SAFE
The core of this job — tasting and adjusting dishes, running a hot line through a Saturday rush, butchering and plating, correcting a cook's technique mid-service — happens with hands in an unpredictable physical space that robotics cannot yet handle outside narrow fast-food assembly. What AI does erode is the paperwork tier: menu drafting, recipe scaling, food-cost spreadsheets, par-level ordering, scheduling, and inventory reconciliation. No license shields the role (ServSafe-style food safety certification is required in most jurisdictions but is a low bar), so the moat is physical and reputational rather than regulatory.
Dipped in 2020, then grew past where it started.
Median pay $51,530 → $62,470 -3.0% 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
+7.1% 197,300 → 211,300 on the projections basis
Hard to automate, and growing
The work resists current AI and the BLS projects +7.1% more of these jobs by 2034. Note that safe does not mean well paid — several of the fastest-growing resistant occupations are among the lowest paid on the register.
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.
~24,400 openings a year on average, including replacing people who leave.
ChefCookBakerCake IcerHead ChefHead CookPie MakerSous ChefCake MakerCake MixerHead BakerPizza ChefSalad ChefSushi ChefChocolatierMaster ChefPantry ChefPastry ChefPastry CookBanquet ChefCake FrosterChef ManagerConfectionerCook Manager
Holding it up: embodiment . Weakest point: liability shield .
Tasks largely resist digitisation Seasoning by taste, judging a sear by sound and smell, breaking down a whole fish, and expediting twelve tickets at staggered fire times are not tasks that decompose into machine-readable steps, which puts this at 16 rather than 20 only because the back-office layer — menu costing, prep lists, scheduling, vendor ordering — is genuinely being taken over.
Hands-on in uncontrolled environments You spend the shift standing on rubber mats between a 500°F flat-top and a fryer, moving through a crowded line with knives and hot pans, in a space whose layout, ticket volume, and equipment failures change hourly — this is about as uncontrolled as an indoor workplace gets, hence 19.
Certification preferred, not legally required ServSafe or an equivalent food handler card is legally mandated in most states and the person-in-charge requirement under the FDA Food Code names a certified manager, but the exam is a few hours of study, there is no board that can strip your career, and the restaurant's insurance and the owner absorb a foodborne illness claim — that combination is a 5, not a 0 and not an 11.
Exists to be accountable for ambiguous calls You decide whether a case of fish that smells marginal goes out or gets dumped, whether to 86 a dish mid-service, how to reconfigure the line when a cook walks out at 7pm, and how to hit food cost without visibly cutting quality — real ambiguity with money and diner safety attached, short of 18 because a bad call rarely kills anyone and is usually recoverable the next service.
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 (16/20 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 (13/20) is whether buyers specifically pay for a person. Judgment and accountability (15/20) 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 33 of this occupation's 68 points (49%).
Embodiment (19/20) 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 82/100, still SAFE.
Allergen-disclosure liability naming a responsible kitchen manager, e.g. an FASTER Act-style sesame/top-9 labeling extension to foodservice, or state menu-allergen laws (Illinois, Massachusetts, Rhode Island already require allergen-trained managers on duty) enforced with fines or criminal negligence exposure after a fatality
Task-mix shift: as ordering, par levels, costing, and scheduling are absorbed by inventory/POS AI, the residual job concentrates in the judgment tier — tasting and correcting, staff training, vendor and product selection, service recovery. The role does have two genuine tiers, so shedding the clerical one raises the share of work AI cannot do
State/local health codes moving from ServSafe-style certificate-holder rules to a named 'certified food protection manager' who must be personally on premises and signs HACCP logs with personal liability — already the structure in FDA Food Code 2022 §2-102.12 adoption and NYC's food protection certificate; if adopted with personal-liability teeth plus mandatory HACCP plans for sous-vide/ROP (already required by variance in many states), the signer role hardens
Continued growth of explicitly human-authored dining as a marketed category — chef's-name-on-the-door concepts, Michelin/James Beard credit attaching to a named individual, and 'no AI-generated menu' disclosure norms if guides or POS platforms start labeling AI-designed menus
Labor and safety enforcement making the chef the accountable party for line-level calls — e.g. wage-and-hour joint-liability rulings, or a health-department suspension record that follows the named manager rather than only the operator
The limit. Already 68 and near-max on embodiment (19) and task_resistance (16); realistic headroom is almost entirely in liability_shield, and even a full CFPM personal-liability regime is a weak moat compared to a professional license, since the certificate is a short exam, not a restricted-entry credential. Displacement pressure here is more likely to arrive as fewer chef slots per venue (centralized commissary production, AI-run back office reducing sous/head-cook headcount) than as replacement of the role itself — a risk the register's dimensions do not capture.
| New York-Newark-Jersey City, NY-NJ | 20,010 | $71,780 +15% |
| Los Angeles-Long Beach-Anaheim, CA | 11,430 | $69,990 +12% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 8,210 | $57,940 -7% |
| Chicago-Naperville-Elgin, IL-IN | 6,840 | $60,770 -3% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 5,700 | $65,680 +5% |
| San Francisco-Oakland-Fremont, CA | 5,340 | $68,970 +10% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 4,680 | $74,900 +20% |
| Boston-Cambridge-Newton, MA-NH | 4,430 | $72,470 +16% |
| Terre Haute, IN | 50 | $85,920 +38% |
| Kahului-Wailuku, HI | 250 | $84,990 +36% |
| Albany-Schenectady-Troy, NY | 470 | $84,430 +35% |
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 68. 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.