← Risk register SOC 45-2099 · reviewed 2026-08-11

Agricultural Workers, All Other

3,620 US workers · median $39,850/yr · Agriculture

EXPOSED

This is a catch-all bucket — irrigation setup, hand-weeding, sorting and grading produce, animal handling, equipment tending, seasonal field labor — and almost none of it is text or screen work, so language models barely touch it. The real exposure is mechanical: autonomous tractors, GPS-guided sprayers, robotic weeders and optical sorters are commercially deployed right now, and they target exactly the repetitive field and packhouse tasks that define the modal worker here. There is no license, no signature requirement, and no customer paying for a relationship, so nothing slows substitution except capital cost and crop geometry.

10-year outlook: Headcount in the repetitive field and packhouse tasks keeps shrinking as ag robotics scales, while the workers who run and fix the machines, handle livestock, and lead crews stay in demand and get paid better.

US employment, 2019–2025-44.6%
6,5403,620 workers

Most of this decline happened after 2021 — it is not the pandemic dip.

Median pay $29,590 → $39,850 +7.7% in real terms (nominal +34.7%, less ~25% US inflation over the period)

The job count is not the verdict

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

+2.3%

Percentage only. The projection counts a different population from the 3,620 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.

Growing, and only partly exposed

The BLS expects +2.3% more of these jobs by 2034, and at 46/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.

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.

~1,500 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 24 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

RiderScoutCanterChokerCutterDoggerDriverFeederGopherPullerSniperBrusherCatcherChainerChopperClimberLaborerScalperSkidderSkinnerSlipperSnubberSpudderStumper

This is a catch-all code, not a single job

The BLS uses Agricultural Workers, All Other for work that doesn't fit any named occupation, so it covers roles that have little in common with each other. Two consequences worth knowing before you read anything below:

If a more specific occupation on the register describes what you actually do, that page is the one to trust.

Score — 46/100 resistance

Holding it up: embodiment (18/20). Weakest point: liability shield (2/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 15 + 18 + 2 + 4 + 7 = 46. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 15/20

Tasks largely resist digitisation Setting irrigation lines across uneven ground, hand-pulling weeds between close-spaced rows, catching and restraining animals, and clearing jammed equipment are all judged by touch and eye in the moment — a 15 rather than 18 because the packhouse sorting and grading portion of this bucket is already being done by optical graders on commercial lines.

Embodiment 18/20

Hands-on in uncontrolled environments The work is outdoors in mud, heat, dust and livestock pens, on terrain no rail or gantry can be built over, with tasks that require bending into a crop canopy and gripping wet or living material — the 18 rather than 20 reflects the share of this SOC working inside sheds, greenhouses and packing rooms where conditions are at least partly controlled.

Liability shield 2/20

No licence, no signature requirement No state licence, no certification exam, and no signature on any document — the 2 rather than 0 acknowledges pesticide-handler cards and worker protection standard training that some of these jobs require before a worker can be sent into a treated field.

Trust premium 4/20

Anonymous artifact production Produce leaves the field anonymous and graded by specification, not by who picked it; the 4 reflects that the person who returns each season and knows one farm's fields, gates and quirks is genuinely harder to replace than a first-day hire, but the buyer never learns their name.

Judgment & accountability 7/20

Meaningful discretion Calls like when a plant is ready to cut, whether an animal is off-feed, or when a hose fitting is about to fail are real and made unsupervised — but they sit at 7 because the decisions are within a day's crop or one animal, and the crew leader or grower owns anything with money or safety attached.

Confidence: medium · reviewed 2026-08-11 · how scoring works · 1 deployment report on file

What this job involves — and which parts are yours

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.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: embodiment, physical-presence

How to future-proof this job

All 35 skills ranked by how many jobs they open →

What would move this back up — beyond any one person

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 61/100, still EXPOSED.

5 specific changes that would raise this score
  • already happening embodiment +2

    Displacement of machine-friendly crops (row vegetables, tree nuts, wheat) leaves the remaining hand-work concentrated in geometries robots still fail at: steep-slope vineyards, greenhouse trellis pruning, mixed-species organic beds, live animal handling in unpredictable pens. Watch USDA specialty-crop labor surveys and grower reports of robotic weeder failure rates in high-density diversified plantings.

  • already happening trust premium +2

    Third-party certification schemes that require documented human handwork or human animal handling — Certified Humane / GAP Step 4+ pasture handling, Demeter Biodynamic, some organic hand-weeding attestations — attach a price premium to labor practice, not just crop. This is a premium paid to the farm, though, not to the worker, so the pass-through is weak.

  • plausible liability shield +5

    A pesticide-applicator or biosecurity rule requiring a certified individual physically present and personally accountable for each autonomous application or animal-movement event — analogous to EPA Worker Protection Standard handler certification, or USDA APHIS foreign-animal-disease traceability requirements after an HPAI or FMD incident. Also watch state autonomous-tractor rules (California Cal/OSHA has long barred driverless operation of ag equipment without an attendant; Title 8 §3441(b)) which effectively require a named human in the field.

  • plausible task resistance +3

    Task-mix shift: the occupation genuinely has two tiers. If optical sorters and autonomous sprayers take the repetitive tier, what remains is machine tending, fault diagnosis, calibration, and exception handling — plus organic-certification handwork that must not be chemically or mechanically treated. Watch job postings that merge 'ag worker' with 'field robotics technician' at operations like Driscoll's or Bowery-style controlled-ag firms.

  • plausible judgment accountability +3

    If irrigation-allocation and water-curtailment regimes (SGMA groundwater allocations in California, Colorado River cuts) push per-plot water decisions onto whoever is physically present, the irrigation-setup role starts owning consequential, auditable calls under ambiguity rather than executing a schedule.

The limit. Even with every lever, this stays mid-band. It is a residual bucket defined by what did not fit elsewhere, and the levers that work best (licensing, judgment) attach to individuals who then get reclassified out of 45-2099 into supervisor or technician codes — so the code itself can shrink while the surviving work looks more resistant. Trust premium has no real route to the worker: buyers pay farms, not field hands, and there is no relationship a customer is purchasing.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 15 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Most of these jobs

Bakersfield-Delano, CA 150 $34,320 -14%
Fresno, CA 110 $49,680 +25%
Baltimore-Columbia-Towson, MD 90 $36,680 -8%
Los Angeles-Long Beach-Anaheim, CA 90 $56,840 +43%
San Juan-Bayamon-Caguas, PR 90 $25,720 -35%
Knoxville, TN 60 $33,680 -15%
Nashville-Davidson--Murfreesboro--Franklin, TN 60 $29,090 -27%
Riverside-San Bernardino-Ontario, CA 60 $59,670 +50%

Best paid

Sacramento-Roseville-Folsom, CA 50 $67,900 +70%
Riverside-San Bernardino-Ontario, CA 60 $59,670 +50%
Los Angeles-Long Beach-Anaheim, CA 90 $56,840 +43%

Percentages are against this occupation's national median of $39,850. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this

The score above is about what the work exposes. This is reporting about real deployments in this occupation — the difference between "could be automated" and "somebody automated it."

Van Noord Growers

1 of 1 reported case, with sources

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.

File a field report

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