Headline risk
3%
Very Low RiskForest and conservation technicians
United States AI Work Index tracks this occupation on the shared structural baseline and then layers on local demand resilience, wages, and confidence.
Why This Score
Share of job tasks that overlap with current AI capabilities
Median annual wage
Projected employment change over 10 years
Typical preparation needed for this occupation
Occupation profile
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.
Task evidence
100% weighted task match · 5% effective coverage
Scores combine AI task overlap, human advantages, and local demand. How it works
United States Now
Median Wage
USD 54,310
Employment 2024
33.8K
Projected Change (2024–34)
-3.2%
Openings (2024–34)
3.9K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Thin and space trees and control weeds and undergrowth, using manual tools and chemicals, or supervise workers performing these tasks. AI use: 0%
- 2. Provide information about, and enforce, regulations, such as those concerning environmental protection, resource utilization, fire safety, and accident prevention. AI use: 0%
- 3. Train and lead forest and conservation workers in seasonal activities, such as planting tree seedlings, putting out forest fires, and maintaining recreational facilities. AI use: 0%
- 4. Manage forest protection activities, including fire control, fire crew training, and coordination of fire detection and public education programs. AI use: 0%
- 5. Patrol park or forest areas to protect resources and prevent damage. AI use: 0%
- 6. Map forest tract data using digital mapping systems. AI use: 0%
Technologies
Requirements
Work context
Worker profile
Median age 41.5 · 274K employed
Under 25: 8% · 25–54: 69% · 55+: 23%
Related
Source coverage
11/11 source families · O*NET 30.2 / OEWS 2024 / ORS 2025 / OOH 2025-08-28 / Projections 2024-34 / CPS 2025 / Anthropic task penetration
Mapping quality
major_group_fallback · employment series present
Narrative & sources
Published limitations
This page shows the local country layer, not realised individual job outcomes. The global structural baseline is shared across countries; only the local demand and wage layer changes here.
Built from O*NET occupation descriptions, task statements, technology skills, work context, Job Zones, Anthropic task penetration, BLS OEWS wages, BLS projection tables, BLS ORS requirements, BLS OOH narrative content, BLS skills data, and BLS CPS occupation age tables.