EXPOSED
Planting seedlings on uneven slopes, clearing brush with chainsaws and hand tools, building and repairing trails, and spraying herbicide in dense terrain are jobs no language model touches and no current robot handles at cost. What AI does erode is the thin desk layer — plot data entry, stand inventory summaries, spraying and burn-day recordkeeping, and the mapping/prioritization work now increasingly done from drone and satellite imagery. Exposure here comes less from AI than from the occupation's low licensure, low wage, and seasonal-contract structure, which leaves no bargaining shield if crew sizes shrink.
Part 2020 shock, part continued decline in the years since.
Median pay $31,770 → $43,680 +10.0% 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
-4.7%
Percentage only. The projection counts a different population from the 6,050 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 -4.7% by 2034, but at 50/100 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.
~2,000 openings a year on average, including replacing people who leave.
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Holding it up: embodiment . Weakest point: liability shield .
Tasks largely resist digitisation Hand-planting bare-root seedlings at correct depth and spacing on 30-degree slopes, felling and limbing with a chainsaw, and swinging a Pulaski to cut trail tread are tasks no machine performs at crew-labor cost, which is why this sits at 16 rather than 20 — the plot measurements, tally sheets, and stand summaries that once justified a crew member's afternoon are already being pulled from drone and LiDAR passes.
Hands-on in uncontrolled environments You work on unimproved ground in whatever weather the season delivers, carrying a planting bag, backpack sprayer, or saw through slash and blowdown, and no part of the day happens indoors — the only thing keeping this off 20 is that some units are pre-marked plantation rows rather than pure wildland.
No licence, no signature requirement Nothing you do requires a state licence; the herbicide applications are made under a supervisor's or contractor's certification, the burn plan is signed by a qualified burn boss, and your chainsaw and first-aid cards are employer-required training rather than a credential the law makes personally answerable — hence 4, not zero, since those cards do gate who gets on the crew.
Executes defined procedures on defined inputs Planting prescriptions, spacing, tank mixes, and unit boundaries arrive already specified by a forester or contract spec, so your discretion is confined to reading terrain, picking microsites, and calling a hazard tree or a shutdown for wind — real calls, but bounded ones, which is why 6 rather than 10.
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 (4/20) is whether the law requires a licensed human to sign. Trust premium (5/20) is whether buyers specifically pay for a person. Judgment and accountability (6/20) 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 15 of this occupation's 50 points (30%).
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.
No occupation passed every test: close enough to forest and conservation 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:
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 64/100, still EXPOSED.
Crew work concentrating in roles where a named, personally certified individual must sign: state-certified commercial pesticide applicator credentials under FIFRA/40 CFR 171 (already required for herbicide application, but often held by one supervisor per crew — a state rule requiring certified-applicator status per person handling restricted-use product, not per crew, would raise this), plus state Certified Prescribed Burn Manager status (Florida F.S. 590.125, North Carolina, Georgia, Texas) where the certified burner signs the burn plan and carries the gross-negligence liability standard.
Task-mix shift within a genuinely two-tier job: if drone/satellite pipelines absorb the mapping, plot summary and burn-day recordkeeping tier, the residual role is the sawyer/burner/applicator tier that no current machine performs at cost on slope and in dense fuels. This raises the score of the job that remains without raising the number of jobs.
Growth of the prescribed-fire and fuels-reduction share of the work, where the burn boss / crew lead owns documented go/no-go calls against a written prescription (weather, fuel moisture, smoke-sensitive receptors) and the RX-level NWCG qualification travels with the person. Escaped-fire litigation and post-2020 state smoke-management rules make that call individually attributable in a way that seedling planting is not.
Carbon and biodiversity credit registries (Verra VM0047, ACR, Climate Action Reserve) requiring physical ground-plot measurement by a qualified field crew rather than remote-sensing-only estimation, after buyer-side backlash over satellite-derived overcrediting. That converts field measurement into a paid-for human verification step rather than a cost to be optimized away.
The limit. Even with all of these, headcount is set by agency and contract budgets, not by AI capability — a high resistance score here can coexist with fewer crew slots. The certification routes also split the occupation: they lift certified burners and applicators well above the planting-and-brush tier, which has no visible route to a liability shield or trust premium at all.
| Los Angeles-Long Beach-Anaheim, CA | 370 | $43,680 +0% |
| Sacramento-Roseville-Folsom, CA | 330 | $43,680 +0% |
| Seattle-Tacoma-Bellevue, WA | 220 | $45,510 +4% |
| Oxnard-Thousand Oaks-Ventura, CA | 180 | $43,680 +0% |
| Sioux Falls, SD-MN | 150 | $37,470 -14% |
| San Diego-Chula Vista-Carlsbad, CA | 140 | $43,680 +0% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 110 | $39,490 -10% |
| Riverside-San Bernardino-Ontario, CA | 110 | $43,680 +0% |
| Milwaukee-Waukesha, WI | 30 | $52,850 +21% |
| Pittsburgh, PA | 30 | $51,330 +18% |
| Boston-Cambridge-Newton, MA-NH | 80 | $51,300 +17% |
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 50. 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.