What does a score of 26 mean for a Textile Knitting and Weaving Machine Setters, Operators, and Tenders?

It means that, weighted across the 19 tasks we analyzed for this role, the task mix sits at 26 on a 0–100 exposure scale — in the second quartile of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.

Which tasks in this role are most exposed to AI?

This role has no strongly automatable task in the current data release.

Which parts of this job are most durable?

The most durable responsibilities are: Thread yarn, thread, and fabric through guides, needles, and rollers of machines for weaving, knitting, or other processing; Repair or replace worn or defective needles and other components, using hand tools; Clean, oil, and lubricate machines, using air hoses, cleaning solutions, rags, oil cans, or grease guns. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.

Is this score personalized to me?

No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.

Textile Knitting and Weaving Machine Setters, Operators, and Tenders

Set up, operate, or tend machines that knit, loop, weave, or draw in textiles.

Also known as: Belt Weaver · Cloth Weaver · Carpet Weaver · Blanket Weaver · Automated Weaver · Broadloom Weaver

AI Task Exposure Score

Moderate exposure

More exposed than 29% of 968 occupations · Rank #658 (1 = most exposed)

This score estimates how exposed the tasks in a role are to current and near-term AI capabilities. It does not predict whether a specific person will lose a job.

Your free role snapshot

Start with the work, not the headline

This occupation baseline already contains different kinds of work. These are the two ends of its current task range and one useful action you can take now.

Most exposed task

Program electronic equipment.

Augmentable 55/100 exposure

Most durable task

Clean, oil, and lubricate machines, using air hoses, cleaning solutions, rags, oil cans, or grease guns.

Durable 10/100 exposure

Useful next step

Make one change to the task mix

Pilot AI on one augmentable task, then document the judgment, relationships, and accountability you still own.

Want this mapped to your actual week? Know what to strengthen, what to delegate to AI with review, and what to do over the next 7, 30, and 90 days.

Build my 7/30/90-day action plan — $9

Most exposed tasks

No task is classified fully automatable in this release. The highest-exposure task relative to this role is shown in the free snapshot above; the assistive work is detailed next.

Augmentable tasks

Work where AI assists rather than replaces — the productivity frontier of this role.

Program electronic equipment.55
Record information about work completed and machine settings.55
Study guides, loom patterns, samples, charts, or specification sheets, or confer with supervisors or engineering staff to determine setup requirements.40

Most durable tasks

Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.

Thread yarn, thread, and fabric through guides, needles, and rollers of machines for weaving, knitting, or other processing.10
Repair or replace worn or defective needles and other components, using hand tools.10
Clean, oil, and lubricate machines, using air hoses, cleaning solutions, rags, oil cans, or grease guns.10

Task exposure values and classifications are published, versioned estimates audited against the anchored rubric. This page reads them from the data release rather than generating them at request time. Bars show exposure contribution relative to this role’s task mix.

What this means

A score of 26 puts Textile Knitting and Weaving Machine Setters, Operators, and Tenders in the second quartile of analyzed occupations. In practice, exposure this level is about the mix: 0 of 19 analyzed tasks lean automatable, 3 augmentable, and 16 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.

Lower-exposure adjacent roles

Shown only when the target is at least 10 points lower under the same score version and skill overlap is at least 50%. These are adjacent roles with lower task exposure — not guaranteed “safe careers”.

Paper Goods Machine Setters, Operators, and Tenders

16 ▼ 10 pts lower

Skill overlap ≈ 56% · Related O*NET role; Paper Goods Machine Setters, Operators, and Tenders is an adjacent path (Elevated band).

Labor-market context

$39,530median wage
13,030employed
1,700annual openings
-11.1%projected growth

Context only — labor statistics are not inputs to the exposure score. See methodology.

Turn your actual week into a plan

Know which work to strengthen, what to delegate to AI with review, and what to do over the next 7, 30, and 90 days. Your $9 plan includes a confidence-rated personal score, task matrix, human moat, and only genuinely lower-exposure adjacent roles.

Build my 7/30/90-day action plan — $9

Related roles

Adjacent by skills or family — no exposure claim implied.

How this score was calculated

The score is the plain average of the AI-exposure values of this role’s 19 analyzed tasks (equal task weights in this release — no hidden factors):

Augmentable 3 tasks, averaging 50/100 exposure
Durable 16 tasks, averaging 22/100 exposure

score = (3×50 + 16×22) ÷ 19 ≈ 26

Every task’s exposure value was scored against a published anchored rubric that scores tasks as actually performed — physical, in-person, and accountability requirements included (data release 2026.07.12-r2). The band (Moderate) is a corpus quartile; the percentile is tie-aware across all 968 occupations.

FAQ — Textile Knitting and Weaving Machine Setters, Operators, and Tenders

Will AI replace Textile Knitting and Weaving Machine Setters, Operators, and Tenders?: This score cannot predict whether this occupation or any individual job will be replaced. It shows which tasks current and near-term AI can perform or accelerate, which tasks remain more durable, and where a worker can adapt. Employer decisions, demand, regulation, and how the role changes are outside the score.
What does a score of 26 mean for a Textile Knitting and Weaving Machine Setters, Operators, and Tenders?: It means that, weighted across the 19 tasks we analyzed for this role, the task mix sits at 26 on a 0–100 exposure scale — in the second quartile of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.
Which tasks in this role are most exposed to AI?: This role has no strongly automatable task in the current data release.
Which parts of this job are most durable?: The most durable responsibilities are: Thread yarn, thread, and fabric through guides, needles, and rollers of machines for weaving, knitting, or other processing; Repair or replace worn or defective needles and other components, using hand tools; Clean, oil, and lubricate machines, using air hoses, cleaning solutions, rags, oil cans, or grease guns. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.
Is this score personalized to me?: No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.

Score version jr-v1 · data release 2026.07.12-r2 · updated 2026-07-13 · baseline mapping: 19 of 19 tasks carry source-level provenance · methodology