As of July 2026, Conservation Scientists has an AI-exposure score of 59/100 (Elevated exposure) on the AI-Safe Careers index. This is an estimate of task exposure, not a prediction of job loss.
Score inputs for this role: This role starts from O*NET 29.1 occupational descriptors and is empirically grounded by Penn/OpenAI GPTs are GPTs study, Anthropic Economic Index (June 26, 2026), Felten, Raj and Seamans AIOE index. BLS labor-market figures are separate context, not score inputs.

AI Exposure Score for

Conservation Scientists

59/100
Elevated exposure
LowModerateElevatedHighVery High

More exposed than 60% of the roles we track. Median pay ~US$73,010. About 2,500 projected openings a year (BLS 2024–34 - growth plus replacement).

Pay & demand figures are US medians (BLS, in USD) - your local figures will differ. Your exposure score applies broadly.

Early-career context (study ages 22-25)

This role is in the Elevated exposure band, but its assessed task mix is not automation-heavy. The study found the decline concentrated where AI was more likely to automate rather than augment work, so the headline figure should not be applied directly.

The November 2025 revision reports a 16% relative employment decline for workers ages 22-25 in the most AI-exposed U.S. occupations, after firm-level controls, relative to workers in less-exposed fields and more experienced workers in the same occupations.

Use the task map to identify durable work and the skills worth building early.

Stanford Digital Economy Lab, Canaries in the Coal Mine - November 2025 revision

This is group-level U.S. payroll evidence, not a personal forecast. The authors do not claim that AI alone caused the change, and this context does not alter the exposure score.

Data sources, not endorsements: O*NET and curated role data; empirical AI signals where matched; BLS employment, pay, and demand as separate context.Methodology Data sources
Role snapshot

What this role usually involves

O*NET 29.1 exact occupation

Manage, improve, and protect natural resources to maximize their use without damaging the environment. May conduct soil surveys and develop plans to eliminate soil erosion or to protect rangelands. May instruct farmers, agricultural production managers, or ranchers in best ways to use crop rotation, contour plowing, or terracing to conserve soil and water; in the number and kind of livestock and forage plants best suited to particular ranges; and in range and farm improvements, such as fencing and reservoirs for stock watering.

Common titles
ConservationistLand Resource SpecialistResearch Soil ScientistResource ConservationistEnvironmental AnalystEnvironmental Quality Scientist
O*NET job-zone preparation
Job Zone 4 · Considerable Preparation Needed Most of these occupations require a four-year bachelor's degree, but some do not. A considerable amount of work-related skill, knowledge, or experience is needed for these occupations.

Broad guidance for this preparation level; exact requirements vary by role and employer.

Skills and knowledge
Reading ComprehensionComplex Problem SolvingSpeakingCritical ThinkingScienceWriting
Tools and technology
ESRI ArcGIS softwareMicrosoft ExcelMicrosoft Office softwareMicrosoft WordAdobe AcrobatAutodesk AutoCAD
Work context
Email useTelephoneFace-to-face discussionsDecision latitudeFrequent contact with others

Source: O*NET 29.1 exact occupation - Conservation Scientists, SOC 19-1031.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.

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Conservation Scientists tasks, by AI exposure

Automatable
  • Gather information from geographic information systems (GIS) databases or applications to formulate land use recommendations.
  • Enter local soil, water, or other environmental data into adaptive or Web-based decision tools to identify appropriate analyses or techniques.
  • Provide information, knowledge, expertise, or training to government agencies at all levels to solve water or soil management problems or to assure coordination of resource protection activities.
1 more automatable task locked in the report.
Augmentable
  • Develop or maintain working relationships with local government staff or board members.
  • Respond to complaints or questions on wetland jurisdiction, providing information or clarification.
13 more augmentable tasks locked in the report.
Durable
  • Develop, conduct, or participate in surveys, studies, or investigations of various land uses to inform corrective action plans.

We analyzed all 20 Conservation Scientists tasks - 4 automatable, 15 augmentable and 1 durable. The full task map - every task with exactly what to do about each - is in your Career Report.

Your report unlocks three concrete artifacts

Full task map

Every task scored with what to automate, augment, or protect.

Adjacent path comparison

Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.

30/60/90 plan + PDF

A keepable roadmap plus resume and LinkedIn repositioning.

Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.

Adjacent career paths

Relatedness shows how reachable a move may be. A path is labeled lower exposure only when its score is at least 6 points lower; every row shows the measured difference.

Environmental Restoration Planners
80% skills overlap; 6 points lower - lower exposure; Elevated band; ~US$82,220
View path
53
7 more adjacent paths with exposure deltas, salary, demand, and reachability in your Career Report.
Agent Reality Check (on-site workflow preview)

Gather information from geographic information systems (GIS) databases or applications to formulate land use recommendations.

Check what deployed AI agents can attempt on tasks like this using dated capability evidence. You review the real task before any analysis runs.
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Your AI-Safe Career Report

Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.

Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026

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Important: This is an estimate of AI exposure, not a prediction that your job will disappear. It is designed to help you understand how your role may change and improve your career resilience.