Shigoto Zukan
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Will AI replace Textile Knitting and Weaving Machine Setters, Operators, and Tenders?AI replacement risk 39% and how the work is changing

United States Manufacturing & Repair Confidence ★★★★★

Median annual pay
$39,530
25th–75th pct. $36,390–$45,220
Top pay (est.)
$63,900
Top 10% $49,130
Pay in 5 years
$44,300est.
2031
Pay in 10 years
$49,500est.
$42,600–$57,500
Outlook score
31/100
★★☆☆☆ Below average
AI replacement risk
39%
Low
Job growth (10 yr)
−13.7%
1,300 openings / yr

Will AI replace Textile Knitting and Weaving Machine Setters, Operators, and Tenders? AI replacement risk

39%
Low
Ranked #363 safest from AI among all U.S. occupations
Very lowLowModerateHighVery high

How AI is changing this job

A written analysis for this occupation is being prepared.

AI replacement risk compares the parts of a job that are easy to hand to AI or software (processing information, documentation, repetitive computer work) with the parts that are hard to automate (physical work, working closely with people, judgment in unpredictable settings), using O*NET work activities, work context, skills and knowledge. The result is a relative position among all occupations in the country, scaled to 0–100%. Methodology →

Skills, education and requirements for Textile Knitting and Weaving Machine Setters, Operators, and Tenders

Key skills

Operations Monitoring
3.1
Monitoring
3.0
Operation and Control
3.0
Quality Control Analysis
2.6
Active Listening
2.5
Speaking
2.4
Reading Comprehension
2.4
Coordination
2.2

O*NET skill level ratings (0–7).

Key knowledge areas

Production and Processing
3.7
English Language
2.9
Mechanical
2.5
Education and Training
2.4
Public Safety and Security
2.1
Computers and Electronics
2.0
Administration and Management
1.8
Mathematics
1.5

What the work involves

Handling and Moving ObjectsControlling Machines and ProcessesPerforming General Physical ActivitiesJudging the Qualities of Objects, Services, or PeopleGetting InformationInspecting Equipment, Structures, or MaterialsMonitoring Processes, Materials, or SurroundingsUpdating and Using Relevant Knowledge

Important abilities

Arm-Hand SteadinessFinger DexterityControl PrecisionManual DexterityOral ComprehensionMultilimb Coordination

Education of workers

High school diploma
95%
Less than high school
5%

Training before entry

Up to 1 month
32%
1–3 months
27%
3–6 months
13%
6–12 months
10%
1–2 years
9%
None / short demo
9%

Related work experience

1–2 years
24%
3–6 months
22%
1–3 months
17%
6–12 months
17%
None
11%
Up to 1 month
9%

Job Zone 2 — some preparation needed (O*NET)

Difficulty of entry: ★☆☆☆☆ Easy to enter (from education, training, experience and Job Zone)

Pay and employment figures are national statistics. Projected pay, outlook scores and AI replacement risk are estimates from the Shigoto Zukan model, not guarantees. To request a correction, use the contact form. How to read the data
Sources: BLS OEWS May 2025; BLS Employment Projections 2025–35; O*NET 31.0 Database by USDOL/ETA (CC BY 4.0), modified by Shigoto Zukan. Pay ranges, projections and scores are Shigoto Zukan estimates.