Will AI replace Forest and Conservation Workers?

Not as a job, but it is already doing parts of the work. Across the 17 official task statements scored for Forest and Conservation Workers (United States, SOC 45-4011), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 4 out of 100 (range 3–9, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.

Which tasks in “Forest and Conservation Workers” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Maintain tallies of trees examined and counted during tree marking or measuring efforts” (29/100, low); “Explain or enforce regulations regarding camping, vehicle use, fires, use of buildings, or sanitation” (18/100, minimal); “Confer with other workers to discuss issues, such as safety, cutting heights, or work needs” (13/100, minimal). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.

Which tasks in “Forest and Conservation Workers” stay human?

About 100% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Sort tree seedlings, discarding substandard seedlings, according to standard charts or verbal instructions” (0/100, minimal); “Maintain campsites or recreational areas, replenishing firewood or other supplies and cleaning kitchens or restrooms” (0/100, minimal); “Operate skidders, bulldozers, or other prime movers to pull a variety of scarification or site preparation equipment over areas to be regenerated” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.

What should someone working in “Forest and Conservation Workers” do about AI?

Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 100% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.

How is the AI exposure score for Forest and Conservation Workers calculated?

Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 17 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

US dataswitch to UK

Forest and Conservation Workers

checking equipment to ensure that it is operating properly, explaining or enforcing regulations regarding camping and operating skidders. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: checking equipment to ensure that it is operating properly is work software can't reach.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 0%
changing shape: 0%
staying human: 100%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 4 out of 100 (3–9 allowing for uncertainty): minimal exposure, across 17 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.

How we know this

What is measured: Every published task statement for forest and conservation workers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

What shifts is the routine end of the work: the overhead at the edges, not the middle you trained for.

Your week, as this page understands it

Under supervision, perform manual labor necessary to develop, maintain, or protect areas such as forests, forested areas, woodlands, wetlands, and rangelands through such activities as raising and transporting seedlings; combating insects, pests, and diseases harmful to plant life; and building structures to control water, erosion, and leaching of soil. Includes forester aides, seedling pullers, tree planters, and gatherers of nontimber forestry products such as pine straw. The job title says “forest” or “conservation workers”: officially one job, two names. The real job is the part underneath: checking equipment to ensure that it is operating properly. That is the thing someone has to be right about.

The exposed part of this job is specific, and we won’t pretend it is coming back. But forest and conservation workers is not one task. It is 17 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is checking equipment to ensure that it is operating properly, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 0%
changing shape: 0%
staying human: 100%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

Your job, task by task

These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.

Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Shifting to AI

0 tasks

Tasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.

Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.

Changing shape

0 tasks

Tasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.

Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.

Staying human

17 tasks

Tasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.

Checking equipment to ensure that it is operating properly
This work happens in the physical world: equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Check equipment to ensure that it is operating properly.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Checking that equipment runs properly means putting hands on it.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Fighting forest fires or performing prescribed burning tasks under the direction of fire suppression officers or forestry technicians
This work happens in the physical world: forest fires, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Fight forest fires or perform prescribed burning tasks under the direction of fire suppression officers or forestry technicians.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Fighting fires or running a prescribed burn is physically demanding outdoor work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Performing fire protection or suppression duties
This work happens in the physical world: fire protection, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Perform fire protection or suppression duties, such as constructing fire breaks or disposing of brush.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Cutting fire breaks and clearing brush is heavy outdoor work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Conferring with other workers to discuss issues
The value here is that a specific person handles other workers and stands behind it. That is earned, not computed.
importance 3 · Core
Source: “Confer with other workers to discuss issues, such as safety, cutting heights, or work needs.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Crew discussions about safety and cutting heights happen between people on the job, though notes can be prepared beforehand.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 1/4.
Explaining or enforcing regulations regarding camping
This work happens in the physical world: regulations, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Explain or enforce regulations regarding camping, vehicle use, fires, use of buildings, or sanitation.” (O*NET task statement)
How this row was scored
Exposure score: 18 out of 100 (11–25 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Rules about fires, camping and vehicles are documented and easy to explain, but enforcing them means being there with visitors.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Maintaining tallies of trees examined and counted during tree marking or measuring efforts
This work happens in the physical world: tallies of trees, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Maintain tallies of trees examined and counted during tree marking or measuring efforts.” (O*NET task statement)
How this row was scored
Exposure score: 29 out of 100 (22–36 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Keeping a running tally of trees counted or marked is simple record work that software and handheld apps handle.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Thinning or spacing trees, using power thinning saws
This work happens in the physical world: trees, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Thin or space trees, using power thinning saws.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Thinning trees with a power saw is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Erecting signs or fences, using posthole diggers, shovels or other hand tools
This work happens in the physical world: signs, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Erect signs or fences, using posthole diggers, shovels, or other hand tools.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Putting up signs and fences is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Identifying diseased or undesirable trees and removing them
This work happens in the physical world: diseased, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Identify diseased or undesirable trees and remove them, using power saws or hand saws.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Spotting and felling diseased trees is done with a saw in the woods.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Selecting or cutting trees according to markings or sizes
This work happens in the physical world: trees, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Select or cut trees according to markings or sizes, types, or grades.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Selecting and cutting trees to marking or grade is physical work in the forest.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.

Show the other 7 tasks

Spraying or injecting vegetation with insecticides to kill insects or to protect against disease or with herbicides to reduce competing vegetation
staying human
This work happens in the physical world: vegetation, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Spray or inject vegetation with insecticides to kill insects or to protect against disease or with herbicides to reduce competing vegetation.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Spraying or injecting vegetation with chemicals is physical field work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Pruning or shearing tree tops or limbs to control growth
staying human
This work happens in the physical world: tree tops, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Prune or shear tree tops or limbs to control growth, increase density, or improve shape.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Pruning and shearing tree limbs is hands-on work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Selecting tree seedlings, prepare the ground or plant the trees in reforestation areas, using manual planting tools
staying human
This work happens in the physical world: tree seedlings, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Select tree seedlings, prepare the ground, or plant the trees in reforestation areas, using manual planting tools.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Preparing ground and planting seedlings by hand is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Providing assistance to forest survey crews by clearing site-lines
staying human
This work happens in the physical world: assistance, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Provide assistance to forest survey crews by clearing site-lines, holding measuring tools, or setting stakes.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Clearing sight lines, holding tools and setting stakes for survey crews is physical field work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Operating skidders, bulldozers or other prime movers to pull a variety of scarification or site preparation equipment over areas
staying human
This work happens in the physical world: skidders, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Operate skidders, bulldozers, or other prime movers to pull a variety of scarification or site preparation equipment over areas to be regenerated.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Operating skidders and bulldozers is machine work done from the seat.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Maintaining campsites or recreational areas
staying human
This work happens in the physical world: campsites, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Maintain campsites or recreational areas, replenishing firewood or other supplies and cleaning kitchens or restrooms.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Maintaining campsites, firewood and restrooms is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Sorting tree seedlings, discarding substandard seedlings, according to standard charts or verbal instructions
staying human
This work happens in the physical world: tree seedlings, discarding substandard seedlings, in a real place. Software cannot follow it there.
importance 2 · Supplemental
Source: “Sort tree seedlings, discarding substandard seedlings, according to standard charts or verbal instructions.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Sorting seedlings and discarding poor ones means handling each plant.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.

What this job pays, and how many people do it

Median pay: $43,680a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
People doing this job: 6,050in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)

What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.

Why this is shifting

The reason is boringly specific. Almost none of this job is reading one thing and writing another (the shape today's tools are built for), because the work turns on equipment, which happens with people and things rather than on a screen. The rows above are the evidence rather than the reassurance: checking equipment to ensure that it is operating properly and fighting forest fires or performing prescribed burning tasks under the direction of fire suppression officers or forestry technicians. The parts that are changing are the paperwork and the tools around the job, not the middle of it, which is why this page talks about your tasks changing, not your job ending.

Your move

Over a pint: what I’d tell you if you were my friend

Start with what does not change: checking equipment to ensure that it is operating properly is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 0% of this job's task weight sits in rows the software is already learning, 0% in rows that change shape rather than disappear, and 100% in rows it is nowhere near. That is the position, measured across 17 scored tasks. It is not a forecast about you.

So the thing worth your attention is not the job going away. It is the layer around it. The routine end of the work is the part turning into software, and being the person who understands that layer is worth money.

This week: one thing

Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to the routine work, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.

What you end up holding: a straight answer about what is actually being rolled out, and when
How long it takes: ten minutes

If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether forest fires are in scope or not. Nothing to log into, no license needed.

Over the next 90 days

Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near checking equipment to ensure that it is operating properly. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.

Over the next 12 months

On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.

The roads out of here, and why I am not sending you down them

I looked at the obvious moves out of this job, and here is what I found.

I checked the 12 nearest US occupations to forest and conservation workers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was forest and conservation technicians: only about 4% of its durable work is work you already do. And on the numbers you do not need one. This job scores 4/100 here, with only 0% of the task list in the top band, and “check equipment to ensure that it is operating properly” is not work that hands over cleanly. None of them beats deepening what you already have.

How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.

3 moves I checked and rejected

These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.

Forest and Conservation Technicians
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already thin or space trees, using power thinning saws, and their equivalent is to thin and space trees and control weeds and undergrowth, using manual tools and…. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Foresters
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already fight forest fires or perform prescribed burning tasks under the direction of fire…, and their equivalent is to direct, and participate in, forest fire suppression. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Occupational Health and Safety Technicians
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already perform fire protection or suppression duties, and their equivalent is to inspect fire suppression systems or portable fire systems to ensure proper working order. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →

What I’d stop worrying about

A friend tells you what not to spend fear on. This is that list.

The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 0% of its task weight, across 17 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like checking equipment to ensure that it is operating properly arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.

If you run a team doing this job

If you run a team doing this job, the conversation you owe them is the one on this page, and sooner than feels comfortable. Show them the ledger rather than a reassurance: the rows moving toward the software are the routine work, and the rows that are not are where you want your people visible. Ask each of them to do the this-week move and bring the list to your next one-to-one. It turns a rumour into a piece of work, and it tells you which parts of your team's week are actually at stake. And say the thing out loud that a team lead usually leaves unsaid: a shrinking team is your exposure too, so do the move yourself as well.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Forestry and related workers is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United Kingdom page →partial match

In UK official statistics this job is counted as Forestry and related workers. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.

Your route through this

Where to go next, and what it costs

Free, and complete

The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.

Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

Why there is no community here

Collab365, who build this site, run paid Spaces for a small number of subjects, and none of them is built for this job. We are not going to point you at the nearest one and call it a fit.

So the free services listed on this page are the whole answer, and it is the same answer we would give a friend.

Noted, and thank you. We’ll email you if a Space for forest / conservation workers launches. Nothing else.

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No Space for forest / conservation workers yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for forest / conservation workers existed, with researched problems, courses and people in the same boat, would you want in?

Your email

We use your email address for one thing: to tell you if a Space for forest / conservation workers launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.

Questions people ask about this job

Will AI replace Forest and Conservation Workers?: Not as a job, but it is already doing parts of the work. Across the 17 official task statements scored for Forest and Conservation Workers (United States, SOC 45-4011), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 4 out of 100 (range 3–9, band: minimal). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
Which tasks in “Forest and Conservation Workers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Maintain tallies of trees examined and counted during tree marking or measuring efforts” (29/100, low); “Explain or enforce regulations regarding camping, vehicle use, fires, use of buildings, or sanitation” (18/100, minimal); “Confer with other workers to discuss issues, such as safety, cutting heights, or work needs” (13/100, minimal). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “Forest and Conservation Workers” stay human?: About 100% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Sort tree seedlings, discarding substandard seedlings, according to standard charts or verbal instructions” (0/100, minimal); “Maintain campsites or recreational areas, replenishing firewood or other supplies and cleaning kitchens or restrooms” (0/100, minimal); “Operate skidders, bulldozers, or other prime movers to pull a variety of scarification or site preparation equipment over areas to be regenerated” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
What should someone working in “Forest and Conservation Workers” do about AI?: Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 100% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
How is the AI exposure score for Forest and Conservation Workers calculated?: Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 17 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

Where these numbers come from

Worth knowing about these figures

The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Task statements: onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
Task weights: onet-db (im-rt)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
Pay and employment: bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))

Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.

The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.

The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.

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Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.

Plain text

Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).

BibTeX

@misc{collab365futureproof2026q41,
  title        = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
  author       = {{Collab365}},
  year         = {2026},
  url          = {https://futureproof.collab365.com/data/2026-q4.1},
  note         = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.