US dataswitch to UK
Foresters
monitoring contract compliance and results of forestry activities to assure adherence to government regulations, performing inspections of forests or forest nurseries and mapping forest area soils and vegetation to estimate the amount of standing timber and future value and growth. If that's your week, this page is about your job.
The honest answer
AI changes the edges of this job, not the middle: monitoring contract compliance and results of forestry activities to assure adherence to government regulations is work software can't reach.
What shifts is studying different tree species' classification: the paper around the work, not the work.
Your week, as this page understands it
Manage public and private forested lands for economic, recreational, and conservation purposes. May inventory the type, amount, and location of standing timber, appraise the timber's worth, negotiate the purchase, and draw up contracts for procurement. May determine how to conserve wildlife habitats, creek beds, water quality, and soil stability, and how best to comply with environmental regulations. May devise plans for planting and growing new trees, monitor trees for healthy growth, and determine optimal harvesting schedules. The job title says “foresters”. The real job is the part underneath: monitoring contract compliance and results of forestry activities to assure adherence to government regulations. 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 foresters is not one task. It is 25 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is monitoring contract compliance and results of forestry activities to assure adherence to government regulations, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 6%
- changing shape
- 25%
- staying human
- 69%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 32 out of 100 (26–39 allowing for uncertainty): low exposure, across 25 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 foresters 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.
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.
- One row is marked low confidence, so treat it as a ballpark rather than a fine measurement.
- 2 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- 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
2 tasksTasks 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.
Studying different tree species' classification
This is reading one thing and writing another: different tree species' classification in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Study different tree species' classification, life history, light and soil requirements, adaptation to new environmental conditions and resistance to disease and insects.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (76–90 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Species biology and site requirements sit in abundant published literature software reads and summarizes well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Analyzing effect of forest conditions on tree growth rates and tree species prevalence and the yield
This is reading one thing and writing another: effect of forest conditions in, a record out. That is the shape today's tools are built for.
importance 3 · SupplementalSource: “Analyze effect of forest conditions on tree growth rates and tree species prevalence and the yield, duration, seed production, growth viability, and germination of different species.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Working out how forest conditions affect growth and yield is data analysis software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Changing shape
5 tasksTasks 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.
Establishing short- and long-term plans for management of forest lands and forest resources
The software now makes the first pass at short-, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Establish short- and long-term plans for management of forest lands and forest resources.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Long-term forest management plans are built from inventory data and models, which software drafts well.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Mapping forest area soils and vegetation to estimate the amount of standing timber and future value and growth
The software now makes the first pass at forest area soils, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Map forest area soils and vegetation to estimate the amount of standing timber and future value and growth.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Satellite and aerial data with mapping software already estimate timber volumes and growth well.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Planning and directing forest surveys and related studies and preparing reports and recommendations
The software now makes the first pass at forest surveys, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · CoreSource: “Plan and direct forest surveys and related studies and prepare reports and recommendations.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Designing surveys and writing up findings and recommendations is desk work software drafts well.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Determining methods of cutting and removing timber with minimum waste and environmental damage
The software now makes the first pass at methods, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Determine methods of cutting and removing timber with minimum waste and environmental damage.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Good harvesting methods are well documented, though the final call depends on the specific stand and terrain.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Staying human
18 tasksTasks 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.
Monitoring contract compliance and results of forestry activities to assure adherence to government regulations
This work happens in the physical world: contract compliance, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Monitor contract compliance and results of forestry activities to assure adherence to government regulations.” (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: Rules and contract terms are written down, but confirming what happened on the ground needs a visit.
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.
Planning and implementing projects for conservation of wildlife habitats and soil and water quality
This work happens in the physical world: projects, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Plan and implement projects for conservation of wildlife habitats and soil and water quality.” (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: Conservation plans can be drafted from data, but carrying the work out happens in the woods.
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.
Performing inspections of forests or forest nurseries
This work happens in the physical world: inspections of forests, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Perform inspections of forests or forest nurseries.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Inspecting a forest or nursery means walking it and seeing the trees.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Negotiating terms and conditions of agreements and contracts for forest harvesting
The value here is that a specific person handles terms and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Negotiate terms and conditions of agreements and contracts for forest harvesting, forest management and leasing of forest lands.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (14–28 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Software can prepare terms, but agreeing a harvesting deal depends on trust built with the other side.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Show the other 15 tasks
Developing techniques for measuring and identifying trees
changing shapeThe software now makes the first pass at techniques, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · CoreSource: “Develop techniques for measuring and identifying trees.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (31–55 allowing for uncertainty): partial exposure, low confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Tree measurement methods are well documented so software can propose approaches, but testing them happens in the field.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Providing advice and recommendations, as a consultant on forestry issues
staying humanThe value here is that a specific person handles advice and stands behind it. That is earned, not computed.
importance 3 · CoreSource: “Provide advice and recommendations, as a consultant on forestry issues, to private woodlot owners, firefighters, government agencies or to companies.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Forestry guidance is well documented, but landowners act on advice from someone they know and trust.
The five ratings: output a model can produce 2/4 · 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 3/4.
Developing new techniques for wood or residue
staying humanThe ratings behind this row put new techniques well outside what today's tools can do on their own.
importance 2 · SupplementalSource: “Develop new techniques for wood or residue use.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over.
The rating behind it: Inventing genuinely new uses for wood and residue needs experiment and testing, not just reading.
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 0/4 · how much data exists 3/4.
Monitoring forest-cleared lands to ensure that they are reclaimed to their most suitable end
staying humanThis work happens in the physical world: forest-cleared lands, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Monitor forest-cleared lands to ensure that they are reclaimed to their most suitable end use.” (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: Records can be checked on screen, but confirming that cleared land has recovered means going to look.
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.
Monitoring wildlife populations and assessing the impacts of forest operations on population and habitats
staying humanThis work happens in the physical world: wildlife populations, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Monitor wildlife populations and assess the impacts of forest operations on population and habitats.” (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: Population data can be analyzed on screen, but counting and observing wildlife means being in the forest.
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.
Planning and directing construction and maintenance of recreation facilities
staying humanThis work happens in the physical world: construction, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Plan and direct construction and maintenance of recreation facilities, fire towers, trails, roads and bridges, ensuring that they comply with guidelines and regulations set for forested public lands.” (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: Trails, bridges and towers can be planned on paper, but directing the building work happens on site.
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.
Conducting public educational programs on forest care and conservation
staying humanThis work happens in the physical world: public educational programs, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Conduct public educational programs on forest care and conservation.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low 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: Software can write the materials, but running a public education session means standing in front of an audience.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Subcontracting with loggers or pulpwood cutters for tree removal and to aid in road layout
staying humanThe value here is that a specific person handles loggers and stands behind it. That is earned, not computed.
importance 4 · SupplementalSource: “Subcontract with loggers or pulpwood cutters for tree removal and to aid in road layout.” (O*NET task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Contracts with loggers draft quickly, but agreeing terms and road layout involves the people and the site.
The five ratings: output a model can produce 2/4 · 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 2/4.
Planning and supervising forestry projects
staying humanThis work happens in the physical world: forestry projects, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Plan and supervise forestry projects, such as determining the type, number and placement of trees to be planted, managing tree nurseries, thinning forest and monitoring growth of new seedlings.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 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: Planting plans can be drafted on screen, but supervising nursery and thinning work happens outdoors.
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 1/4 · how much data exists 3/4.
Planning cutting programs and managing timber sales from harvested areas
staying humanThis work happens in the physical world: programs, in a real place. Software cannot follow it there.
importance 4 · CoreSource: “Plan cutting programs and manage timber sales from harvested areas, assisting companies to achieve production goals.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 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: Cutting programs can be planned on a map, but running a timber sale involves the site and the buyers.
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 1/4 · how much data exists 3/4.
Contacting local forest owners and gain permission to take inventory of the type
staying humanThe value here is that a specific person handles local forest owners and stands behind it. That is earned, not computed.
importance 3 · SupplementalSource: “Contact local forest owners and gain permission to take inventory of the type, amount, and location of all standing timber on the property.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (14–28 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Getting permission from a landowner depends on a personal approach, though the paperwork is easy to prepare.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Procuring timber from private landowners
staying humanThis work happens in the physical world: timber, in a real place. Software cannot follow it there.
importance 4 · SupplementalSource: “Procure timber from private landowners.” (O*NET task statement)
How this row was scored
Exposure score: 9 out of 100 (2–16 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Buying timber from private owners depends on a relationship and on seeing the standing trees.
The five ratings: output a model can produce 1/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Choosing and preparing sites for new trees
staying humanThis work happens in the physical world: sites, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Choose and prepare sites for new trees, using controlled burning, bulldozers, or herbicides to clear weeds, brush, and logging debris.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 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 and preparing planting sites is machinery and burning work carried out on the ground.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Supervising activities of other forestry workers
staying humanThis work happens in the physical world: activities of other forestry workers, in a real place. Software cannot follow it there.
importance 3 · CoreSource: “Supervise activities of other forestry workers.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (0–13 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Supervising a forestry crew means being on site, watching how the work is going and directing people directly.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Directing and participating in forest fire suppression
staying humanThis work happens in the physical world: forest fire suppression, in a real place. Software cannot follow it there.
importance 3 · SupplementalSource: “Direct, and participate in, forest fire suppression.” (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 value is that a specific person does it.
The rating behind it: Fighting a forest fire is physical work on the fireline.
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 2/4 · how much data exists 2/4.
What this job pays, and how many people do it
- Median pay
- $76,400a 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
- 10,430in 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. Most of what is shifting here is reading one thing and writing another: different tree species' classification in, a record out. The rows above are exactly that shape: studying different tree species' classification and analyzing effect of forest conditions on tree growth rates and tree species prevalence and the yield. What it cannot do is be there in the room, and that is still where contract compliance gets done. 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: monitoring contract compliance and results of forestry activities to assure adherence to government regulations is the middle of this job, and the evidence on this page says it stays with a person.
So, given all that: 6% of this job's task weight sits in rows the software is already learning, 25% in rows that change shape rather than disappear, and 69% in rows it is nowhere near. That is the position, measured across 25 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. Studying different tree species' classification 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 different tree species' classification, 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 contract compliance is 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 establishing short- and long-term plans for management of forest lands and forest resources. 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 foresters (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 10% of its durable work is work you already do and it pays 28.6% less. And on the numbers you do not need one. This job scores 32/100 here, with only 6% of the task list in the top band, and “monitor contract compliance and results of forestry activities to assure adherence to…” 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 perform inspections of forests or forest nurseries, and their equivalent is to perform reforestation or forest renewal. Across both published task lists that is about 10% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 10% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. It is a pay cut, in those words: $54,560 against your $76,400, 28.6% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Forest and Conservation Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already direct, and participate in, forest fire suppression, and their equivalent is to fight forest fires or perform prescribed burning tasks under the direction of fire…. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $43,680 against your $76,400, 42.8% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Zoologists and Wildlife Biologists
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already monitor wildlife populations and assess the impacts of forest operations on population and…, and their equivalent is to inventory or estimate plant and wildlife populations. 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.
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: 6% of its task weight, across 25 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 monitoring contract compliance and results of forestry activities to assure adherence to government regulations 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.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Biological scientists 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
The other groups this work is counted across:
In UK official statistics this job is counted as Biological scientists, Managers and proprietors in forestry, fishing and related services and Agricultural and fishing trades n.e.c.. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.
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.
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Anywhere in the US:
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Anywhere in the US:
CareerOneStop - Licensed occupations finder
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Anywhere in the US:
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No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for foresters, and we are not going to point you at the nearest one and call it a fit.
There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 6% of the work on this page is already inside what they can do.
7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.
The AI Authority is a general community about working with AI, not a course for foresters. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.
Noted, and thank you. We’ll email you if a Space for foresters launches. Nothing else.
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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 Foresters?
- Not as a job, but it is already doing parts of the work. Across the 25 official task statements scored for Foresters (United States, SOC 19-1032), 6% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 32 out of 100 (range 26–39, band: low). 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 “Foresters” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Study different tree species' classification, life history, light and soil requirements, adaptation to new environmental conditions and resistance to disease…” (83/100, very high); “Analyze effect of forest conditions on tree growth rates and tree species prevalence and the yield, duration, seed production, growth viability, and germinat…” (75/100, high); “Establish short- and long-term plans for management of forest lands and forest resources” (56/100, partial). 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 “Foresters” stay human?
- About 69% 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: “Direct, and participate in, forest fire suppression” (0/100, minimal); “Supervise activities of other forestry workers” (6/100, minimal); “Perform inspections of forests or forest nurseries” (8/100, 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 “Foresters” do about AI?
- Start from the ledger rather than the headline: 6% of this job's weighted core work is exposed, and roughly 69% 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 Foresters 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 25 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
About the data on this page
- One row is marked low confidence, so treat it as a ballpark rather than a fine measurement.
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 2 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- 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.
Using these figures?
Cite this
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}
}Data as of release 2026-q4.1, published . 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.