AI Automation Index

Will AI Replace Textile Cutting Machine Setters, Operators, and Tenders?

Task-level automation exposure for Textile Cutting Machine Setters, Operators, and Tenders: 18 O*NET tasks scored against their work activities, plus the simulator.

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Automation Exposure

27% weighted task index

18 of 18 tasks scored

Median Salary

$38,760 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Low

9,000 people hold this job — size, not growth

Projected 2025–35

-13.6% employment change

900 openings a year · BLS line item

Pay by state

BLS OEWS publishes 38 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$22,880 – $47,160

Highest medians

Connecticut $47,160

New York $46,810

New Hampshire $45,930

Hawaii $45,760

Washington $45,380

Lowest medians

Puerto Rico $22,880

Nevada $28,630

Arkansas $29,140

Iowa $30,060

Texas $30,160

State figures come from the 51-6062 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 27%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 59%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 0%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 7%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 18/100 Low

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

18 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 17%

3 tasks

Medium exposure (≥ 35%) 11%

2 tasks

Low exposure (below 35%) 72%

13 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Constituent Tasks

#21156 · Core · 28% automatable

Inspect products to ensure that the quality standards and specifications are met.

visual inspection — Product inspection needs physical visual/tactile check

Inspect products or operations to ensure that standards are met. Inspect work to ensure standards are met. Inspect textile products.

#14145 · Core · 8% automatable

Place patterns on top of layers of fabric and cut fabric following patterns, using electric or manual knives, cutters, or computer numerically controlled cutting devices.

physical manipulation — Physical alignment of patterns on workpieces

Cut fabrics. Position patterns on equipment, materials, or workpieces.

#14153 · Core · 12% automatable

Start machines, monitor operations, and make adjustments as needed.

physical manipulation — Textile cutting/production is hands-on machine work

Operate textile cutting or production equipment.

#14150 · Core · 12% automatable

Adjust machine controls, such as heating mechanisms, tensions, or speeds, to produce specified products.

physical manipulation — Textile cutting/production is hands-on machine work

Operate textile cutting or production equipment.

#14155 · Core · 82% automatable

Record information about work completed and machine settings.

data analysis — Record production data into structured logs

Record operational or production data.

#14146 · Core · 65% automatable

Notify supervisors of mechanical malfunctions.

text generation — Notifying maintenance needs is routine messaging

Notify others of equipment repair or maintenance needs.

#14149 · Core · 18% automatable

Inspect machinery to determine whether repairs are needed.

visual inspection — Physical inspection of production machinery in situ

Inspect production equipment.

#14152 · Core · 55% automatable

Confer with coworkers to obtain information about orders, processes, or problems.

interpersonal — Colleague information exchange is relational, contextual

Exchange information with colleagues.

#14147 · Core · 10% automatable

Repair or replace worn or defective parts or components, using hand tools.

physical manipulation — Hands-on removal and fitting of worn components

Replace worn equipment components. Repair production equipment or tools.

#14154 · Core · 8% automatable

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

physical manipulation — Manual lubrication of production equipment

Clean production equipment. Lubricate production equipment.

#14162 · Supplemental · 5% automatable

Thread yarn, thread, or fabric through guides, needles, and rollers of machines.

physical manipulation — Feeding materials into equipment is physical

Feed materials or products into or through equipment.

#14156 · Supplemental · 12% automatable

Operate machines to cut multiple layers of fabric into parts for articles such as canvas goods, house furnishings, garments, hats, or stuffed toys.

physical manipulation — Textile cutting/production is hands-on machine work

Operate textile cutting or production equipment.

#14148 · Supplemental · 15% automatable

Adjust cutting techniques to types of fabrics and styles of garments.

physical manipulation — Physical control setting for cutting

Set equipment controls to meet cutting specifications.

#14161 · Supplemental · 55% automatable

Program electronic equipment.

decision support — Programming production equipment needs physical setup and verification

Program equipment to perform production tasks.

#14157 · Supplemental · 61% automatable

Study guides, samples, charts, and specification sheets or confer with supervisors or engineering staff to determine set-up requirements.

visual inspection — Blueprint setup reading partial, human confirms

Study blueprints or other instructions to determine equipment setup requirements. Exchange information with colleagues.

#14159 · Supplemental · 12% automatable

Stop machines when specified amounts of product have been produced.

physical manipulation — Textile cutting/production is hands-on machine work

Operate textile cutting or production equipment.

#14158 · Supplemental · 21% automatable

Operate machines for test runs to verify adjustments and to obtain product samples.

physical manipulation — Operating production equipment physically on site

Conduct test runs of production equipment. Operate textile cutting or production equipment.

#14160 · Supplemental · 8% automatable

Install, level, and align components, such as gears, chains, guides, dies, cutters, or needles, to set up machinery for operation.

physical manipulation — Physical control setting for cutting

Mount attachments or tools onto production equipment. Set equipment controls to meet cutting specifications. Install mechanical components in production equipment.

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Community Sentiment

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Method

How this was scored

1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

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