EXPOSED
The modal worker here owns or manages an operation: walking fields and pens, diagnosing sick livestock, repairing equipment, hiring and directing crews, and making planting, culling, and marketing calls with weather and commodity prices against them. AI and precision-ag software are already eating the desk half — yield modeling, input optimization, crop insurance paperwork, spray scheduling, market analysis, recordkeeping — and autonomous tractors are real for row-crop tillage and harvest on flat ground. What resists is the unstructured physical work, the animal handling, and bearing the financial consequences of a bad season, which is why this scores mid-band rather than safe: displacement here looks like consolidation and fewer operators per acre, not robots replacing farmers.
Headcount grew steadily across the period.
Median pay $71,160 → $89,900 +1.1% 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
-1.3%
Percentage only. The projection counts a different population from the 6,500 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Shrinking, but not obviously because of AI
The BLS projects -1.3% by 2034, but at 62/100 this work is only moderately exposed — not the profile of a job current AI can simply do. Occupations shrink for many reasons, and the score does not point at automation as this one's cause.
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.
~85,500 openings a year on average, including replacing people who leave.
FarmerGrowerBeekeeperFarm ManagerDairy GrazierDairy ManagerField ManagerPlant ManagerRanch ManagerRange ManagerOrganic FarmerFeedlot ManagerNursery ManagerOrchard ManagerAgronomy ManagerHatchery ManagerLocation ManagerSow Farm ManagerShellfish ManagerActivation ManagerAgriculture FarmerBeef Farm OperatorDairy Farm ManagerFarm Field Manager
Holding it up: embodiment . Weakest point: liability shield .
Tasks largely resist digitisation Pulling a breech calf at 2am, diagnosing why a specific pivot section stopped turning, and deciding a field is dry enough to enter by how the soil feels underfoot are tasks no vendor sells software for — 15 rather than 18 because the paperwork, agronomic modeling, and marketing half of the job is already being done by FBN, Climate FieldView, and crop insurance platforms.
Hands-on in uncontrolled environments The workday is spent in pens, on ladders, under equipment, and in fields where the mud, heat, livestock temperament, and weather are all uncontrolled variables — an 18 rather than 20 only because a real share of hours goes to the office desk doing loan applications, payroll, and grain contracts.
Certification preferred, not legally required No licence stands between you and the work: anyone can buy land and start farming, and while restricted-use pesticide applicator certification and CDL matter for specific duties, they gate a task rather than the occupation, which is what puts this at 5 rather than 2.
Exists to be accountable for ambiguous calls You decide when to plant against a forecast that may be wrong, whether to cull a marginal cow, when to price the crop, and how much of next year's inputs to prepay — nobody reviews these, and a bad call shows up as a lien on the farm rather than a performance review.
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 (15/20 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 (8/20) is whether buyers specifically pay for a person. Judgment and accountability (16/20) 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 29 of this occupation's 62 points (47%).
Embodiment (18/20) 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.
No occupation passed every test: close enough to farmers, ranchers, and other agricultural managers on skills and subject matter, at least 10 points more resistant, no big jump in training, no new licence, no pay cut, and not shrinking on its own. That happens for 223 of the 654 occupations here that aren't SAFE, and it is worth stating plainly rather than leaving the section off.
The usual reason is that exposure travels with the skill profile. The jobs most similar to yours tend to be exposed for the same reasons yours is, so the near neighbours don't clear the gap — and the ones that do are a different kind of work, not a transfer of what you already know. Read that as a limit of this method, not a verdict that you're stuck: it only compares whole occupations, and it cannot see specialisation, industry, or anything you'd bring that isn't in a federal skill survey.
Here is that claim on your own job rather than in the abstract. These are the three occupations closest to this one by skill and subject matter — the places the work would most naturally transfer — with what the register scores them:
That is the whole problem in three lines. The nearest work is not meaningfully safer, so there is no move here that trades a similar skill set for a better verdict. This is not us running out of ideas — it is what the neighbourhood looks like.
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 75/100 — SAFE.
Pesticide/restricted-use application law already requires a certified applicator of record; EPA's 2024 Certification of Pesticide Applicators rule tightened supervision requirements. If state ag departments extend the named-human-of-record model to autonomous sprayers and drone application (FAA Part 137 exemptions already name a responsible remote pilot-in-command per operation), the licensed operator becomes legally unremovable per machine, not per farm. Organic certification (NOP) and FSMA Produce Safety Rule similarly designate a responsible individual who signs food-safety plans.
Direct-to-consumer and certified channels where buyers pay for a named human steward: Real Organic Project and Regenerative Organic Certified require on-farm human inspection and grower attestation; ag-tourism, CSA, and brand-story premiums pay specifically because an identifiable family operates the land. Growth in these channels raises the share of revenue that is explicitly human-attached, but they remain a small slice of acreage.
State veterinary practice acts plus the veterinarian-client-patient relationship requirement for antibiotic use (FDA GFI #263) already put prescribing behind a licensed human; if drug-residue and animal-welfare audit regimes (e.g., FARM program, packer welfare audits) require a named manager to sign treatment and euthanasia records, that signature attaches personal exposure to the manager role.
Genuine two-tier structure: if autonomous tillage/harvest and AI agronomy absorb the routine acreage tasks and paperwork, the residual job concentrates on ambiguity — disease outbreak triage, drought-year replant decisions, marketing under basis volatility, labor management under H-2A audit. Watch for whether consolidated operations retain managers whose day is nearly all exception-handling.
Already near ceiling: owner-operators bear the loss personally. A further increase would require lenders or crop insurers to formally designate and document a decision-maker of record — e.g., Farm Credit or FCIC loss-adjustment rules refusing indemnity where planting and input decisions were made by an unsupervised automated system.
The limit. Embodiment and judgment are already near maximum, so almost all headroom is in liability and trust — and both are capped by the fact that displacement here is consolidation. A licensed-applicator or food-safety signature protects the role, not the headcount: one manager can sign for many more acres, so scores can rise while the 6,500-worker count falls.
| Fresno, CA | 200 | $104,600 +16% |
| Napa, CA | 150 | $158,660 +76% |
| Bakersfield-Delano, CA | 130 | $123,340 +37% |
| Visalia, CA | 130 | $98,040 +9% |
| Dallas-Fort Worth-Arlington, TX | 100 | $97,880 +9% |
| Houston-Pasadena-The Woodlands, TX | 100 | $92,800 +3% |
| Stockton-Lodi, CA | 100 | $101,990 +13% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 90 | $86,180 -4% |
| Napa, CA | 150 | $158,660 +76% |
| Santa Maria-Santa Barbara, CA | 70 | $142,560 +59% |
| Yakima, WA | 40 | $126,170 +40% |
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 62. 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.