Will AI replace Sewing Machine Operators?

Not as a job, but it is already doing parts of the work. Across the 26 official task statements scored for Sewing Machine Operators (United States, SOC 51-6031), 4% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 4 out of 100 (range 3–8, 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 “Sewing Machine Operators” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Record quantities of materials processed” (69/100, high); “Select supplies such as fasteners and thread, according to job requirements” (13/100, minimal); “Inspect garments, and examine repair tags and markings on garments to locate defects or damage, and mark errors as necessary” (8/100, minimal). 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 “Sewing Machine Operators” 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: “Draw markings or pin appliques on fabric to obtain variations in design” (0/100, minimal); “Tape or twist together thread or cord to repair breaks” (0/100, minimal); “Baste edges of material to align and temporarily secure parts for final assembly” (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 “Sewing Machine Operators” 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 Sewing Machine Operators 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 26 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.

US dataswitch to UK

Sewing Machine Operators

monitoring machine operation to detect problems, cutting excess material or thread from finished products and selecting supplies, fasteners and thread, according to job requirements. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: placing spools of thread, cord or other materials on spindles, insert bobbins and thread ends through machine guides and components 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 4 out of 100 (3–8 allowing for uncertainty): minimal exposure, across 26 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 sewing machine operators 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 2026-08-04. Read the full method.

What shifts is recording quantities of materials: the overhead at the edges, not the middle you trained for.

Your week, as this page understands it

Operate or tend sewing machines to join, reinforce, decorate, or perform related sewing operations in the manufacture of garment or nongarment products. The job title says “sewing machine operators”. The real job is the part underneath: placing spools of thread, cord or other materials on spindles, insert bobbins and thread ends through machine guides and components. 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 sewing machine operators is not one task. It is 26 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is placing spools of thread, cord or other materials on spindles, insert bobbins and thread ends through machine guides and components, 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 2026-08-04. 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.

4 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 quantities of materials
This is reading one thing and writing another: quantities of materials in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Record quantities of materials processed.” (O*NET task statement)
How this row was scored
Exposure score: 69 out of 100 (62–76 allowing for uncertainty): high exposure, medium 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: Recording quantities is simple admin, though the amounts come from what was actually used at the bench.
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 3/4.

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

25 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.

Placing spools of thread, cord or other materials on spindles, insert bobbins and thread ends through machine guides and components
This work happens in the physical world: spools of thread, cord or other materials, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Place spools of thread, cord, or other materials on spindles, insert bobbins, and thread ends through machine guides and components.” (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 a machine and loading bobbins is fine hand work at the bench.
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 machine operation to detect problems
This work happens in the physical world: machine operation, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Monitor machine operation to detect problems such as defective stitching, breaks in thread, or machine malfunctions.” (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: Spotting a thread break or bad stitch means standing at the running 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.
Guiding garments or garment parts under machine needles and presser feet to sew parts together
This work happens in the physical world: garments, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Guide garments or garment parts under machine needles and presser feet to sew parts together.” (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: Guiding fabric under a needle is entirely manual.
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.
Selecting supplies, fasteners and thread, according to job requirements
This work happens in the physical world: supplies, fasteners and thread, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Select supplies such as fasteners and thread, according to job requirements.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal 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: The spec says which thread and fasteners to use, but someone has to pick and fit them.
The five ratings: output a model can produce 2/4 · 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.
Folding or stretching edges or lengths of items while sewing to facilitate forming specified sections
This work happens in the physical world: edges, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Fold or stretch edges or lengths of items while sewing to facilitate forming specified sections.” (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: Folding and stretching fabric while sewing is skilled hand 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.
Positioning items under needles, using marks on machines, clamps, templates or cloth as guides
This work happens in the physical world: items under needles, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Position items under needles, using marks on machines, clamps, templates, or cloth as guides.” (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: Placing fabric accurately under the needle is hands-on work 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.
Performing equipment maintenance tasks, replacing needles, sanding rough areas of needles or cleaning and oiling sewing machines
This work happens in the physical world: equipment maintenance tasks, replacing needles, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Perform equipment maintenance tasks such as replacing needles, sanding rough areas of needles, or cleaning and oiling sewing machines.” (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: Changing needles and oiling machines 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.
Turning knobs, screws and dials to adjust settings of machines, according to garment styles and equipment performance
This work happens in the physical world: knobs, screws and dials, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Turn knobs, screws, and dials to adjust settings of machines, according to garment styles and equipment performance.” (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: Turning dials and screws to set up a machine is hands-on adjustment.
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.
Cutting excess material or thread from finished products
This work happens in the physical world: excess material, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Cut excess material or thread from finished products.” (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: Trimming loose thread and cloth is done by hand with scissors.
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.

Show the other 16 tasks

Inspecting garments
staying human
This work happens in the physical world: garments, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Inspect garments, and examine repair tags and markings on garments to locate defects or damage, and mark errors as necessary.” (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: Cameras can flag some faults, but checking garments and marking errors happens with the item in hand.
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.
Matching cloth pieces in correct sequences prior to sewing them
staying human
This work happens in the physical world: cloth pieces, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Match cloth pieces in correct sequences prior to sewing them, and verify that dye lots and patterns match.” (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: Matching cloth pieces and dye lots means handling the fabric.
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 operating or tend machines
staying human
This work happens in the physical world: tend machines, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Start and operate or tend machines, such as single or double needle serging and flat-bed felling machines, to automatically join, reinforce, or decorate material or articles.” (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 tending a sewing machine means standing at it throughout.
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.
Mounting attachments, such as needles, cutting blades or pattern plates and adjusting machine guides according to specifications
staying human
This work happens in the physical world: attachments, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Mount attachments, such as needles, cutting blades, or pattern plates, and adjust machine guides according to specifications.” (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 blades, needles and pattern plates is physical setup 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.
Examining and measuring finished articles to verify conformance
staying human
This work happens in the physical world: finished articles, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Examine and measure finished articles to verify conformance to standards, using rulers.” (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: Measuring a finished garment with a ruler means handling the item itself.
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.
Repairing or altering items by adding replacement parts or missing stitches
staying human
This work happens in the physical world: items, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Repair or alter items by adding replacement parts or missing stitches.” (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: Repairing or altering a garment is done with the item under the needle.
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.
Cutting materials
staying human
This work happens in the physical world: materials, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Cut materials according to specifications, using blades, scissors, or electric knives.” (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: Cutting cloth with blades or an electric knife is hand work at the table.
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 holding devices and finished items from machines
staying human
This work happens in the physical world: devices, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Remove holding devices and finished items from machines.” (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: Taking finished pieces off the machine is physical work at the bench.
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.
Positioning and marking patterns on materials to prepare for sewing
staying human
This work happens in the physical world: patterns, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Position and mark patterns on materials to prepare for sewing.” (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: Laying out and marking patterns on cloth is physical work at the table.
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.
Positioning material or articles in clamps
staying human
This work happens in the physical world: material, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Position material or articles in clamps, templates, or hoop frames prior to automatic operation of machines.” (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: Setting fabric into clamps and frames is physical work 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.
Attaching tape, trim, appliques or elastic to specified garments or garment parts, according to item specifications
staying human
This work happens in the physical world: tape, trim, appliques or elastic, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Attach tape, trim, appliques, or elastic to specified garments or garment parts, according to item specifications.” (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: Attaching trim and elastic to a garment is precise hand 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.
Performing specialized or automatic sewing machine functions
staying human
This work happens in the physical world: specialized, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Perform specialized or automatic sewing machine functions, such as buttonhole making or tacking.” (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: Buttonholing and tacking are machine functions run with the fabric in place.
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.
Attaching buttons, hooks, zippers, fasteners or other accessories to fabric, using feeding hoppers or clamp holders
staying human
This work happens in the physical world: buttons, hooks, zippers, fasteners or other accessories, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Attach buttons, hooks, zippers, fasteners, or other accessories to fabric, using feeding hoppers or clamp holders.” (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 buttons, zips and fasteners is fine hand work 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.
Basting edges of material to align and temporarily secure parts for final assembly
staying human
This work happens in the physical world: edges of material, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Baste edges of material to align and temporarily secure parts for final assembly.” (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: Basting parts together to hold them for assembly is hand sewing.
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.
Taping or twisting together thread or cord to repair breaks
staying human
This work happens in the physical world: together thread, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Tape or twist together thread or cord to repair breaks.” (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: Rejoining thread is a small, fiddly job done by hand.
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.
Drawing markings or pin appliques on fabric to obtain variations in design
staying human
This work happens in the physical world: markings, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Draw markings or pin appliques on fabric to obtain variations in design.” (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: Marking fabric and pinning appliques is done by hand on the cloth.
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: $36,670a 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: 104,880in 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: quantities of materials in, a record out. The rows above are exactly that shape: recording quantities of materials. What it cannot do is be there in the room, and that is still where spools of thread, cord or other materials 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: placing spools of thread, cord or other materials on spindles, insert bobbins and thread ends through machine guides and components 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 26 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 quantities of materials 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 quantities of materials, 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 spools of thread, cord or other materials 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 placing spools of thread, cord or other materials on spindles, insert bobbins and thread ends through machine guides and components. 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 sewing machine operators (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was shoe machine operators and tenders: only about 15% of its durable work is work you already do and there are far fewer of those jobs than of yours. And on the numbers you do not need one. This job scores 4/100 here, with only 4% of the task list in the top band, and “place spools of thread, cord, or other materials on spindles, insert bobbins…” 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.

Shoe Machine Operators and Tenders
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already place spools of thread, cord, or other materials on spindles, insert bobbins, and…, and their equivalent is to select and place spools of thread or pre-wound bobbins into shuttles, or onto…. Across both published task lists that is about 15% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 15% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. And it is a narrow door: about 3,280 of those jobs against 104,880 of yours (OEWS May 2025), 3% as many seats.
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 on the work AI is not taking: you already place spools of thread, cord, or other materials on spindles, insert bobbins, and…, and their equivalent is to thread yarn, thread, or fabric through guides, needles, and rollers of machines. Across both published task lists that is about 9% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 9% of the durable side of that job. That is a different job, not a next step. And it is a narrow door: about 22,020 of those jobs against 104,880 of yours (OEWS May 2025), 21% as many seats.
Look at that job’s page anyway →
Tailors, Dressmakers, and Custom Sewers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already guide garments or garment parts under machine needles and presser feet to sew…, and their equivalent is to sew garments, using needles and thread or sewing machines. Across both published task lists that is about 9% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 9% of the durable side of that job. That is a different job, not a next step. And it is a narrow door: about 13,920 of those jobs against 104,880 of yours (OEWS May 2025), 13% as many seats.
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 26 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 placing spools of thread, cord or other materials on spindles, insert bobbins and thread ends through machine guides and components 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 Sewing machinists 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

The other groups this work is counted across:

Tailors and dressmakers

In UK official statistics this job is counted as Sewing machinists and Tailors and dressmakers. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.

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 sewing machine operators 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 sewing machine operators 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 sewing machine operators 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 sewing machine operators 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 Sewing Machine Operators?: Not as a job, but it is already doing parts of the work. Across the 26 official task statements scored for Sewing Machine Operators (United States, SOC 51-6031), 4% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 4 out of 100 (range 3–8, 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 “Sewing Machine Operators” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Record quantities of materials processed” (69/100, high); “Select supplies such as fasteners and thread, according to job requirements” (13/100, minimal); “Inspect garments, and examine repair tags and markings on garments to locate defects or damage, and mark errors as necessary” (8/100, minimal). 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 “Sewing Machine Operators” 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: “Draw markings or pin appliques on fabric to obtain variations in design” (0/100, minimal); “Tape or twist together thread or cord to repair breaks” (0/100, minimal); “Baste edges of material to align and temporarily secure parts for final assembly” (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 “Sewing Machine Operators” 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 Sewing Machine Operators 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 26 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.
4 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 2026-08-04.
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.

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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.