Will AI replace Tree Trimmers and Pruners?

Not as a job, but it is already doing parts of the work. Across the 24 official task statements scored for Tree Trimmers and Pruners (United States, SOC 37-3013), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 5 out of 100 (range 4–9, 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 “Tree Trimmers and Pruners” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Plan and develop budgets for tree work, and estimate the monetary value of trees” (56/100, partial); “Provide information to the public regarding trees, such as advice on tree care” (48/100, partial); “Inspect trees to determine if they have diseases or pest problems” (14/100, 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 “Tree Trimmers and Pruners” stay human?

About 92% 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: “Split logs or wooden blocks into bolts, pickets, posts, or stakes, using hand tools such as ax wedges, sledgehammers, and mallets” (0/100, minimal); “Scrape decayed matter from cavities in trees and fill holes with cement to promote healing and to prevent further deterioration” (0/100, minimal); “Apply tar or other protective substances to cut surfaces or seal surfaces and to protect them from fungi and insects” (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 “Tree Trimmers and Pruners” do about AI?

Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 92% 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 Tree Trimmers and Pruners 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 24 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

Tree Trimmers and Pruners

operating shredding and chipping equipment, trimming top and inspecting trees to determine if they have diseases or pest problems. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: operating boom trucks, loaders, stump chippers, brush chippers, tractors, power saws, trucks, sprayers and other equipment and tools 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: 8%
staying human: 92%

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

Whole-job exposure score 5 out of 100 (4–9 allowing for uncertainty): minimal exposure, across 24 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 tree trimmers and pruners 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 providing information to the public regarding trees: the overhead at the edges, not the middle you trained for.

Your week, as this page understands it

Using sophisticated climbing and rigging techniques, cut away dead or excess branches from trees or shrubs to maintain right-of-way for roads, sidewalks, or utilities, or to improve appearance, health, and value of tree. Prune or treat trees or shrubs using handsaws, hand pruners, clippers, and power pruners. Works off the ground in the tree canopy and may use truck-mounted lifts. The job title says “tree trimmers” or “pruners”: officially one job, two names. The real job is the part underneath: operating boom trucks, loaders, stump chippers, brush chippers, tractors, power saws, trucks, sprayers and other equipment and tools. 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 tree trimmers and pruners is not one task. It is 24 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is operating boom trucks, loaders, stump chippers, brush chippers, tractors, power saws, trucks, sprayers and other equipment and tools, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 0%
changing shape: 8%
staying human: 92%

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.

3 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

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

2 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.

Providing information to the public regarding trees
The software now makes the first pass at information, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Provide information to the public regarding trees, such as advice on tree care.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 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: General tree care advice is well documented, so software answers most public questions 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 1/4 · how much data exists 3/4.
Planning and developing budgets for tree work
The software now makes the first pass at budgets, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Plan and develop budgets for tree work, and estimate the monetary value of trees.” (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: Tree valuation and job budgets follow published formulas and cost data, though the tree needs measuring first.
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.

Staying human

22 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.

Operating boom trucks, loaders, stump chippers, brush chippers, tractors, power saws, trucks, sprayers and other equipment and tools
This work happens in the physical world: boom trucks, loaders, stump chippers, brush chippers, tractors, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Operate boom trucks, loaders, stump chippers, brush chippers, tractors, power saws, trucks, sprayers, and other equipment and 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: Operating boom trucks, chippers and saws means being in the cab or holding the tool.
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.
Cleaning sharpen and lubricate tools and equipment
This work happens in the physical world: sharpen, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean, sharpen, and lubricate tools and equipment.” (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: Cleaning, sharpening and oiling tools is hands-on maintenance.
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.
Operating shredding and chipping equipment
This work happens in the physical world: equipment, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Operate shredding and chipping equipment, and feed limbs and brush into the machines.” (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: Feeding brush into a chipper is physical work done at the machine.
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.
Cutting away dead and excess branches from trees
This work happens in the physical world: away dead, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Cut away dead and excess branches from trees, or clear branches around power lines, using climbing equipment or buckets of extended truck booms, or chainsaws, hooks, handsaws, shears, and clippers.” (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 branches from a tree or around power lines is done aloft with a saw in hand.
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.
Hoisting tools and equipment to tree trimmers
This work happens in the physical world: tools, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Hoist tools and equipment to tree trimmers, and lower branches with ropes or block and tackle.” (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: Hauling tools up to a climber and lowering branches on ropes is physical teamwork on site.
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.
Trimming top and reshape trees to achieve attractive shapes or to remove low-hanging branches
This work happens in the physical world: top, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Trim, top, and reshape trees to achieve attractive shapes or to remove low-hanging branches.” (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: Shaping a tree by cutting it is hands-on work with saws.
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.
Supervising others engaged in tree trimming work and training lower-level employees
This work happens in the physical world: this work, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Supervise others engaged in tree trimming work and train lower-level employees.” (O*NET task statement)
How this row was scored
Exposure score: 4 out of 100 (0–11 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 and training crews happens on site, and safe tree work depends on trust between people who know each other.
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 3/4 · how much data exists 2/4.
Loading debris and refuse onto trucks and haul it away for disposal
This work happens in the physical world: debris, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Load debris and refuse onto trucks and haul it away for disposal.” (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: Loading debris onto a truck and hauling it away 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.

Show the other 14 tasks

Inspecting trees to determine if they have diseases or pest problems
staying human
This work happens in the physical world: trees, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Inspect trees to determine if they have diseases or pest problems.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 allowing for uncertainty): minimal 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: Tree diseases are well documented, but diagnosing one usually means being at the tree and examining it closely.
The five ratings: output a model can produce 2/4 · 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 3/4.
Climbing trees, using climbing hooks and belts or climb ladders to gain access to work areas
staying human
This work happens in the physical world: trees, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Climb trees, using climbing hooks and belts, or climb ladders to gain access to work areas.” (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: Climbing a tree with hooks and a belt is as physical as work gets.
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.
Pruning, cutting down, fertilize and spraying trees as directed by tree surgeons
staying human
This work happens in the physical world: down, fertilize and spraying trees, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Prune, cut down, fertilize, and spray trees as directed by tree surgeons.” (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, felling, feeding and spraying trees is physical work carried out at the tree.
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.
Cabling brace, tie, bolt, stake and guy trees and branches to provide support
staying human
This work happens in the physical world: brace, tie, bolt, in a real place. Software cannot follow it there.
importance 3 · Core
Source: “Cable, brace, tie, bolt, stake, and guy trees and branches to provide support.” (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: Cabling and bracing a tree means fitting hardware to the trunk and branches.
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.
Collecting debris and refuse from tree trimming and removal operations into piles
staying human
This work happens in the physical world: debris, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Collect debris and refuse from tree trimming and removal operations into piles, using shovels, rakes, or other 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: Raking and piling debris is manual work on site.
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.
Clearing sites, streets and grounds of woody and herbaceous materials
staying human
This work happens in the physical world: sites, streets and grounds of woody and herbaceous, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clear sites, streets, and grounds of woody and herbaceous materials, such as tree stumps and fallen trees and limbs.” (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 fallen limbs and stumps from a site is physical labor.
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.
Removing broken limbs from wires
staying human
This work happens in the physical world: broken limbs, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Remove broken limbs from wires, using hooked extension poles.” (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: Reaching a broken limb off a wire with an extension pole is physical work at height.
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.
Trimming jagged stumps, using saws or pruning shears
staying human
This work happens in the physical world: jagged stumps, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Trim jagged stumps, using saws or pruning shears.” (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: Trimming a stump with a saw or shears is done at the stump.
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.
Transplanting and removing trees and shrubs
staying human
This work happens in the physical world: trees, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Transplant and remove trees and shrubs, and prepare trees for moving.” (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: Digging out, moving and replanting trees and shrubs is heavy 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.
Spraying trees to treat diseased or unhealthy trees
staying human
This work happens in the physical world: trees, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Spray trees to treat diseased or unhealthy trees, including mixing chemicals and calibrating spray equipment.” (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: Mixing chemicals, calibrating the sprayer and spraying the tree is hands-on work throughout.
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.
Watering root-feed and fertilize trees
staying human
This work happens in the physical world: root-feed, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Water, root-feed, and fertilize trees.” (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: Watering, root-feeding and fertilizing trees is done on the ground at each tree.
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.
Applying tar or other protective substances to cut surfaces or seal surfaces and to protect them from fungi and insects
staying human
This work happens in the physical world: tar, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Apply tar or other protective substances to cut surfaces or seal surfaces and to protect them from fungi and insects.” (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: Brushing a sealant onto a cut surface is a manual task at the tree.
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.
Scraping decayed matter from cavities in trees and filling holes with cement to promote healing and to prevent further deterioration
staying human
This work happens in the physical world: decayed matter, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Scrape decayed matter from cavities in trees and fill holes with cement to promote healing and to prevent further deterioration.” (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: Scraping out a decayed cavity and filling it is careful handwork on the tree.
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.
Splitting logs or wooden blocks into bolts
staying human
This work happens in the physical world: logs, in a real place. Software cannot follow it there.
importance 2 · Supplemental
Source: “Split logs or wooden blocks into bolts, pickets, posts, or stakes, using hand tools such as ax wedges, sledgehammers, and mallets.” (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: Splitting logs with wedges, sledgehammers and mallets is manual labor.
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.

What this job pays, and how many people do it

Median pay: $50,960a 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: 55,160in 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: information in, a record out. The rows above are exactly that shape: providing information to the public regarding trees. What it cannot do is be there in the room, and that is still where boom trucks, loaders, stump chippers, brush chippers, tractors get 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: operating boom trucks, loaders, stump chippers, brush chippers, tractors, power saws, trucks, sprayers and other equipment and tools 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, 8% in rows that change shape rather than disappear, and 92% in rows it is nowhere near. That is the position, measured across 24 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. Providing information to the public regarding trees 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 information, 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 boom trucks, loaders, stump chippers, brush chippers, tractors 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 providing information to the public regarding trees. 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 tree trimmers and pruners (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was helpers--installation, maintenance, and repair workers: only about 4% of its durable work is work you already do and it pays 22.2% less. And on the numbers you do not need one. This job scores 5/100 here, with only 0% of the task list in the top band, and “operate boom trucks, loaders, stump chippers, brush chippers, tractors, power saws, trucks…” 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.

Helpers--Installation, Maintenance, and Repair Workers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already clean, sharpen, and lubricate tools and equipment, and their equivalent is to clean or lubricate vehicles, machinery, equipment, instruments, tools, work areas, and other objects…. 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. It is a pay cut, in those words: $39,630 against your $50,960, 22.2% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Fallers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already clean, sharpen, and lubricate tools and equipment, and their equivalent is to maintain and repair chainsaws and other equipment, cleaning, oiling, and greasing equipment, and…. 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. And it is a narrow door: about 3,130 of those jobs against 55,160 of yours (OEWS May 2025), 6% as many seats.
Look at that job’s page anyway →
Electrical Power-Line Installers and Repairers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already climb trees, using climbing hooks and belts, or climb ladders to gain access…, and their equivalent is to climb poles or use truck-mounted buckets to access equipment. Across both published task lists that is about 2% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 2% 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 24 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 operating boom trucks, loaders, stump chippers, brush chippers, tractors, power saws, trucks, sprayers and other equipment and tools 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 Groundsmen and greenkeepers 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 Groundsmen and greenkeepers, Gardeners and landscape gardeners 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.
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 tree trimmers / pruners launches. Nothing else.

That did not look like an email address, so nothing was saved. Have another go below.

We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.

No Space for tree trimmers / pruners 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 tree trimmers / pruners 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 tree trimmers / pruners 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 Tree Trimmers and Pruners?: Not as a job, but it is already doing parts of the work. Across the 24 official task statements scored for Tree Trimmers and Pruners (United States, SOC 37-3013), 0% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 5 out of 100 (range 4–9, 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 “Tree Trimmers and Pruners” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Plan and develop budgets for tree work, and estimate the monetary value of trees” (56/100, partial); “Provide information to the public regarding trees, such as advice on tree care” (48/100, partial); “Inspect trees to determine if they have diseases or pest problems” (14/100, 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 “Tree Trimmers and Pruners” stay human?: About 92% 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: “Split logs or wooden blocks into bolts, pickets, posts, or stakes, using hand tools such as ax wedges, sledgehammers, and mallets” (0/100, minimal); “Scrape decayed matter from cavities in trees and fill holes with cement to promote healing and to prevent further deterioration” (0/100, minimal); “Apply tar or other protective substances to cut surfaces or seal surfaces and to protect them from fungi and insects” (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 “Tree Trimmers and Pruners” do about AI?: Start from the ledger rather than the headline: 0% of this job's weighted core work is exposed, and roughly 92% 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 Tree Trimmers and Pruners 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 24 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.
3 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.

How we score a job Download this release Look up another job

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}
}

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.