← Risk register SOC 45-1011 · reviewed 2026-08-11

First-Line Supervisors of Farming, Fishing, and Forestry Workers

27,960 US workers · median $59,320/yr · Agriculture

EXPOSED

This is a boots-in-the-field job: walking crop rows and orchards, judging when a block is ready to pick, assigning crews to tasks, fixing what breaks, and enforcing safety on moving equipment — none of which a language model can do. The automatable slice is the paperwork layer: crew scheduling, payroll and piece-rate tallies, harvest yield logs, H-2A and OSHA compliance records, and pesticide application reports, all of which farm management software plus AI is absorbing quickly. Licensure is thin (pesticide applicator certification in some states), so the moat is physical presence and on-the-spot judgment, not regulation.

10-year outlook: The role persists because someone has to be standing in the field, but the administrative half thins out and each supervisor covers more acres with software doing the scheduling and record-keeping.

US employment, 2019–2025+23.9%
22,56027,960 workers

Headcount grew steadily across the period.

Median pay $48,280 → $59,320 -1.7% in real terms (nominal +22.9%, 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

+2.5%

Percentage only. The projection counts a different population from the 27,960 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 +2.5% more of these jobs by 2034, and at 60/100 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.

~8,500 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.

Saw BossBarn BossBoom BossCamp BossFarm BossCrew ChiefGamekeeperWoods BossBoom MasterCorral BossSow ManagerYarder BossBarn ManagerCrew ForemanFeed ManagerCattle ManagerKennel ManagerArea SupervisorCrew SupervisorFarm SupervisorHarvest ManagerLogistics AgentOrchard ManagerShelter Monitor

Score — 60/100 resistance

Holding it up: embodiment (18/20). Weakest point: liability shield (5/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 14 + 18 + 5 + 10 + 13 = 60. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 14/20

Tasks largely resist digitisation Deciding that this block of strawberries is at picking maturity while the next row needs two more days, then redeploying a 30-person crew mid-morning when a picker goes down or a conveyor jams, is judgment made by walking and touching the crop — it sits at 14 rather than 18 because the recordkeeping half of the day (piece-rate tallies, yield logs, H-2A hour reports) is already being pulled into farm-management platforms.

Embodiment 18/20

Hands-on in uncontrolled environments You are outdoors in heat, dust, mud and cold for most of the shift, climbing on tractors and harvesters, checking irrigation lines and pruning cuts, standing on a fishing deck or a felling site where footing and weather change hourly — the 18 reflects genuinely uncontrolled terrain, short of 20 only because part of the week goes to an office or truck cab for scheduling and compliance paperwork.

Liability shield 5/20

Certification preferred, not legally required There is no supervisor licence in agriculture: a state pesticide applicator certification (and sometimes a commercial driver's licence or first-aid card) is the whole credential stack, and when a worker is injured the citation lands on the employer under the OSHA general duty clause and the Worker Protection Standard, not on you personally — hence 5 rather than 0, since that applicator card is a real legal requirement someone must hold.

Trust premium 10/20

Some relationship component Crews return year after year for the supervisor they trust to pay accurately, communicate in their language, and not push them through a heat-illness day, and that loyalty is what fills a harvest window — but the buyer of the crop deals with the owner or packer, not you, which caps this at 10 instead of the mid-teens.

Judgment & accountability 13/20

Meaningful discretion Calling a work stoppage before a thunderstorm, deciding whether a bruised load still meets the buyer's grade, or pulling a crew off a field within a pesticide re-entry interval are consequential calls made without waiting for a phone call up the chain; it lands at 13 rather than higher because harvest windows, contract grades, and labor budgets are set above you and constrain the range of choices.

Confidence: medium · reviewed 2026-08-11 · how scoring works

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, judgment

How to future-proof this job

Where to go deeper on what this job runs on: Coursera — critical thinking and logic, audit free free to audit · Coursera — project coordination and cross-team delivery free to audit · Toastmasters — public speaking practice at local clubs worldwide low · edX — performance measurement and evaluation free to audit · Khan Academy — reading and vocabulary, all levels, free free · Coursera — work planning and personal productivity free to audit

All 35 skills ranked by how many jobs they open →

Where this experience transfers — nothing clears the bar

No occupation passed every test: close enough to first-line supervisors of farming, fishing, and forestry workers 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:

Farmers, Ranchers, and Other Agricultural Managers EXPOSED 62/100 (+2) · 89% overlap
Industrial Production Managers EXPOSED 52/100 (-8) · 74% overlap
First-Line Supervisors of Landscaping, Lawn Service, and Groundskeeping Workers EXPOSED 62/100 (+2) · 74% overlap

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.

What would move this occupation up is the other direction, and on this page it's the more useful one.

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 77/100 — SAFE.

5 specific changes that would raise this score
  • already happening liability shield +5

    State pesticide-applicator rules tightening so that a certified applicator-in-charge must be physically present and personally sign each application record, including for drone/UAS and autonomous sprayer applications — EPA's Part 171 certification-of-applicators rule and FAA Part 137 exemptions for agricultural UAS already push toward a named certified human responsible for each pass. If states add a supervisor-signature requirement for autonomous equipment passes, this rises sharply.

  • already happening judgment accountability +4

    Task-mix shift: as scheduling, payroll tallies, yield logs and compliance filing get absorbed by farm management software, what remains is the irreducible judgment tier — harvest-timing calls on a block worth six figures, heat-illness stand-down decisions under Cal/OSHA §3395 and the proposed federal heat rule, and crew reassignment when weather turns. Fewer clerical hours per consequential call raises this dimension without any legal change.

  • plausible liability shield +3

    H-2A compliance enforcement (DOL Wage and Hour, the 2024 Farmworker Protection Rule and its litigation) attaching individual supervisor liability for housing, transport, and wage-record accuracy, so a named on-site supervisor must attest to daily hours and piece-rate records rather than software generating them unattested.

  • plausible judgment accountability +3

    OSHA heat-injury and illness prevention standard (proposed 2024) finalizing with named-supervisor duties for acclimatization, rest-break enforcement, and emergency response — making the stand-down call an owned, documented, auditable decision rather than informal practice.

  • plausible task resistance +2

    Autonomous orchard/row-crop equipment scaling to the point the supervisor's day becomes exception-handling for machine failure in mud, canopy, and slope — diagnosing why a robotic harvester is bruising fruit, which is field-diagnostic work no remote system does. Raises task resistance only if fleets grow while remote-operations centers stay thin.

The limit. Trust premium has no realistic route: the buyer is a farm owner or packing shed buying labor coordination at commodity margins, not a client who would pay extra for a human crew boss. Licensure will stay thin outside pesticide handling — no state is likely to license farm supervision generally. Realistic ceiling is roughly the low 70s, and it rests on embodiment plus pesticide/heat-safety signature duties, not on any market preference for human supervisors.

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 118 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 1,430 $46,910 -21%
Fresno, CA 1,340 $48,850 -18%
Salinas, CA 1,240 $62,030 +5%
Visalia, CA 990 $47,800 -19%
Santa Maria-Santa Barbara, CA 710 $48,520 -18%
Los Angeles-Long Beach-Anaheim, CA 520 $73,480 +24%
New York-Newark-Jersey City, NY-NJ 380 $70,120 +18%
Riverside-San Bernardino-Ontario, CA 370 $56,720 -4%

Best paid

Minneapolis-St. Paul-Bloomington, MN-WI 110 $92,560 +56%
Indianapolis-Carmel-Greenwood, IN 50 $91,820 +55%
Coeur d'Alene, ID 40 $82,040 +38%

Percentages are against this occupation's national median of $59,320. 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 — nobody, on the record

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 60. 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.

Read that as a gap in the reporting we can see, not proof of absence — the dispatch runs on English-language feeds and misses plenty. If you know of a case, tell us, or add a field report from inside the job.

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

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

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