As of July 2026,
Agricultural Engineers has an AI-exposure score of 57/100
(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.
Agricultural Engineers
More exposed than 52% of the roles we track. Median pay ~US$98,590. About 100 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.
How this role compares to similar Architecture & Engineering roles
What this role usually involves
Apply knowledge of engineering technology and biological science to agricultural problems concerned with power and machinery, electrification, structures, soil and water conservation, and processing of agricultural products.
Broad guidance for this preparation level; exact requirements vary by role and employer.
Source: O*NET 29.1 exact occupation - Agricultural Engineers, SOC 17-2021.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.
Agricultural Engineers tasks, by AI exposure
No automatable tasks identified for this role - its real, individually-assessed tasks consistently read as augmentable (64%).
- Conduct educational programs that provide farmers or farm cooperative members with information that can help them improve agricultural productivity.
- Test agricultural machinery and equipment to ensure adequate performance.
- Design food processing plants and related mechanical systems.
- Design agricultural machinery components and equipment, using computer-aided design (CAD) technology.
We analyzed all 14 Agricultural Engineers tasks - 9 augmentable and 5 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.
Conduct educational programs that provide farmers or farm cooperative members with information that can help them improve agricultural productivity.
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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