Will AI replace Patternmakers, Wood?

Not as a job, but it is already doing parts of the work. Across the 20 official task statements scored for Patternmakers, Wood (United States, SOC 51-7032), 13% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 21 out of 100 (range 17–26, band: low). 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 “Patternmakers, Wood” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Compute dimensions, areas, volumes, and weights” (100/100, very high); “Maintain pattern records for reference” (75/100, high); “Estimate costs for patternmaking jobs” (75/100, high). 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 “Patternmakers, Wood” stay human?

About 81% 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: “Collect and store patterns and lumber” (0/100, minimal); “Repair broken or damaged patterns” (0/100, minimal); “Glue fillets along interior angles of patterns” (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 “Patternmakers, Wood” do about AI?

Start from the ledger rather than the headline: 13% of this job's weighted core work is exposed, and roughly 81% 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 Patternmakers, Wood 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 20 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

Patternmakers, Wood

reading blueprints, correcting patterns to compensate for defects in castings and setting up, operate and adjusting a variety of woodworking machines. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: fitting fasten and assembling wood parts together to form patterns, models or sections, using glue, nails, dowels, bolts and screws 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: 13%
changing shape: 6%
staying human: 81%

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

Whole-job exposure score 21 out of 100 (17–26 allowing for uncertainty): low exposure, across 20 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 patternmakers, wood 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 computing dimensions, areas, volumes and weights. This page scores what today's tools actually do, not headlines.

Your week, as this page understands it

Plan, lay out, and construct wooden unit or sectional patterns used in forming sand molds for castings. The job title says “patternmakers” or “wood”: officially one job, two names. The real job is the part underneath: fitting fasten and assembling wood parts together to form patterns, models or sections, using glue, nails, dowels, bolts and screws. 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 patternmakers, wood is not one task. It is 20 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is fitting fasten and assembling wood parts together to form patterns, models or sections, using glue, nails, dowels, bolts and screws, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 13%
changing shape: 6%
staying human: 81%

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 rows are marked low confidence, so treat them as a ballpark rather than a fine measurement.
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

3 tasks

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.

Computing dimensions, areas, volumes and weights
This is reading one thing and writing another: dimensions, areas, volumes and weights in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Compute dimensions, areas, volumes, and weights.” (O*NET task statement)
How this row was scored
Exposure score: 100 out of 100 (96–100 allowing for uncertainty): very 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: Working out dimensions, areas, volumes and weights is pure calculation, and software does it faster and more reliably.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Maintaining pattern records for reference
This is reading one thing and writing another: pattern records in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Maintain pattern records for reference.” (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: Keeping an indexed record of patterns is ordinary filing and database work that software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Estimating costs for patternmaking jobs
This is reading one thing and writing another: costs in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Estimate costs for patternmaking jobs.” (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: Costing a patternmaking job from drawings, material prices and shop rates is calculation software does well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Changing shape

1 task

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.

Reading blueprints, drawings or written specifications to determine sizes and shapes of patterns and required machine setups
The software now makes the first pass at blueprints, drawings or written specifications, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · Core
Source: “Read blueprints, drawings, or written specifications to determine sizes and shapes of patterns and required machine setups.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial 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: Reading blueprints and written specifications to work out pattern sizes and machine setups is document work software handles well.
The five ratings: output a model can produce 3/4 · 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.

Staying human

16 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.

Fitting fasten and assembling wood parts together to form patterns, models or sections, using glue, nails, dowels, bolts and screws
This work happens in the physical world: fasten, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Fit, fasten, and assemble wood parts together to form patterns, models, or sections, using glue, nails, dowels, bolts, and screws.” (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: Gluing, nailing and screwing wood parts into a pattern is bench work 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 2/4.
Laying out patterns on wood stock and drawing outlines of units
This work happens in the physical world: patterns, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Lay out patterns on wood stock and draw outlines of units, sectional patterns, or full-scale mock-ups of products, based on blueprint specifications and sketches, and using marking and measuring devices.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 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: Laying out shapes from a drawing is easy to compute, but marking them onto boards is done in the shop.
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 3/4.
Setting up, operate and adjusting a variety of woodworking machines
This work happens in the physical world: up, operate and adjusting a variety, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Set up, operate, and adjust a variety of woodworking machines such as bandsaws and lathes to cut and shape sections, parts, and patterns, 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: Setting up and running bandsaws and lathes to a specification is hands-on machine 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.
Trimming smooth and shaping surfaces and plane, shave, file, scrape and sanding models to attain specified shapes
This work happens in the physical world: smooth, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Trim, smooth, and shape surfaces, and plane, shave, file, scrape, and sand models to attain specified shapes, using hand tools.” (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: Planing, filing, scraping and sanding wood to shape is skilled work with hand tools.
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.
Verifying dimensions of completed patterns
This work happens in the physical world: dimensions of completed patterns, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Verify dimensions of completed patterns, using templates, straightedges, calipers, or protractors.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (0–13 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Measuring tools give the numbers, but someone has to put them on the finished pattern to check it.
The five ratings: output a model can produce 0/4 · 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.
Correcting patterns to compensate for defects in castings
This work happens in the physical world: patterns, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Correct patterns to compensate for defects in castings.” (O*NET task statement)
How this row was scored
Exposure score: 25 out of 100 (13–37 allowing for uncertainty): low exposure, low confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Working out what change fixes a casting fault can be modelled, though the pattern is then corrected by hand.
The five ratings: output a model can produce 2/4 · 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 2/4.

Show the other 10 tasks

Inventorying equipment and supplies, ordering parts and tools
staying human
This work happens in the physical world: equipment, in a real place. Software cannot follow it there.
importance 3 · Core
Source: “Inventory equipment and supplies, ordering parts and tools as necessary.” (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: Reorder points and purchase orders are easily automated, though counting what is actually on the shelf is done 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 0/4 · how much data exists 3/4.
Dividing patterns into sections according to shapes of castings to facilitate removal of patterns from molds
staying human
This work happens in the physical world: patterns, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Divide patterns into sections according to shapes of castings to facilitate removal of patterns from molds.” (O*NET task statement)
How this row was scored
Exposure score: 25 out of 100 (13–37 allowing for uncertainty): low exposure, low confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Where to split a pattern so it lifts cleanly from the mold is a design decision that can be worked out on a computer.
The five ratings: output a model can produce 2/4 · 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 2/4.
Marking identifying information, colors or codes on patterns, parts and templates to indicate assembly methods
staying human
This work happens in the physical world: information, colors or codes, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Mark identifying information such as colors or codes on patterns, parts, and templates to indicate assembly methods.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 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: Working out the right codes and colors is simple, but marking them on the pattern happens in the shop.
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 3/4.
Issuing patterns to designated machine operators
staying human
This work happens in the physical world: patterns, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Issue patterns to designated machine operators.” (O*NET task statement)
How this row was scored
Exposure score: 12 out of 100 (5–19 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: Tracking which pattern goes to which operator is easy to automate, but handing the pattern over happens in the shop.
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 1/4 · how much data exists 3/4.
Selecting lumber to be used for patterns
staying human
This work happens in the physical world: lumber, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Select lumber to be used for patterns.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (0–13 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Choosing boards means looking along the grain and spotting knots and shakes, a judgment made at the timber rack.
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 1/4.
Constructing wooden models, templates, full scale mock-ups, jigs or molds for shaping parts of products
staying human
This work happens in the physical world: wooden models, templates, full scale mock-ups, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Construct wooden models, templates, full scale mock-ups, jigs, or molds for shaping parts of 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: Building the actual wooden model, jig or mold is bench work with tools in 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 2/4.
Finishing completed products or models with shellac
staying human
This work happens in the physical world: completed products, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Finish completed products or models with shellac, lacquer, wax, or paint.” (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: Applying lacquer, wax or paint to a finished model is 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.
Gluing fillets along interior angles of patterns
staying human
This work happens in the physical world: fillets along interior angles of patterns, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Glue fillets along interior angles of patterns.” (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: Gluing fillets into the interior corners of a pattern is close 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.
Repairing broken or damaged patterns
staying human
This work happens in the physical world: broken, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Repair broken or damaged patterns.” (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 a broken pattern means working on the damaged wood with tools.
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.
Collecting and storing patterns and lumber
staying human
This work happens in the physical world: patterns, in a real place. Software cannot follow it there.
importance 3 · Core
Source: “Collect and store patterns and lumber.” (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: Collecting patterns and lumber and putting them away in storage 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.

What this job pays, and how many people do it

Median pay: $49,630a 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: 220in 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: dimensions, areas, volumes and weights in, a record out. The rows above are exactly that shape: computing dimensions, areas, volumes and weights and maintaining pattern records for reference. What it cannot do is be there in the room, and that is still where fasten gets 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: fitting fasten and assembling wood parts together to form patterns, models or sections, using glue, nails, dowels, bolts and screws is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 13% of this job's task weight sits in rows the software is already learning, 6% in rows that change shape rather than disappear, and 81% in rows it is nowhere near. That is the position, measured across 20 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. Computing dimensions, areas, volumes and weights 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 dimensions, areas, volumes and weights, 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 fasten is 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 reading blueprints, drawings or written specifications to determine sizes and shapes of patterns and required machine setups. 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

You did not come here for a career change and I am not selling you one. But one road out of here is worth knowing about, so here it is with the bill attached.

Patternmakers, WoodModel Makers, Wood
a year or morematched on shared tasks
You already fit, fasten, and assemble wood parts together to form patterns, models, or sections, using…. In that job the same thing shows up as fit, fasten, and assemble wood parts together to form patterns, models, or sections, using…. Take both published task lists together and about 42% of the work in that job that the software is not taking is work you are doing today.
About 42% of it you could do on Monday. The rest is the price of the ticket.
The work the two jobs share
- You already do
  “Fit, fasten, and assemble wood parts together to form patterns, models, or sections, using glue, nails, dowels, bolts, and screws.”
  They do
  “Fit, fasten, and assemble wood parts together to form patterns, models, or sections, using glue, nails, dowels, bolts, screws, and other fasteners.”
- You already do
  “Trim, smooth, and shape surfaces, and plane, shave, file, scrape, and sand models to attain specified shapes, using hand tools.”
  They do
  “Trim, smooth, and shape surfaces, and plane, shave, file, scrape, and sand models to attain specified shapes, using hand tools.”
- You already do
  “Set up, operate, and adjust a variety of woodworking machines such as bandsaws and lathes to cut and shape sections, parts, and patterns, according to specifications.”
  They do
  “Set up, operate, and adjust a variety of woodworking machines such as bandsaws and planers to cut and shape sections, parts, and patterns, according to specifications.”
What you would not already have: Nothing in your task list touches “verify dimensions and contours of models during hand-forming processes, using templates and…”, “select wooden stock, determine layouts, and mark layouts of parts on stock…” or “fabricate work aids such as scrapers or templates”. That is the part you would be learning from scratch, and it is roughly the 58% of their durable work you do not already hold.
The honest bill
Pay: $56,550 against your $49,630 (OEWS May 2025 (both)).
- The licence gate: Default-closed. This release carries no licence-register snapshot, so I could not check whether that job is regulated, which means I have to assume it might be. Before you spend a penny, look it up on the US Labor Department’s licensed-occupations finder; the free routes below link straight to it. The route is banded a year or more because of that unknown, not in spite of it.
- The entry ticket: Typical entry-level education is published for only ten occupations in this release, and neither this job nor that one is among them. So I cannot tell you whether a qualification stands in the way. Treat that as an open question to settle before you commit, not as a green light.
- What the pay gap is telling you: $56,550 against your $49,630, 13.9% more (OEWS May 2025 (both)). A real difference, not a life-changing one. Take the move for the work, not the raise.
- What you live on meanwhile: Nobody is going to pay you to retrain. This is evenings and weekends alongside the job you already have, for a year or more, and if that is not possible right now then this route is not open right now, which is worth knowing before you start. The free American Job Center service listed below will talk training funding through with you before you pay anyone.
- Is the target job itself holding up: Model Makers, Wood scores 15/100 on this site’s own exposure measure (minimal), with 6% of its tasks in the top band. Employment projections are not published for this occupation in this release, so this is the exposure leg of the check only. It passed, which is the only reason it is here.
How long: A year or more, part-time, alongside the job you have. That band is set by the unchecked licence question and by the 58% of their work you would be learning, not by any one course.
See what AI is doing to model makers, wood

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.

Patternmakers, Metal and Plastic
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already fit, fasten, and assemble wood parts together to form patterns, models, or sections…, and their equivalent is to assemble pattern sections, using hand tools, bolts, screws, rivets, glue, or welding equipment. Across both published task lists that is about 8% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 8% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Cabinetmakers and Bench Carpenters
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already fit, fasten, and assemble wood parts together to form patterns, models, or sections…, and their equivalent is to attach parts or subassemblies together to form completed units, using glue, dowels, nails…. Across both published task lists that is about 8% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 8% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Foundry Mold and Coremakers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already divide patterns into sections according to shapes of castings to facilitate removal of…, and their equivalent is to sprinkle or spray parting agents onto patterns and mold sections to facilitate removal…. Across both published task lists that is about 7% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 7% of the durable side of that job. That is a different job, not a next step.
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: 13% of its task weight, across 20 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 fitting fasten and assembling wood parts together to form patterns, models or sections, using glue, nails, dowels, bolts and screws 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 Furniture makers and other craft woodworkers 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 Furniture makers and other craft woodworkers. 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.
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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

No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for patternmakers / wood, and we are not going to point you at the nearest one and call it a fit.

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 13% of the work on this page is already inside what they can do.

Try The AI Authority free →

7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.

The AI Authority is a general community about working with AI, not a course for patternmakers / wood. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

Nearby moves

The jobs above, as pages you can read the same way as this one. Your job shares its core work with these. That is what the match is, and it is all it is.

Model Makers, Wood →About 42% of it you could do on Monday. The rest is the price of the ticket.

Noted, and thank you. We’ll email you if a Space for patternmakers / wood 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 patternmakers / wood 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 patternmakers / wood 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 patternmakers / wood 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 Patternmakers, Wood?: Not as a job, but it is already doing parts of the work. Across the 20 official task statements scored for Patternmakers, Wood (United States, SOC 51-7032), 13% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 21 out of 100 (range 17–26, band: low). 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 “Patternmakers, Wood” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Compute dimensions, areas, volumes, and weights” (100/100, very high); “Maintain pattern records for reference” (75/100, high); “Estimate costs for patternmaking jobs” (75/100, high). 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 “Patternmakers, Wood” stay human?: About 81% 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: “Collect and store patterns and lumber” (0/100, minimal); “Repair broken or damaged patterns” (0/100, minimal); “Glue fillets along interior angles of patterns” (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 “Patternmakers, Wood” do about AI?: Start from the ledger rather than the headline: 13% of this job's weighted core work is exposed, and roughly 81% 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 Patternmakers, Wood 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 20 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

About the data on this page

2 rows are marked low confidence, so treat them as a ballpark rather than a fine measurement.
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 2026-08-05.
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.

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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.