Cabinetmakers and Bench Carpenters
In short: today's best AI models could do about 17% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 19% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 81% of the time, stays with people.
Cut, shape, and assemble wooden articles or set up and operate a variety of woodworking machines, such as power saws, jointers, and mortisers to surface, cut, or shape lumber or to fabricate parts for wood products.
77,170 people do this job in the US. $46,680 a year.
Reviewed on October 1, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on0 h
- A person checks AI's work7 h
- Desk work AI can't do yet0 h
- Stays with people33 h
Cabinetmakers and Bench Carpenters, now: of a 40-hour week, AI could take on 0 hours, 7 hours become checking its work, 0 hours are desk work it can't do yet, and 33 hours stay with people.
The largest pieces: Plan the build from the drawings (about 3 h, a person checks); Program the machines (about 1 h, a person checks); Design furniture on the computer (about 1 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 15%
- 4%
- 0%
- 4%
- 78%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 17% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 9%. Today's estimate: 18%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, 0.011% went to this job's tasks in May 2026, the 358th largest of the 447 jobs that showed up at all; 1 of its 20 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0088% to none (released February and March 2025); none to 0.0025% (August 2025 to February 2026); 0.011% to 0.011% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0088% | 546 of 708 | 3 of 20 |
| Released March 2025 | none | n/a | 0 of 20 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 20 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 20 |
| The week of Feb 5, 2026 (released March 2026) | 0.0025% | 628 of 677 | 1 of 20 |
| April 2026 (released June 2026) | 0.011% | 343 of 434 | 1 of 20 |
| May 2026 (released June 2026) | 0.011% | 358 of 447 | 1 of 20 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 89% of this job's working time as physical work. For 85% of the working time, a robot has been shown doing most of the task somewhere: 85% in a purpose-built cell. 0.85 of 3, the 202nd highest of the 923 jobs.
- Not physical 11%
- No robot shown 4%
- In a purpose-built cell 85%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
81% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Make and assemble components, the hands-on work, 20%
- Repair furniture, the hands-on work, 9%
- Assemble the piece, the hands-on work, 8%
- Cut and fit joints, the hands-on work, 6%
- Run woodworking machines, the hands-on work, 6%
- Prepare surfaces for finishing, the hands-on work, 5%
What becomes checking the machine
19% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it.
- Plan the build from the drawings, costly if wrong, 7%
- Design furniture on the computer, costly if wrong, 4%
- Program the machines, costly if wrong, 4%
- Estimate materials, costly if wrong, 2%
- Specify projects with customers, costly if wrong, 0.9%
- Mark out parts from plans, costly if wrong, 0.6%
What to learn
- The hands-on craft. About 78% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- Briefing a model and checking its drafts. About 15% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 20 tasks from .
| Task | ||||
|---|---|---|---|---|
| Produce or assemble components of articles, such as store fixtures, office equipment, cabinets, or high-grade furniture.Building the parts and putting them together.Done hourly or more by most who do it. Robots: in a purpose-built cell, Ro-Bois-Tic robotic nesting/edgebanding/boring line (KUKA robot with Thermwood, Fravol, Omal machines) (CNC Automation / Machineries AutomaTech / KUKA) (sold). Anthropic's rating. | 20% | 3.3 h50 min to 1.7 work days | Hands-on 100% | Stays with people |
| Establish the specifications of articles to be constructed or repaired, or plan the methods or operations for shaping or assembling parts, based on blueprints, drawings, diagrams, or oral or written instructions.Working out the method and the specifications, from the drawings and the instructions.Done daily by most who do it. | 10% | 1.3 h25 min to 3.3 h | Documents 70%, in person 30% | 70%Desk part half by now |
| Repair or alter wooden furniture, cabinetry, fixtures, paneling, or other pieces.Repairs at the bench.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 9% | 2.5 h38 min to 1.3 work days | Hands-on 100% | Stays with people |
| Attach parts or subassemblies together to form completed units, using glue, dowels, nails, screws, or clamps.Gluing, doweling and clamping.Done daily by most who do it. Robots: in a purpose-built cell, HOMAG CABTEQ T-500 carcass joining press (with turner and belt conveyors) (sold). Anthropic's rating. | 8% | 1.3 h25 min to 4.2 h | Hands-on 100% | Stays with people |
| Cut timber to the right size, and shape and trim parts of joints to ensure a snug fit, using hand tools, such as planes, chisels, or wood files.Planes, chisels and files on the joints.Done daily by most who do it. Robots: in a purpose-built cell, Weinig SOLID CUT TF 2000 / OptiCut optimizing cross-cut saws (Michael Weinig AG) (sold). Anthropic's rating. | 6% | 1.1 h17 min to 2.5 h | Hands-on 100% | Stays with people |
| Set up or operate machines, including power saws, jointers, mortisers, tenoners, molders, or shapers, to cut, mold, or shape woodstock or wood substitutes.Setting up and running saws, jointers and shapers.Done daily by most who do it. Robots: in a purpose-built cell, WEINIG/Raimann VarioRip 310 M2 with RipAssist (Michael Weinig AG) (sold). Anthropic's rating. | 6% | 50 min17 min to 2.5 h | Hands-on 100% | Stays with people |
| Trim, sand, or scrape surfaces or joints to prepare articles for finishing.Sanding and scraping.Done daily by most who do it. Robots: in a purpose-built cell, Omnirobotic PSA-80 PRO Panel Sanding Assistant (AutonomyOS) (sold). Anthropic's rating. | 5% | 50 min17 min to 2.5 h | Hands-on 100% | Stays with people |
| Match materials for color, grain, or texture, giving attention to knots or other features of the wood.Choosing pieces by eye.Done daily by most who do it. Robots: in a purpose-built cell, Opti-Match (model 35A) (Cameron Automation / James L. Taylor Manufacturing) (deployed). Anthropic's rating. | 5% | 38 min13 min to 1.7 h | Hands-on 100% | Stays with people |
| Design furniture, using computer-aided drawing programs.Drawing the design in the software.Done more than monthly by most who do it. | 4% | 3.3 h50 min to 1.3 work days | Documents 100% | 80%Half by now |
| Dip, brush, or spray assembled articles with protective or decorative finishes, such as stain, varnish, paint, or lacquer.Staining, varnishing or spraying.Done more than yearly by most who do it.Robots: in a purpose-built cell, CMA Robotics ADPS robotic spraying cell (Robotic Solutions LLC) (deployed). Anthropic's rating. | 4% | 1.3 h25 min to 3.3 h | Hands-on 100% | Stays with people |
| Program computers to operate machinery.Programming the cutting machines at the console.Done daily by most who do it. | 4% | 1.7 h25 min to 5 h | Systems 100% | 94%Half by now |
| Measure and mark dimensions of parts on paper or lumber stock prior to cutting, following blueprints, to ensure a tight fit and quality product.Marking the stock from the drawings.Done daily by most who do it. Robots: in a purpose-built cell, Hundegger K2-Industry (marker / inkjet marking system options) (Hans Hundegger AG) (sold). Anthropic's rating. | 3% | 38 min13 min to 1.7 h | Hands-on 80%, documents 20% | 20%Desk part half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Cabinetmakers and Bench Carpenters is within reach of AI now?
- An estimated 18% of the working time is within reach of AI models now and 19% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Cabinetmakers and Bench Carpenters come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Plan the build from the drawings (70% of the task's time now); Program the machines (94% of the task's time now, 100% by the end of 2028); and Design furniture on the computer (80% of the task's time now, 100% by the end of 2028).
- Which tasks of Cabinetmakers and Bench Carpenters stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Make and assemble components; Repair furniture; and Assemble the piece. Together such tasks are about 75% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Cabinetmakers and Bench Carpenters learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the hands-on craft; reviewing work you did not do yourself; and briefing a model and checking its drafts. By the end of 2028 on the long-run pace at four in five, about 81% of the working time stays with people, 19% becomes checking a model's work and 0% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Cabinetmakers and Bench Carpenters?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.011% went to this job's tasks, the 358th largest share of the 447 jobs that showed up; 1 of its 20 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Cabinetmakers and Bench Carpenters?
- Anthropic's robot exposure rating (September 2026) finds 89% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 85% of the working time. Its index is 0.85 of 3. One example: Ro-Bois-Tic robotic nesting/edgebanding/boring line (KUKA robot with Thermwood, Fravol, Omal machines) for "make and assemble components". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 20 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on October 1, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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