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AI Automation Index
Will AI Replace Forest and Conservation Workers?
Task-level automation exposure for Forest and Conservation Workers: 17 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
19%
weighted task index
17 of 17 tasks scored
Median Salary
$43,680 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Low
6,050 people hold this job — size, not growth
Projected 2025–35
-1.5%
employment change
2,200 openings a year · BLS line item
Pay by state
BLS OEWS publishes 27 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$30,470 – $59,460
Highest medians
Idaho $59,460
Hawaii $56,330
Virginia $54,560
Massachusetts $51,890
Pennsylvania $50,250
Lowest medians
Texas $30,470
Montana $32,600
Iowa $33,600
Connecticut $34,010
Georgia $34,150
State figures come from the 45-4011 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 19%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 68%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 19%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 5%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 36/100
Moderate
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
17 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 5%
1 tasks
Medium exposure (≥ 35%) 13%
2 tasks
Low exposure (below 35%) 82%
14 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Emerging & rewritten tasks
Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.
- New 08/2023 · Incumbent
Create field maps using geographic information systems technology.
Constituent Tasks
#7026 · Core · 22% automatable
Check equipment to ensure that it is operating properly.
visual inspection — Condition assessment needs physical presence
Inspect equipment or facilities to determine condition or maintenance needs.
#7028 · Core · 5% automatable
Fight forest fires or perform prescribed burning tasks under the direction of fire suppression officers or forestry technicians.
situated mobility — Wildland firefighting is physical work in unpredictable terrain
Perform forest firefighting activities.
#7029 · Core · 5% automatable
Perform fire protection or suppression duties, such as constructing fire breaks or disposing of brush.
situated mobility — Wildland firefighting is physical work in unpredictable terrain
Perform forest firefighting activities.
#7027 · Core · 55% automatable
Confer with other workers to discuss issues, such as safety, cutting heights, or work needs.
interpersonal — Coordination needs live negotiation and context
Communicate with other workers to coordinate activities.
#7035 · Supplemental · 70% automatable
Maintain tallies of trees examined and counted during tree marking or measuring efforts.
data analysis — Record inventory data; field collection is human
Record agricultural or forestry inventory data.
#7041 · Supplemental · 55% automatable
Explain or enforce regulations regarding camping, vehicle use, fires, use of buildings, or sanitation.
decision support — General guidance good; site-specific judgment needs human
Advise others on farming or forestry operations, regulations, or equipment.
#7042 · Supplemental · 8% automatable
Operate skidders, bulldozers, or other prime movers to pull a variety of scarification or site preparation equipment over areas to be regenerated.
physical manipulation — Forestry equipment operation is heavy hands-on work
Operate forestry equipment.
#7032 · Supplemental · 10% automatable
Spray or inject vegetation with insecticides to kill insects or to protect against disease or with herbicides to reduce competing vegetation.
physical manipulation — Applying chemicals to plants is field manual work
Apply chemical solutions to plants to protect against disease or insects or to enhance growth.
#7034 · Supplemental · 7% automatable
Thin or space trees, using power thinning saws.
physical manipulation — Forestry equipment operation is heavy hands-on work
Trim trees or other vegetation. Operate forestry equipment.
#7031 · Supplemental · 20% automatable
Identify diseased or undesirable trees and remove them, using power saws or hand saws.
visual inspection — Crop quality needs physical inspection and sensory judgment
Evaluate quality of plants or crops. Cut trees or logs.
#7030 · Supplemental · 24% automatable
Select or cut trees according to markings or sizes, types, or grades.
decision support — Forestry methods need field and site judgment
Determine forestry techniques or methods. Cut trees or logs.
#7038 · Supplemental · 7% automatable
Prune or shear tree tops or limbs to control growth, increase density, or improve shape.
physical manipulation — Forestry equipment operation is heavy hands-on work
Trim trees or other vegetation. Operate forestry equipment.
#7045 · Supplemental · 10% automatable
Maintain campsites or recreational areas, replenishing firewood or other supplies and cleaning kitchens or restrooms.
physical manipulation — Equipment and facility cleaning is hands-on
Clean equipment or facilities.
#7037 · Supplemental · 7% automatable
Erect signs or fences, using posthole diggers, shovels, or other hand tools.
physical manipulation — Agricultural building is hands-on outdoor construction
Build agricultural structures.
#7039 · Supplemental · 4% automatable
Select tree seedlings, prepare the ground, or plant the trees in reforestation areas, using manual planting tools.
physical manipulation — Planting crops requires physical field work
Plant crops, trees, or other plants.
#7040 · Supplemental · 3% automatable
Provide assistance to forest survey crews by clearing site-lines, holding measuring tools, or setting stakes.
physical manipulation — Manual agricultural labor in unstructured fields
Perform manual agricultural, aquacultural, or horticultural tasks.
#20632 · Supplemental · 7% automatable
Sort tree seedlings, discarding substandard seedlings, according to standard charts or verbal instructions.
physical manipulation — Agricultural material sorting is hands-on field work
Sort forestry or agricultural materials.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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