Fallers
In short: today's best AI models could do about 0% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 100% of the time, stays with people.
Use axes or chainsaws to fell trees using knowledge of tree characteristics and cutting techniques to control direction of fall and minimize tree damage.
3,130 people do this job in the US. $52,100 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on0 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people40 h
Fallers, now: of a 40-hour week, AI could take on 0 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 40 hours stay with people.
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 0%
- 0%
- 100%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 0%. Today's estimate: 0%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
None of this job's 17 tasks showed up in the Claude.ai conversations Anthropic sampled in any of its 7 releases, from February 2025 to May 2026.
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 91% of this job's working time as physical work. For 47% of the working time, a robot has been shown doing most of the task somewhere: 46% in a purpose-built cell, 1% in a structured facility. 0.48 of 3, the 317th highest of the 923 jobs.
- Not physical 9%
- No robot shown 44%
- In a purpose-built cell 46%
- In a structured facility 1%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
The tasks
Sorted by . 17 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Clear brush from work areas and escape routes, and cut saplings and other trees from direction of falls, using axes, chainsaws, or bulldozers.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 17% | 33 min13 min to 1.7 h | Stays with people | |
| Select trees to be cut down, assessing factors such as site, terrain, and weather conditions before beginning work.Done hourly or more by most who do it. | 13% | 21 min8 min to 50 min | Stays with people | |
| Control the direction of a tree's fall by scoring cutting lines with axes, sawing undercuts along scored lines with chainsaws, knocking slabs from cuts with single-bit axes, and driving wedges.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 11% | 17 min8 min to 33 min | Stays with people | |
| Measure felled trees and cut them into specified log lengths, using chain saws and axes.Done hourly or more by most who do it. Robots: in a purpose-built cell, Inotech Intellibuck stem merchandiser; USNR LogPro merchandiser (sold). Anthropic's rating. | 10% | 17 min8 min to 38 min | Stays with people | |
| Work as a member of a team, rotating between chain saw operation and skidder operation.Done several times a day by most who do it.Robots: no robot shown. Anthropic's rating. | 8% | 3.3 h50 min to 6.7 h | Stays with people | |
| Appraise trees for certain characteristics, such as twist, rot, and heavy limb growth, and gauge amount and direction of lean, to determine how to control the direction of a tree's fall with the least damage.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 7% | 13 min4 min to 29 min | Stays with people | |
| Trim off the tops and limbs of trees, using chainsaws, delimbers, or axes.Done hourly or more by most who do it. Robots: in a purpose-built cell, Arbro-Stroke 400 / 1000 stroke harvester head (sold). Anthropic's rating. | 7% | 21 min8 min to 50 min | Stays with people | |
| Determine position, direction, and depth of cuts to be made, and placement of wedges or jacks.Done hourly or more by most who do it. | 6% | 10 min4 min to 21 min | Stays with people | |
| Saw back-cuts, leaving sufficient sound wood to control direction of fall.Done hourly or more by most who do it. Robots: in a purpose-built cell, SAHA (Supervised Autonomous HArvester, based on RCM Harveri 25) (ETH Zurich Robotic Systems Lab / DigiForest consortium) (demonstrated). Anthropic's rating. | 6% | 8 min4 min to 17 min | Stays with people | |
| Maintain and repair chainsaws and other equipment, cleaning, oiling, and greasing equipment, and sharpening equipment properly.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 25 min13 min to 50 min | Stays with people | |
| Assess logs after cutting to ensure that the quality and length are correct.Done hourly or more by most who do it. Robots: in a purpose-built cell, CT Log (computed tomography log scanner) (MiCROTEC) (sold). Anthropic's rating. | 4% | 7 min3 min to 13 min | Stays with people | |
| Insert jacks or drive wedges behind saws to prevent binding of saws and to start trees falling.Done several times a day by most who do it. Robots: no robot shown. Anthropic's rating. | 2% | 7 min3 min to 13 min | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Tree Trimmers and Pruners5% now, 6% by 2028
- Logging Equipment Operators2% now, 2% by 2028
- Forest and Conservation Workers2% now, 2% by 2028
- Log Graders and Scalers6% now, 6% by 2028
- Sawing Machine Setters, Operators, and Tenders, Wood8% now, 8% by 2028
- Landscaping and Groundskeeping Workers0% now, 0% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Fallers is within reach of AI now?
- An estimated 0% of the working time is within reach of AI models now and 0% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Fallers come within reach first?
- No task has a meaningful share of its time within reach now or by the end of 2028, on the long-run pace at four in five: the work is mostly people work and body work, which the site does not count.
- Which tasks of Fallers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Clear brush from work areas and escape routes, and cut saplings and other trees from direction of falls, using axes, chainsaws, or bulldozers; Select trees to be cut down, assessing factors such as site, terrain, and weather conditions before beginning work; and Control the direction of a tree's fall by scoring cutting lines with axes, sawing undercuts along scored lines with chainsaws, knocking slabs from cuts with single-bit axes, and driving wedges. Together such tasks are about 100% of the working time.
- Do people already use AI for the work of Fallers?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Fallers?
- Anthropic's robot exposure rating (September 2026) finds 91% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 47% of the working time, 1% in a structured facility. Its index is 0.48 of 3. One example: Inotech Intellibuck stem merchandiser; USNR LogPro merchandiser for "measure felled trees and cut them into specified log lengths, using chain saws and axes". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 17 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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