine Operators?
- 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 0%. 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 Sewing Machine Operators?
- Anthropic's robot exposure rating (September 2026) finds 92% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 84% of the working time, 4% in a structured facility. Its index is 0.88 of 3. One example: Brightpick Autopicker (2.0) for "select thread and fasteners". 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 26 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on September 30, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), 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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