COOKED
The work is loading materials, setting glue temperature and flow, watching the bead, and pulling defective parts on a repetitive line inside a controlled plant — physical enough that language AI can't touch it, but standardized enough that vision-inspection systems and automated dispensing cells already replace it in modernized factories. There is no license, no client relationship, and little discretion beyond stopping the line and calling maintenance. Displacement here comes from capital equipment and machine vision, not chatbots, which means it arrives slower but with fewer remaining niches.
Part 2020 shock, part continued decline in the years since.
Median pay $34,340 → $46,460 +8.2% 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
+1% 12,200 → 12,300 on the projections basis
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +1% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.
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.
~1,300 openings a year on average, including replacing people who leave.
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Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier An automated dispensing cell can lay a bead on a fixtured part all day, but it can't hand-feed warped veneer, re-thread a web after a break, clear a carbonized hot-melt nozzle, or re-glue a mis-fed panel — those recovery tasks are why this sits at 11 and not at 5 with pure button-tending.
Some physical or field component You are on your feet at the machine loading stock, clamping and unclamping work, wiping adhesive off rollers and handling 350°F hot melt and solvent fumes — real physical exposure, but inside a lit plant with a fixed machine and a written PPE rule, which is what keeps this at 12 rather than the 15+ of a millwright crawling into equipment on a customer site.
No licence, no signature requirement There is no state licence, no board, no certificate you carry between employers — the plant's OSHA lockout/tagout and respirator training is company paperwork, not a credential that makes you personally answerable for the bond holding, so 1 is nearly the floor.
Executes defined procedures on defined inputs Temperature, open time, pressure and dwell come off a spec sheet or the job ticket, and your real calls are narrow: scrap this part or pass it, stop the line or keep running, page maintenance now or after the run — genuine but bounded decisions, which is a 5 rather than a 2.
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 (11/20 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 (1/20) 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 (5/20) 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 9 of this occupation's 32 points (28%).
Embodiment (12/20) 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.
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 49/100 — EXPOSED.
Sign-off authority on bond process records: surface prep window, open time, cure profile deviation, and disposition of a suspect bond line that cannot be nondestructively verified. FAA and MRB (Material Review Board) practice in aerospace already treats bonded-joint disposition as a documented human call because bond strength is not fully inspectable. If the operator's signature is the release for a lot whose failure mode is catastrophic and invisible, the role owns a consequential ambiguous call.
Task-mix shift as high-volume dispensing cells absorb the routine tier. The genuinely two-tier split here is repetitive line tending (automatable now) versus low-volume, large-format, or variable-geometry bonding — composite aerostructures, wind blade shear webs, bus and rail body panels, prototype and repair work — where fixturing changes per part, surface prep is manual, and no fixed dispensing path exists. If employment concentrates in the aerospace/composites/repair segment, the remaining job is setup and diagnosis rather than loading.
Operator-level certification becoming a hard audit requirement rather than a paperwork nicety: NADCAP AC7118 (adhesive bonding) accreditation and Boeing/Airbus process specs already require named, qualified bonding operators with documented training records for structural bonds, and FDA 21 CFR 820 / ISO 13485 process-validation rules push the same for implant and catheter bonding. If a primary-structure or Class III device bond can only be released with a qualified operator's name on the lot record — and an AS9100 or FDA audit finding voids the lot without it — the qualification becomes a personal, non-transferable gate, not just a skill.
Migration of work from plant floor to field bonding: on-wing composite patch repair, wind turbine blade leading-edge and shear-web repair at height, rail car and marine hull rebonding. These are unstructured, weather- and access-constrained environments where no dispensing cell can be installed; GE Vernova/Vestas blade repair programs and MRO composite repair shops already staff this way.
The limit. The liability and judgment levers only reach the minority of these 11,500 workers in aerospace, defense, and medical device plants; for consumer-goods, packaging, furniture, and footwear bonding lines there is no license, no signature, and no buyer who cares who ran the glue head, and no plausible route to one. Trust premium is omitted deliberately — nobody specifies a human adhesive operator by name. Even a full stack of these levers moves the occupation out of the bottom tier only for the certified aerospace/medical slice; the aggregate ceiling is roughly the mid-50s, and the routine-line population is not reachable by any of it.
| Dallas-Fort Worth-Arlington, TX | 460 | $51,540 +11% |
| Hickory-Lenoir-Morganton, NC | 390 | $33,870 -27% |
| Los Angeles-Long Beach-Anaheim, CA | 350 | $39,780 -14% |
| Eugene-Springfield, OR | 300 | $49,180 +6% |
| Seattle-Tacoma-Bellevue, WA | 250 | $100,830 +117% |
| Charlotte-Concord-Gastonia, NC-SC | 220 | $34,550 -26% |
| Greensboro-High Point, NC | 220 | $34,790 -25% |
| Cincinnati, OH-KY-IN | 180 | $45,100 -3% |
| Seattle-Tacoma-Bellevue, WA | 250 | $100,830 +117% |
| Little Rock-North Little Rock-Conway, AR | 60 | $61,400 +32% |
| Minneapolis-St. Paul-Bloomington, MN-WI | 100 | $60,290 +30% |
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 32. 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.