As of August 2026,
Range Managers has an AI-exposure score of 55/100
(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.
Range Managers
More exposed than 46% 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.
Will AI replace Range Managers?
No exposure score can predict whether AI will replace this role. The 55/100 score means our current model estimates elevated task exposure from the sources listed on this page. It does not predict an employer decision, headcount, or an individual outcome. The task map below shows the work assessed and where human judgment remains important.
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.
How this role compares to similar Science roles
What this role usually involves
Research or study range land management practices to provide sustained production of forage, livestock, and wildlife.
Broad guidance for this preparation level; exact requirements vary by role and employer.
Source: O*NET 29.1 exact occupation - Range Managers, SOC 19-1031.02. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.
Range Managers tasks, by AI exposure
No automatable tasks identified for this role - its individually-assessed tasks split 75% augmentable / 25% durable.
- Plan and direct construction and maintenance of range improvements, such as fencing, corrals, stock-watering reservoirs, and soil-erosion control structures.
- Study forage plants and their growth requirements to determine varieties best suited to particular range.
- Manage forage resources through fire, herbicide use, or revegetation to maintain a sustainable yield from the land.
- Measure and assess vegetation resources for biological assessment companies, environmental impact statements, and rangeland monitoring programs.
We analyzed all 16 Range Managers tasks - 12 augmentable and 4 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
Every task scored with what to automate, augment, or protect.
Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.
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
No evidence-backed lower-exposure match appears in this O*NET adjacency set. The adjacent paths below remain useful comparisons; the strongest resilience moves are task-level.
Plan and direct construction and maintenance of range improvements, such as fencing, corrals, stock-watering reservoirs, and soil-erosion control structures.
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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Range Managers - median pay by US state (BLS OEWS, USD)
Median annual wage, in USD. US national: US$73,010. More states are being added.