Forest and Conservation Technicians
In short: today's best AI models could do about 7% 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 93% of the time, stays with people.
Provide technical assistance regarding the conservation of soil, water, forests, or related natural resources. May compile data pertaining to size, content, condition, and other characteristics of forest tracts under the direction of foresters, or train and lead forest workers in forest propagation and fire prevention and suppression. May assist conservation scientists in managing, improving, and protecting rangelands and wildlife habitats.
30,410 people do this job in the US. $54,560 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on3 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people37 h
Forest and Conservation Technicians, now: of a 40-hour week, AI could take on 3 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 37 hours stay with people.
The largest pieces: Map forest tract data using digital mapping systems (about 1 h); Develop and maintain computer databases (under an hour); Provide forestry education and general information, advice, and recommendations to woodlot owners, community organizations, and the general public (under an hour).
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.
- 7%
- 0%
- 93%
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, 1%. Today's estimate: 7%.
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
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 20 tasks showed up. Within each of Anthropic's methods, never across a change: 0.028% to 0.097% (released February and March 2025); 0.072% to 0.037% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.028% | 387 of 708 | 1 of 20 |
| Released March 2025 | 0.097% | 164 of 703 | 2 of 20 |
| The week of Aug 4, 2025 (released September 2025) | 0.072% | 186 of 655 | 2 of 20 |
| The week of Nov 13, 2025 (released January 2026) | 0.051% | 234 of 672 | 2 of 20 |
| The week of Feb 5, 2026 (released March 2026) | 0.037% | 295 of 677 | 2 of 20 |
| April 2026 (released June 2026) | none | n/a | 0 of 20 |
| May 2026 (released June 2026) | none | n/a | 0 of 20 |
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 56% of this job's working time as physical work. For 17% of the working time, a robot has been shown doing most of the task somewhere: 8% in a purpose-built cell, 9% in a structured facility. 0.26 of 3, the 402nd highest of the 923 jobs.
- Not physical 44%
- No robot shown 40%
- In a purpose-built cell 8%
- In a structured facility 9%
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 . 20 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Manage forest protection activities, including fire control, fire crew training, and coordination of fire detection and public education programs.Done more than yearly by most who do it. | 19% | 1.3 work days3.3 h to 3.1 work days | Stays with people | |
| Thin and space trees and control weeds and undergrowth, using manual tools and chemicals, or supervise workers performing these tasks.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 16% | 6.7 h3.3 h to 1.3 work days | Stays with people | |
| Perform reforestation or forest renewal, including nursery and silviculture operations, site preparation, seeding and tree planting programs, cone collection, and tree improvement.Done more than yearly by most who do it.Robots: in a purpose-built cell, Autoplant autonomous forest regeneration machine (Bracke planting/scarifying head on autonomous vehicle platform) (Skogforsk / Luleå University of Technology / KTH / Bracke Forest AB) (demonstrated). Anthropic's rating. | 10% | 6.7 h3.3 h to 2.5 work days | Stays with people | |
| Train and lead forest and conservation workers in seasonal activities, such as planting tree seedlings, putting out forest fires, and maintaining recreational facilities.Done more than weekly by most who do it. | 9% | 6.7 h2.5 h to 1.7 work days | Stays with people | |
| Patrol park or forest areas to protect resources and prevent damage.Done more than monthly by most who do it. Robots: in a structured facility, Knightscope K5 Autonomous Security Robot (deployed). Anthropic's rating. | 6% | 4.2 h1.7 h to 6.7 h | Stays with people | |
| Provide technical support to forestry research programs in areas such as tree improvement, seed orchard operations, insect and disease surveys, or experimental forestry and forest engineering research.Done yearly or less by most who do it.Robots: no robot shown. Anthropic's rating. | 6% | 6.7 h2.5 h to 2.5 work days | Stays with people | |
| Conduct laboratory or field experiments with plants, animals, insects, diseases, and soils.Done yearly or less by most who do it.Robots: in a structured facility, Mobile robotic chemist (KUKA mobile manipulator platform) (University of Liverpool) (demonstrated). Anthropic's rating. | 5% | 1 work day3.3 h to 3.1 work days | Stays with people | |
| Select and mark trees for thinning or logging, drawing detailed plans that include access roads.Done yearly or less by most who do it.Robots: no robot shown. Anthropic's rating. | 4% | 6.7 h3.3 h to 2.1 work days | Stays with people | |
| Plan and supervise construction of access routes and forest roads.Done more than monthly by most who do it.Robots: no robot shown. Anthropic's rating. | 4% | 2.1 work days6.7 h to 1 work week | Stays with people | |
| Survey, measure, and map access roads and forest areas such as burns, cut-over areas, experimental plots, and timber sales sections.Done more than yearly by most who do it.Robots: no robot shown. Anthropic's rating. | 4% | 1 work day3.3 h to 2.5 work days | Stays with people | |
| Map forest tract data using digital mapping systems.Done more than monthly by most who do it. | 3% | 5 h2.5 h to 1 work day | 99%Half by now | |
| Inspect trees and collect samples of plants, seeds, foliage, bark, and roots to locate insect and disease damage.Done more than yearly by most who do it.Robots: no robot shown. Anthropic's rating. | 3% | 3.3 h1.7 h to 6.7 h | 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.
- Foresters7% now, 50% by 2028
- Range Managers7% now, 34% by 2028
- Forest and Conservation Workers2% now, 2% by 2028
- Conservation Scientists57% now, 70% by 2028
- Forest Fire Inspectors and Prevention Specialists16% now, 16% by 2028
- First-Line Supervisors of Farming, Fishing, and Forestry Workers23% now, 24% 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 Forest and Conservation Technicians is within reach of AI now?
- An estimated 7% of the working time is within reach of AI models now and 7% 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 Forest and Conservation Technicians come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Map forest tract data using digital mapping systems (99% of the task's time now); Develop and maintain computer databases (87% of the task's time now, 100% by the end of 2028); and Provide forestry education and general information, advice, and recommendations to woodlot owners, community organizations, and the general public (99% of the task's time now).
- Which tasks of Forest and Conservation Technicians stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Manage forest protection activities, including fire control, fire crew training, and coordination of fire detection and public education programs; Thin and space trees and control weeds and undergrowth, using manual tools and chemicals, or supervise workers performing these tasks; and Perform reforestation or forest renewal, including nursery and silviculture operations, site preparation, seeding and tree planting programs, cone collection, and tree improvement. Together such tasks are about 93% of the working time.
- Do people already use AI for the work of Forest and Conservation Technicians?
- 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 2%. 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 Forest and Conservation Technicians?
- Anthropic's robot exposure rating (September 2026) finds 56% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 17% of the working time, 9% in a structured facility. Its index is 0.26 of 3. One example: Knightscope K5 Autonomous Security Robot for "patrol park or forest areas to protect resources and prevent damage". 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 20 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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