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Textile Knitting and Weaving Machine Setters, Operators, and Tenders

Textile Knitting and Weaving Machine Setters, Operators, and Tenders score 16 out of 100, which is low exposure to AI. That ranks #681 of 923 US occupations, where #1 is the most exposed. Of the 20 tasks in this job, AI could speed up 3 on its own and 1 more with extra software built on top of it. In April–May 2026, 1 of these tasks showed up in real conversations with Claude, Anthropic's AI assistant.

16/ 100
Low
Rank
#681of 923 jobs
US workers
13,030BLS, May 2025
Median pay
$39,530a year
In real AI use
1 of 20tasks, April–May 2026

Task by task

Each task this job involves, as listed by O*NET, rated on whether a large language model like GPT-4 could cut the time it takes by at least half at the same quality. Tasks marked Seen in real AI use appeared in conversations with Claude in April–May 2026 (Anthropic Economic Index).

  • AI can speed this up on its own: 3 (15%)
  • AI can speed this up with extra software: 1 (5%)
  • Little or no AI speed-up: 16 (80%)
  • Record information about work completed and machine settings.AI can speed this up on its own · core task
  • Program electronic equipment.AI can speed this up on its own · supplemental task
  • Study guides, loom patterns, samples, charts, or specification sheets, or confer with supervisors or engineering staff to determine setup requirements.AI can speed this up on its own · supplemental task
  • Observe woven cloth to detect weaving defects.AI can speed this up with extra software · core task
  • Remove defects in cloth by cutting and pulling out filling.Little or no AI speed-up · core task
  • Inspect products to ensure that specifications are met and to determine if machines need adjustment.Little or no AI speed-up · core task
  • Thread yarn, thread, and fabric through guides, needles, and rollers of machines for weaving, knitting, or other processing.Little or no AI speed-up · core task
  • Examine looms to determine causes of loom stoppage, such as warp filling, harness breaks, or mechanical defects.Little or no AI speed-up · core task
  • Notify supervisors or repair staff of mechanical malfunctions.Little or no AI speed-up · core task
  • Set up, or set up and operate textile machines that perform textile processing and manufacturing operations such as winding, twisting, knitting, weaving, bonding, or stretching.Little or no AI speed-up · core task
  • Start machines, monitor operations, and make adjustments as needed.Little or no AI speed-up · core task
  • Inspect machinery to determine whether repairs are needed.Little or no AI speed-up · core task
  • Confer with co-workers to obtain information about orders, processes, or problems.Little or no AI speed-up · core task · Seen in real AI use
  • Stop machines when specified amounts of product have been produced.Little or no AI speed-up · core task
  • Clean, oil, and lubricate machines, using air hoses, cleaning solutions, rags, oil cans, or grease guns.Little or no AI speed-up · supplemental task
  • Operate machines for test runs to verify adjustments and to obtain product samples.Little or no AI speed-up · supplemental task
  • Wash and blend wool, yarn, or cloth.Little or no AI speed-up · supplemental task
  • Repair or replace worn or defective needles and other components, using hand tools.Little or no AI speed-up · supplemental task
  • Install, level, and align machine components such as gears, chains, guides, dies, cutters, or needles to set up machinery for operation.Little or no AI speed-up · supplemental task
  • Adjust machine heating mechanisms, tensions, and speeds to produce specified products.Little or no AI speed-up · supplemental task

Questions about textile knitting and weaving machine setters, operators, and tenders and AI

Will AI replace textile knitting and weaving machine setters, operators, and tenders?

Unlikely. Most of the work is hard for today's AI to speed up. Textile Knitting and Weaving Machine Setters, Operators, and Tenders score 16 out of 100 (low exposure), #681 of 923 US jobs. AI could speed up 4 of the job's 20 tasks, 3 of them on its own, while 16 see little or no speed-up. Exposure means the work is likely to change, not that the job will disappear.

Which textile knitting and weaving machine setters, operators, and tenders tasks can AI do?

The most exposed tasks include "Record information about work completed and machine settings"; "Program electronic equipment"; "Study guides, loom patterns, samples, charts, or specification sheets, or confer with supervisors or engineering staff to determine setup requirements".

Which textile knitting and weaving machine setters, operators, and tenders tasks are hardest for AI?

Tasks with little or no AI speed-up include "Remove defects in cloth by cutting and pulling out filling"; "Inspect products to ensure that specifications are met and to determine if machines need adjustment"; "Thread yarn, thread, and fabric through guides, needles, and rollers of machines for weaving, knitting, or other processing".

Are people already using AI for this work?

Yes. In April–May 2026, 1 of the 20 tasks showed up in real conversations with Claude, according to the Anthropic Economic Index.

How many people work as textile knitting and weaving machine setters, operators, and tenders, and what do they earn?

About 13,030 people in the US, with median pay of $39,530 a year (BLS, May 2025).

How to read this score. Exposure measures how much of the work AI could speed up, not whether the job will disappear. A highly exposed job can change shape, with people spending less time on routine tasks and more on the rest. The score counts tasks AI can speed up on its own in full, and tasks that need extra software at half weight.

The ratings come from published research based on GPT-4 (2023). To show what's happening now, each task is also checked against the latest Anthropic Economic Index, which records which tasks people actually use AI for. That data is refreshed automatically when Anthropic publishes a new release. Read the full method.

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