EXPOSED
This job already sits inside the automation it tends: the machine does the weld, and the operator loads parts, sets parameters, watches the arc, and pulls bad pieces. Modern cells with vision-guided seam tracking, adaptive parameter control, and automated loaders erode the tending and monitoring share fast, while the setup, fixturing, and troubleshooting tier — physically present, hands in the cell — holds up better. Employment is already small (31,600) and concentrated in high-volume manufacturing, where capital spending on robotics is exactly what shrinks this title.
Nearly all of this fall was the 2020 shock. It has been climbing back since.
Median pay $38,310 → $47,920 +0.1% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
-9%
Percentage only. The projection counts a different population from the 31,600 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -9% by 2034. This is the case where the score and the forecast agree, and it is the one worth taking seriously.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~3,200 openings a year on average, including replacing people who leave.
BuilderFabricatorMig WelderRod WelderSpot WelderMill OperatorWeld OperatorBraze OperatorField OperatorFurnace BrazerLaser OperatorMachine BurnerMachine WelderRobotic WelderAluminum WelderReflow OperatorBillet AssemblerCertified WelderExplosion WelderInduction BrazerMachine OperatorWelding OperatorIndustrial WelderOxygraph Operator
Holding it up: embodiment . Weakest point: trust premium .
Mixed — a routine tier and a judgment tier Loading fixtures, hitting cycle start, watching for burn-through and gauging weld bead against a go/no-go sample are the daily core, and all four are already handled in newer cells by part-present sensors, adaptive current control and post-weld vision inspection — the 8 rather than 4 reflects the setup tier that survives: dialing in wire feed and gas flow on a new part number, shimming a fixture that's drifted, and diagnosing why the tip keeps burning back.
Hands-on in uncontrolled environments You are inside the guarding to change contact tips, clear spatter off the nozzle, re-clamp a warped weldment and reach into a cell that runs hot, bright and full of fume — 15 not 19 because the cell floor, the fixture and the part geometry are engineered and repeatable, unlike a structural welder working off a beam in weather.
Certification preferred, not legally required No state licence gates machine welding; a plant may want an AWS D1.1 or D17.1 procedure qualification or a Section IX operator qualification for pressure work, and that certifies the welding procedure and your ability to run it — it doesn't make you the person a failure lands on, which is the QC inspector and the engineer who wrote the WPS.
Executes defined procedures on defined inputs Decisions are bounded by the WPS, the travel-speed and amperage window on the setup sheet, and the reject criteria on the visual-inspection card — you decide whether a bead undercuts badly enough to scrap and when to call maintenance, real calls but ones with a written answer and a supervisor to escalate to.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (8/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (5/20) is whether the law requires a licensed human to sign. Trust premium (3/20) is whether buyers specifically pay for a person. Judgment and accountability (6/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 14 of this occupation's 37 points (38%).
Embodiment (15/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
Furniture Finishers EXPOSED
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 52/100, still EXPOSED.
Genuine two-tier job: if the loading/tending/visual-inspection tier is absorbed by cobot loaders and in-process vision, the surviving title is fixture design, distortion control, weld-defect root-cause on new alloys (aluminum, high-strength steel in EV battery trays), and requalifying WPS after any parameter change. Task-mix shift alone raises resistance without any regulatory move.
Code-driven welder/operator qualification tied to a named person: ASME Section IX and AWS D1.1 already require a qualified welding operator and a signed WPS/PQR record for pressure vessels, structural steel, and nuclear work. If AWS/ASME tighten machine-welding rules so that an AWS Certified Welding Inspector or CWI-supervised operator must personally sign each production run's parameter sheet and destructive-test coupon — rather than accepting machine data logs — the sign-off attaches to a human. Watch ASME BPV Section IX ballot items on automated/adaptive-parameter welding and NRC 10 CFR 50 App. B supplier audits.
Migration of the remaining work toward non-repeatable settings — shipyard modules, aerospace repair, field pipeline tie-ins where the cell must be rigged in place. Submerged-arc and orbital equipment set up on-site in confined or overhead positions resists fixturing automation more than a factory cell does.
Authority to stop the line on a suspected weld defect, formalized in contract: USW and IAM agreements at some fabricators already carry quality-hold language. If defect-disposition authority (scrap/rework/accept) is explicitly assigned to the operator rather than a quality engineer or the machine's own accept/reject threshold, the consequential call is owned.
The limit. Trust premium has no realistic route — buyers of welded assemblies specify code compliance and NDT results, never a human hand. And any liability gain lands on the certified-inspector tier, which is a different, smaller title; the 51-4122 headcount can shrink even as the surviving role scores higher.
| Detroit-Warren-Dearborn, MI | 1,190 | $44,060 -8% |
| Los Angeles-Long Beach-Anaheim, CA | 830 | $45,990 -4% |
| Grand Rapids-Wyoming-Kentwood, MI | 730 | $41,760 -13% |
| Nashville-Davidson--Murfreesboro--Franklin, TN | 720 | $51,290 +7% |
| Houston-Pasadena-The Woodlands, TX | 700 | $54,500 +14% |
| Indianapolis-Carmel-Greenwood, IN | 550 | $38,970 -19% |
| Louisville/Jefferson County, KY-IN | 460 | $50,740 +6% |
| New York-Newark-Jersey City, NY-NJ | 440 | $57,900 +21% |
| Tuscaloosa, AL | 40 | $82,250 +72% |
| Phoenix-Mesa-Chandler, AZ | 230 | $75,200 +57% |
| New Orleans-Metairie, LA | 60 | $74,910 +56% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 37. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.