Will AI replace Textile Bleaching and Dyeing Machine Operators and Tenders?

Not as a job, but it is already doing parts of the work. Across the 23 official task statements scored for Textile Bleaching and Dyeing Machine Operators and Tenders (United States, SOC 51-6061), 4% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 12 out of 100 (range 10–17, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.

What should someone working in “Textile Bleaching and Dyeing Machine Operators and Tenders” do about AI?

Start from the ledger rather than the headline: 4% of this job's weighted core work is exposed, and roughly 96% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.

US dataswitch to UK

Textile Bleaching and Dyeing Machine Operators and Tenders

weighing ingredients, such as dye, raveling seams that connect cloth ends when processing and removing dyed articles from tanks and machines for drying and further processing. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: adjusting equipment controls to maintain specified heat is work software can't reach.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 4%
changing shape: 0%
staying human: 96%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 12 out of 100 (10–17 allowing for uncertainty): minimal exposure, across 23 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.

How we know this

What is measured: Every published task statement for textile bleaching and dyeing machine operators and tenders is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

What shifts is recording production information, fabric yardage processed, temperature readings, fabric tensions and machine speeds: the overhead at the edges, not the middle you trained for.

Your week, as this page understands it

Operate or tend machines to bleach, shrink, wash, dye, or finish textiles or synthetic or glass fibers. The job title says “textile bleaching”, “dyeing machine operators” or “tenders”: officially one job, several names. The real job is the part underneath: adjusting equipment controls to maintain specified heat. That is the thing someone has to be right about.

The exposed part of this job is specific, and we won’t pretend it is coming back. But textile bleaching and dyeing machine operators and tenders is not one task. It is 23 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is adjusting equipment controls to maintain specified heat, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 4%
changing shape: 0%
staying human: 96%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

Your job, task by task

These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.

2 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Shifting to AI

1 task

Tasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.

Recording production information, fabric yardage processed, temperature readings, fabric tensions and machine speeds
This is reading one thing and writing another: production information, fabric yardage processed, temperature readings in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Record production information such as fabric yardage processed, temperature readings, fabric tensions, and machine speeds.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Logging yardage, temperatures and machine speeds is exactly the record keeping software already does automatically.
The five ratings: output a model can produce 4/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.

Changing shape

0 tasks

Tasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.

Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.

Staying human

22 tasks

Tasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.

Notifying supervisors or mechanics of equipment malfunctions
This work happens in the physical world: supervisors, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Notify supervisors or mechanics of equipment malfunctions.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: The message itself is easy, but noticing the fault means being on the floor beside the machine.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Adjusting equipment controls to maintain specified heat
This work happens in the physical world: equipment controls, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Adjust equipment controls to maintain specified heat, tension, and speed.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Adjusting heat, tension and speed means working the controls at the machine.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Starting and controlling machines and equipment
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Start and control machines and equipment to wash, bleach, dye, or otherwise process and finish fabric, yarn, thread, or other textile goods.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Starting and steering the machine is done at the controls on the floor.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Monitoring factors, temperatures and dye flow rates to ensure that they are within specified ranges
This work happens in the physical world: factors, temperatures and dye flow rates, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Monitor factors such as temperatures and dye flow rates to ensure that they are within specified ranges.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Temperatures and flow rates are already tracked by instruments, so checking them against limits is easy to automate.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Conferring with coworkers to get information about order details
This work happens in the physical world: coworkers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Confer with coworkers to get information about order details, processing plans, or problems that occur.” (O*NET task statement)
How this row was scored
Exposure score: 29 out of 100 (22–36 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Passing order details around is easy to automate, but on the floor it happens in short face-to-face exchanges.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Examining and feeling products to identify defects and variations from coloring and other processing standards
This work happens in the physical world: products, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Examine and feel products to identify defects and variations from coloring and other processing standards.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Judging colour and finish partly by feel needs the cloth in your hands.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Adding dyes, water, detergents or chemicals to tanks to dilute or strengthen solutions
This work happens in the physical world: dyes, water, detergents or chemicals, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Add dyes, water, detergents, or chemicals to tanks to dilute or strengthen solutions, according to established formulas and solution test results.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Mixing solutions in tanks to a formula is hands-on work with the equipment.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Observing display screens, control panels, equipment and cloth entering or exiting processes to determine if equipment is operating correctly
This work happens in the physical world: display screens, control panels, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Observe display screens, control panels, equipment, and cloth entering or exiting processes to determine if equipment is operating correctly.” (O*NET task statement)
How this row was scored
Exposure score: 19 out of 100 (12–26 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Sensors and cameras can read a process well, but watching cloth run through still means standing at the line.
The five ratings: output a model can produce 3/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Weighing ingredients, such as dye, to be mixed together for use in textile processing
This work happens in the physical world: ingredients, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Weigh ingredients, such as dye, to be mixed together for use in textile processing.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Weighing out dye powder is done by hand at the scales.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.

Show the other 13 tasks

Keying in processing instructions to program electronic equipment
staying human
This work happens in the physical world: processing instructions, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Key in processing instructions to program electronic equipment.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Typing a recipe into the machine’s controller is routine data entry, though it is done standing at the panel.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Studying guides, charts and specification sheets and conferring with supervisors to determine machine setup requirements
staying human
This work happens in the physical world: guides, charts and specification sheets, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Study guides, charts, and specification sheets, and confer with supervisors to determine machine setup requirements.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Working out setup from charts and spec sheets is document reading software handles well, though supervisors are consulted in person.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Inspecting machinery to determine necessary adjustments and repairs
staying human
This work happens in the physical world: machinery, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Inspect machinery to determine necessary adjustments and repairs.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (1–15 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Deciding what a machine needs comes from looking, listening and reaching into it.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Preparing dyeing machines for production runs
staying human
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Prepare dyeing machines for production runs, and conduct test runs of machines to ensure their proper operation.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Preparing a machine and running a test batch is hands-on work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Testing solutions used to process textile goods to detect variations from standards
staying human
This work happens in the physical world: solutions, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Test solutions used to process textile goods to detect variations from standards.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Testing a dye bath means drawing and handling samples at the tank.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Removing dyed articles from tanks and machines for drying and further processing
staying human
This work happens in the physical world: dyed articles, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Remove dyed articles from tanks and machines for drying and further processing.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Lifting wet goods out of tanks is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Sewing ends of cloth together
staying human
This work happens in the physical world: ends of cloth together, in a real place. Software cannot follow it there.
importance 5 · Supplemental
Source: “Sew ends of cloth together, by hand or using machines, to form endless lengths of cloth to facilitate processing.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Sewing cloth ends together is handwork at the machine.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Soaking specified textile products for designated times
staying human
This work happens in the physical world: specified textile products, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Soak specified textile products for designated times.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Loading and soaking goods for a set time is hands-on work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Threading ends of cloth or twine through specified sections of equipment prior to processing
staying human
This work happens in the physical world: ends of cloth, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Thread ends of cloth or twine through specified sections of equipment prior to processing.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Threading cloth through the machine is handwork.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Mounting rolls of cloth on machines
staying human
This work happens in the physical world: rolls of cloth, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Mount rolls of cloth on machines, using hoists, or place textile goods in machines or pieces of equipment.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Hoisting rolls of cloth onto machines is heavy physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Performing machine maintenance, such as cleaning and oiling equipment and repairing or replacing worn or defective parts
staying human
This work happens in the physical world: machine maintenance, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Perform machine maintenance, such as cleaning and oiling equipment, and repair or replace worn or defective parts.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Cleaning, oiling and swapping worn parts is hands-on maintenance.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Raveling seams that connect cloth ends when processing
staying human
This work happens in the physical world: seams, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Ravel seams that connect cloth ends when processing is completed.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Unpicking the joining seams afterwards is handwork.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Installing level and align components, gears, chains, dies, cutters and needles
staying human
This work happens in the physical world: level, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Install, level, and align components such as gears, chains, dies, cutters, and needles.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Fitting and aligning gears, dies and needles is hands-on work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.

What this job pays, and how many people do it

Median pay: $38,180a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
People doing this job: 5,310in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)

What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.

Why this is shifting

The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: production information, fabric yardage processed, temperature readings in, a record out. The rows above are exactly that shape: recording production information, fabric yardage processed, temperature readings, fabric tensions and machine speeds. What it cannot do is be there in the room, and that is still where equipment controls get done. Which is why this page talks about your tasks changing, not your job ending.

Your move

Over a pint: what I’d tell you if you were my friend

Start with what does not change: adjusting equipment controls to maintain specified heat is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 4% of this job's task weight sits in rows the software is already learning, 0% in rows that change shape rather than disappear, and 96% in rows it is nowhere near. That is the position, measured across 23 scored tasks. It is not a forecast about you.

So the thing worth your attention is not the job going away. It is the layer around it. Recording production information, fabric yardage processed, temperature readings, fabric tensions and machine speeds is the part turning into software, and being the person who understands that layer is worth money.

This week: one thing

Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to production information, fabric yardage processed, temperature readings, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.

What you end up holding: a straight answer about what is actually being rolled out, and when
How long it takes: ten minutes

If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether equipment controls are in scope or not. Nothing to log into, no license needed.

Over the next 90 days

Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near notifying supervisors or mechanics of equipment malfunctions. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.

Over the next 12 months

On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.

The roads out of here, and why I am not sending you down them

I looked at the obvious moves out of this job, and here is what I found.

I checked the 12 nearest US occupations to textile bleaching and dyeing machine operators and tenders (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was textile cutting machine setters, operators, and tenders: only about 26% of its durable work is work you already do. And on the numbers you do not need one. This job scores 12/100 here, with only 4% of the task list in the top band, and “notify supervisors or mechanics of equipment malfunctions” is not work that hands over cleanly. None of them beats deepening what you already have.

How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.

3 moves I checked and rejected

These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.

Textile Cutting Machine Setters, Operators, and Tenders
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already adjust equipment controls to maintain specified heat, tension, and speed, and their equivalent is to adjust machine controls, such as heating mechanisms, tensions, or speeds, to produce specified…. Across both published task lists that is about 26% of the durable work in that job.
Why I am not recommending it: It is closer than most, and still not close enough: about 26% of that job's durable work is already yours, against the 35% I want to see before I will call something a route.
Look at that job’s page anyway →
Textile Knitting and Weaving Machine Setters, Operators, and Tenders
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already inspect machinery to determine necessary adjustments and repairs, and their equivalent is to inspect machinery to determine whether repairs are needed. Across both published task lists that is about 24% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 24% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Textile Winding, Twisting, and Drawing Out Machine Setters, Operators, and Tenders
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “notify supervisors or mechanics of equipment malfunctions”. Across the whole of both lists that adds up to about 22% of the work in that job the software is not taking.
Why I am not recommending it: You would be starting most of it from nothing: about 22% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →

What I’d stop worrying about

A friend tells you what not to spend fear on. This is that list.

The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 4% of its task weight, across 23 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like adjusting equipment controls to maintain specified heat arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Textile process operatives is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United Kingdom page →partial match

In UK official statistics this job is counted as Textile process operatives. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.

Your route through this

Where to go next, and what it costs

Free, and complete

The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.

Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

Why there is no community here

Collab365, who build this site, run paid Spaces for a small number of subjects, and none of them is built for this job. We are not going to point you at the nearest one and call it a fit.

So the free services listed on this page are the whole answer, and it is the same answer we would give a friend.

Noted, and thank you. We’ll email you if a Space for textile bleaching / dyeing machine operators / tenders launches. Nothing else.

That did not look like an email address, so nothing was saved. Have another go below.

We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.

No Space for textile bleaching / dyeing machine operators / tenders yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for textile bleaching / dyeing machine operators / tenders existed, with researched problems, courses and people in the same boat, would you want in?

Your email

We use your email address for one thing: to tell you if a Space for textile bleaching / dyeing machine operators / tenders launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.

Questions people ask about this job

Will AI replace Textile Bleaching and Dyeing Machine Operators and Tenders?: Not as a job, but it is already doing parts of the work. Across the 23 official task statements scored for Textile Bleaching and Dyeing Machine Operators and Tenders (United States, SOC 51-6061), 4% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 12 out of 100 (range 10–17, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
Which tasks in “Textile Bleaching and Dyeing Machine Operators and Tenders” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Record production information such as fabric yardage processed, temperature readings, fabric tensions, and machine speeds” (75/100, high); “Monitor factors such as temperatures and dye flow rates to ensure that they are within specified ranges” (38/100, low); “Key in processing instructions to program electronic equipment” (38/100, low). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “Textile Bleaching and Dyeing Machine Operators and Tenders” stay human?: About 96% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Weigh ingredients, such as dye, to be mixed together for use in textile processing” (0/100, minimal); “Install, level, and align components such as gears, chains, dies, cutters, and needles” (0/100, minimal); “Ravel seams that connect cloth ends when processing is completed” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
What should someone working in “Textile Bleaching and Dyeing Machine Operators and Tenders” do about AI?: Start from the ledger rather than the headline: 4% of this job's weighted core work is exposed, and roughly 96% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
How is the AI exposure score for Textile Bleaching and Dyeing Machine Operators and Tenders calculated?: Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 23 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

Where these numbers come from

Worth knowing about these figures

The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
2 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Task statements: onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
Task weights: onet-db (im-rt)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
Pay and employment: bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))

Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.

The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.

The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.

How we score a job Download this release Look up another job

Using these figures?

Cite this

Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.

Plain text

Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).

BibTeX

@misc{collab365futureproof2026q41,
  title        = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
  author       = {{Collab365}},
  year         = {2026},
  url          = {https://futureproof.collab365.com/data/2026-q4.1},
  note         = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.