EXPOSED
The core loop — load product, set time/temperature, watch gauges, pull batches, log readings, clean the equipment — is physical work in a food plant, which shields it from language AI but not from the PLC-and-sensor automation that has been eating these lines for decades. Recipe adherence, batch logging, and process-parameter monitoring are already handled by control systems on modern lines; what keeps a human on the floor is unjamming conveyors, hand-loading awkward product, sanitation, and catching an off-color or off-texture batch. There is no license, no signature, and no customer relationship to defend the role.
Roughly flat across the period, with year-to-year wobble.
Median pay $31,110 → $41,590 +6.9% 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
+0.6% 29,700 → 29,900 on the projections basis
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +0.6% 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.
~4,400 openings a year on average, including replacing people who leave.
FryerBoilerCookerMasherScalderSteamerGum CookGum MakerChip FryerFish FryerBrine MakerCorn CookerDonut FryerDough MakerKettle CookNut SteamerVat SkimmerBakery FryerSteam TenderSugar BoilerTripe CookerCasing CookerCooker TenderKettle Tender
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Setting fryer or retort time-and-temperature, holding a hold-tube at 161°F, and logging CCP readings are already PLC-and-recorder functions on any line built this century, but hand-loading irregular product into baskets, clearing a jammed conveyor mid-cook, breaking down and sanitizing a kettle, and eyeballing a batch that came out pale or mushy keep enough of the shift unautomated to hold this at 11 rather than down in the single digits.
Hands-on in uncontrolled environments The shift is spent on a wet, hot plant floor moving 40-pound baskets and totes, reaching into steam-jacketed kettles and fryers, hosing down and reassembling equipment on sanitation, and working around live steam, hot oil, and moving belts — uncontrolled enough to sit at 14, short of 18 because it is one fixed plant with guarded machines rather than an unpredictable outdoor or client site.
No licence, no signature requirement No state license, no board, no personal signature: the plant's HACCP plan and the PCQI or QA manager who wrote it carry the food-safety accountability, and a food-handler card plus in-house line training is the whole credential wall, which is why this lands at 2 rather than 0-only-because-you-initial-the-cook-log.
Executes defined procedures on defined inputs Cook parameters come from a written recipe and the HACCP critical limits, deviations go to QA or the supervisor rather than being resolved on the floor, and the discretion you actually own — call this batch off-texture, stop the line for a jam, adjust for a slightly wetter incoming lot — is real but bounded, putting it at 5 rather than in the procedural-only 0-2 range.
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 (2/20) 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 10 of this occupation's 35 points (29%).
Embodiment (14/20) 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.
Butchers and Meat Cutters EXPOSED
Cooks, Institution and Cafeteria 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 49/100, still EXPOSED.
Task-mix shift: as PLC control absorbs time/temp setting, gauge watching and batch logging, what remains is jam clearing, hand-loading irregular product, sanitation teardown in confined wet spaces, and sensory catch of off-batches. That residual bundle is genuinely harder to automate than the tier being taken. The score rises as the routine tier disappears — visible as job postings shifting from 'operator' to 'line technician/sanitation' language.
FDA FSMA preventive-controls rules already require a 'preventive controls qualified individual' (PCQI) to validate and sign off on critical control points; if FDA or a large customer audit scheme (SQF, BRCGS) tightens this so that a named, trained human operator must personally verify and initial each thermal-process CCP deviation rather than accepting automated sensor logs, the tender role acquires a documentary signature function. Low-acid canned food regulation (21 CFR 113) already mandates certified retort operator supervision — extension of that certification model beyond retorts to broader cooking lines is the specific watchable change.
If a food-safety recall or listeria outbreak leads to criminal exposure for line-level personnel (as in the Blue Bell and Peanut Corporation of America prosecutions, which reached managers), and firms respond by making the operator on shift the documented decision-owner for hold/release of a suspect batch, the role owns a consequential ambiguous call. Watch for 'operator authority to stop the line' clauses in HACCP plans and union contracts.
If plant footprints keep favoring high-mix, short-run co-packing (private label, allergen-segregated runs, frequent changeovers) over single-product continuous lines, the environment stays unpredictable: manual changeover, allergen washdown, varied product geometry. Watchable in co-packer capacity growth and changeover frequency per shift.
The limit. No plausible route to trust premium: buyers of packaged food never learn who tended the cooker and do not pay for it. Even with every lever, this stays a production job whose core loop is the archetype of what PLC automation was built for; the ceiling is roughly mid-50s and the headcount trend can fall even as the per-worker score rises.
| Chicago-Naperville-Elgin, IL-IN | 1,900 | $44,280 +6% |
| New York-Newark-Jersey City, NY-NJ | 880 | $41,590 +0% |
| Dallas-Fort Worth-Arlington, TX | 850 | $35,240 -15% |
| Houston-Pasadena-The Woodlands, TX | 600 | $32,180 -23% |
| San Antonio-New Braunfels, TX | 530 | $30,340 -27% |
| Baltimore-Columbia-Towson, MD | 520 | $36,740 -12% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 510 | $38,890 -6% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 490 | $39,790 -4% |
| Cedar Rapids, IA | 40 | $63,690 +53% |
| Modesto, CA | 140 | $59,010 +42% |
| Kiryas Joel-Poughkeepsie-Newburgh, NY | 80 | $57,680 +39% |
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 35. 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.