Forest and conservation workers
SOC Code: 45-4011
Forest and conservation workers carries a 29% AI exposure score (Medium automation risk), with a median annual wage of $43,680 and -4.7% projected employment growth from 2024 to 2034 (BLS), affecting approximately 10,800 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 29% AI exposure, Forest and conservation workers sits 8 points below the 37.2% average across 832 U.S. occupations - more exposed than 26% of them. Most of its core tasks still require human judgment.
Career outlook score
35/100
Forest and conservation workers, weighted across 3 of 3 tracked dimensions
A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.
- Median wage F $43,680
Annual median wage, percentile rank vs all tracked occupations
- Projected growth F -4.7%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) B 29% exposure
Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure
Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).
Automation-risk inventory
Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Forest and conservation workers in the Medium band.
Credential × growth standing
Open entry with non-declining BLS pace
Forest and conservation workers keeps an HS / some college bar (333 of 832) and sits in Slow growth (245 of 832). Lower formal gates with a non-shrinking employment line - skill and AI desks matter more than credentials here.
Where Forest and conservation workers sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Forest and conservation workers sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
29% Lower than most lower than 74% of 832 occupations
Occupations, banded by AI-exposure score
Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.
Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034
Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.
Forest and conservation workers vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Forest and conservation workers is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Where This Score Comes From
Forest and conservation workers's Medium automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score below 40% reflects tasks anchored in physical dexterity, unstructured environments, or high-touch human interaction that current AI cannot reliably replicate.
The employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 45-4011) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Forest and conservation workers be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.
For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Forest and conservation workers. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Check equipment to ensure that it is operating properly.
- 2. Fight forest fires or perform prescribed burning tasks under the direction of fire suppression officers or forestry technicians.
- 3. Perform fire protection or suppression duties, such as constructing fire breaks or disposing of brush.
- 4. Maintain tallies of trees examined and counted during tree marking or measuring efforts.
- 5. Confer with other workers to discuss issues, such as safety, cutting heights, or work needs.
- 6. Explain or enforce regulations regarding camping, vehicle use, fires, use of buildings, or sanitation.
- 7. Operate skidders, bulldozers, or other prime movers to pull a variety of scarification or site preparation equipment over areas to be regenerated.
- 8. Spray or inject vegetation with insecticides to kill insects or to protect against disease or with herbicides to reduce competing vegetation.
- 9. Thin or space trees, using power thinning saws.
- 10. Identify diseased or undesirable trees and remove them, using power saws or hand saws.
Key Skills Required
- Critical Thinking
- Monitoring
- Reading Comprehension
- Active Listening
- Speaking
- Active Learning
- Coordination
- Judgment and Decision Making
- Complex Problem Solving
- Time Management
Knowledge Areas
- Public Safety and Security
- English Language
- Customer and Personal Service
- Administration and Management
- Geography
- Biology
- Communications and Media
- Transportation
- Education and Training
- Computers and Electronics
Frequently Asked Questions
Will AI replace Forest and conservation workers?
Forest and conservation workers has an AI exposure score of 29%, indicating a medium level of automation risk. The majority of tasks in this role require human judgment, creativity, or physical presence that AI cannot easily replicate.
What is the job outlook for Forest and conservation workers?
According to BLS Employment Projections 2024-2034, Forest and conservation workers is projected to decline by 4.7% over the decade. Current employment stands at approximately 10,800 workers.
What skills are needed for Forest and conservation workers?
Key skills for Forest and conservation workers include Critical Thinking, Monitoring, Reading Comprehension, and others. Typical entry-level education is High school diploma or equivalent.
How much do Forest and conservation workers earn?
The median annual wage for Forest and conservation workers is $43,680, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.
What education is required for Forest and conservation workers?
The typical entry-level education for Forest and conservation workers is High school diploma or equivalent. Employers generally expect None of related work experience. On-the-job training typically involves Moderate-term on-the-job training. Requirements can vary by employer and specialization.
Which companies employ Forest and conservation workers?
Forest and conservation workers roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.
AI Exposure Rating
Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.
Nationwide occupations with similar workforce profiles
Two data-derived peer sets for Forest and conservation workers: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (29% here).
- Biochemists and biophysicists · AI exposure 29%
- Construction managers · AI exposure 29%
- Crane and tower operators · AI exposure 29%
- Electrical and electronics repairers, powerhouse, substation, and relay · AI exposure 29%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (-4.7% here).
- Dental laboratory technicians · growth -4.7%
- Wellhead pumpers · growth -4.7%
- Weighers, measurers, checkers, and samplers, recordkeeping · growth -4.8%
- Fishing and hunting workers · growth -4.6%
Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.
Related Occupations
Showing 6 of 10 occupations with a comparable automation-risk profile.
What to do with this
Use Forest and conservation workers' numbers above to compare, not just read in isolation.
- Compare Forest and conservation workers side by side against another occupation on wage, growth, and AI exposure. Workforce comparison tool
- Understand how the AI exposure score above is actually calculated before treating it as a verdict. Reading AI exposure scores
- See the full ranked list of occupations with the lowest automation exposure nationwide. Safest occupations from AI
AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.
Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).