Welders, Cutters, Solderers, and Brazers
In short: today's best AI models could do about 11% 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 the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 89% of the time, stays with people.
Use hand-welding, flame-cutting, hand-soldering, or brazing equipment to weld or join metal components or to fill holes, indentations, or seams of fabricated metal products.
416,210 people do this job in the US. $53,750 a year.
Reviewed on September 30, 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 work4 h
- Desk work AI can't do yet0 h
- Stays with people36 h
Welders, Cutters, Solderers, and Brazers, now: of a 40-hour week, AI could take on 0 hours, 4 hours become checking its work, 0 hours are desk work it can't do yet, and 36 hours stay with people.
The largest pieces: Choose welding methods (about 2 h, a person checks); Make templates from blueprints (about 1 h, a person checks); Plan the job from the drawings (under an hour, 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.
- 11%
- 0%
- 0%
- 2%
- 88%
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 11% 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, 10%. Today's estimate: 11%.
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, no reportable share went to this job's tasks in May 2026; 0 of its 30 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0037% to 0.0021% (released February and March 2025).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0037% | 643 of 708 | 1 of 30 |
| Released March 2025 | 0.0021% | 666 of 703 | 1 of 30 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 30 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 30 |
| The week of Feb 5, 2026 (released March 2026) | none | n/a | 0 of 30 |
| April 2026 (released June 2026) | none | n/a | 0 of 30 |
| May 2026 (released June 2026) | none | n/a | 0 of 30 |
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 93% of this job's working time as physical work. For 90% of the working time, a robot has been shown doing most of the task somewhere: 84% in a purpose-built cell, 6% in a structured facility. 0.96 of 3, the 136th highest of the 923 jobs.
- Not physical 7%
- No robot shown 2%
- In a purpose-built cell 84%
- In a structured facility 6%
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
89% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Weld in all positions, the hands-on work, 11%
- Weld different metals and alloys, the hands-on work, 8%
- Repair metal products, the hands-on work, 7%
- Set up and run welding equipment, the hands-on work, 5%
- Prepare surfaces for welding, the hands-on work, 4%
- Align and clamp workpieces, the hands-on work, 4%
What becomes checking the machine
11% 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.
- Choose welding methods, severe if wrong, 5%
- Make templates from blueprints, costly if wrong, 3%
- Plan the job from the drawings, costly if wrong, 2%
- Set up torches and consumables, costly if wrong, 0.5%
What to learn
- The hands-on craft. About 88% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
- 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 11% 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.
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 . 30 tasks from .
| Task | ||||
|---|---|---|---|---|
| Weld components in flat, vertical, or overhead positions.Welding flat, vertical and overhead.Done daily by most who do it. Robots: in a purpose-built cell, Path Robotics AW-3 / AF-1 autonomous robotic welding cells (deployed). Anthropic's rating. | 11% | 50 min13 min to 2.5 h | Hands-on 100% | Stays with people |
| Weld separately or in combination, using aluminum, stainless steel, cast iron, and other alloys.Welding aluminum, stainless, cast iron and other alloys.Done daily by most who do it. Robots: in a purpose-built cell, Path Robotics intelligent welding cells (Obsidian AI) (deployed). Anthropic's rating. | 8% | 1.3 h17 min to 3.3 h | Hands-on 100% | Stays with people |
| Develop templates and models for welding projects, using mathematical calculations based on blueprint information.Working out the dimensions and making the template.Done daily by most who do it. Robots: in a purpose-built cell, ProNest LT CAD/CAM driving CNC plasma/waterjet/oxyfuel cutting tables (Hypertherm) (sold). Anthropic's rating. | 7% | 1.1 h25 min to 2.1 h | Documents 50%, hands-on 50% | 50%Desk part half by now |
| Determine required equipment and welding methods, applying knowledge of metallurgy, geometry, and welding techniques.Working out the process and settings for the metal and the joint.Done daily by most who do it. | 7% | 38 min13 min to 1.3 h | Documents 70%, hands-on 30% | 70%Desk part half by now |
| Repair products by dismantling, straightening, reshaping, and reassembling parts, using cutting torches, straightening presses, and hand tools.Taking the piece apart, straightening it, and putting it back together.Done more than monthly by most who do it. Robots: no robot shown. Anthropic's rating. | 7% | 2.1 h50 min to 4.2 h | Hands-on 100% | Stays with people |
| Recognize, set up, and operate hand and power tools common to the welding trade, such as shielded metal arc and gas metal arc welding equipment.Choosing, setting up and running the welding gear.Done daily by most who do it. Robots: in a purpose-built cell, Path Robotics AW-3 / AF-1 autonomous welding cells (Obsidian AI) (deployed). Anthropic's rating. | 5% | 25 min8 min to 50 min | Hands-on 100% | Stays with people |
| Prepare all material surfaces to be welded, ensuring that there is no loose or thick scale, slag, rust, moisture, grease, or other foreign matter.Cleaning the metal back to bright before the weld.Done daily by most who do it. Robots: in a purpose-built cell, Cohesive Robotics Smart Finishing Robotic Workcell (sold). Anthropic's rating. | 4% | 25 min8 min to 50 min | Hands-on 100% | Stays with people |
| Align and clamp workpieces together, using rules, squares, or hand tools, or position items in fixtures, jigs, or vises.Setting the pieces true in the jig or vise.Done daily by most who do it. Robots: in a purpose-built cell, Path Robotics AF-1 Autonomous Fit-up cell (sold). Anthropic's rating. | 4% | 25 min8 min to 50 min | Hands-on 100% | Stays with people |
| Monitor the fitting, burning, and welding processes to avoid overheating of parts or warping, shrinking, distortion, or expansion of material.Keeping an eye on heat and movement as the weld goes in.Done daily by most who do it. Robots: in a purpose-built cell, Path Robotics AW-3 / Obsidian Intelligent Welding Cell (sold). Anthropic's rating. | 4% | 29 min8 min to 1.7 h | Hands-on 100% | Stays with people |
| Guide and direct flames or electrodes on or across workpieces to straighten, bend, melt, or build up metal.Running the torch or electrode along the work.Done daily by most who do it.Robots: in a structured facility, Avweld robotic cladding & hardfacing cells (ABB 6-axis robots, gantry robot, laser cladding) (sold). Anthropic's rating. | 4% | 38 min8 min to 1.7 h | Hands-on 100% | Stays with people |
| Chip or grind off excess weld, slag, or spatter, using hand scrapers or power chippers, portable grinders, or arc-cutting equipment.Chipping and grinding the finished weld.Done daily by most who do it. Robots: in a purpose-built cell, FANUC M-710iC weld grinding cell (Acme Manufacturing integration) (sold). Anthropic's rating. | 4% | 25 min8 min to 58 min | Hands-on 100% | Stays with people |
| Analyze engineering drawings, blueprints, specifications, sketches, work orders, and material safety data sheets to plan layout, assembly, and operations.Reading the drawings and the order and laying out the sequence. | 3% | 38 min17 min to 1.7 h | Documents 60%, in person 40% | 60%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.
- Welding, Soldering, and Brazing Machine Setters, Operators, and Tenders11% now, 11% by 2028
- Structural Metal Fabricators and Fitters4% now, 4% by 2028
- Aircraft Structure, Surfaces, Rigging, and Systems Assemblers4% now, 4% by 2028
- Engine and Other Machine Assemblers9% now, 9% by 2028
- Boilermakers3% now, 3% by 2028
- Electric Motor, Power Tool, and Related Repairers3% now, 3% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
- Fabricated Metal Product Manufacturing (3323 and 3324 only)70,020 people
- Machinery Manufacturing (3331, 3332, 3334, and 3339 only)56,750 people
- Fabricated Metal Product Manufacturing (3321, 3322, 3325, 3326, and 3329 only)25,910 people
- Motor Vehicle Body and Trailer Manufacturing22,560 people
- Machine Shops; Turned Product; and Screw, Nut, and Bolt Manufacturing15,760 people
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 Welders, Cutters, Solderers, and Brazers is within reach of AI now?
- An estimated 11% of the working time is within reach of AI models now and 11% 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 Welders, Cutters, Solderers, and Brazers 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: Choose welding methods (70% of the task's time now); Make templates from blueprints (50% of the task's time now); and Plan the job from the drawings (60% of the task's time now).
- Which tasks of Welders, Cutters, Solderers, and Brazers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Weld in all positions; Weld different metals and alloys; and Repair metal products. Together such tasks are about 81% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Welders, Cutters, Solderers, and Brazers 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; judgment where errors are severe; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 89% of the working time stays with people, 11% 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 Welders, Cutters, Solderers, and Brazers?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. 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 Welders, Cutters, Solderers, and Brazers?
- Anthropic's robot exposure rating (September 2026) finds 93% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 90% of the working time, 6% in a structured facility. Its index is 0.96 of 3. One example: Avweld robotic cladding & hardfacing cells (ABB 6-axis robots, gantry robot, laser cladding) for "direct the flame or arc". 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 30 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 September 30, 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.
This job in your state or metro area
Embed these figures on your site
A small card with the share of working time within reach now and at the end of 2027, 2028 and 2030, the date and a link back. Free under CC BY 4.0; the card carries the credit.
Your own version of this job
The page above is the occupation. Your job is your title and what you actually do: give both, and they are read against these tasks in your browser, nothing sent anywhere. The headline is free: how much of your working time is within reach now and by the end of 2028, and how many of the tasks your description names.
The full personal report is $19, to print or save as a PDF: every task with when it comes within reach, which ones your description names, the parts of your description the task list does not cover, what stays with you, what becomes checking the machine and what to learn.