Will AI replace Soil and Plant Scientists?
Work in Soil and Plant Scientists sits in the in-between: AI reaches some of it (~49% in theory) but is only measured doing about 5% today — part human, part machine.
O*NET-SOC 19-1013
How your 19 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~49%). By late 2025, real-world AI use had reached about 5% of its task activity (still rare). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~49%), real-world use (~5%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 19 tasks, ratedBased on real task-level AI scores — click to collapse
- None — AI cannot fully do any core task alone yet.
- Communicate research or project results to other professionals or the public or teach related courses, seminars, or workshops.
- Develop methods of conserving or managing soil that can be applied by farmers or forestry companies.
- Provide information or recommendations to farmers or other landowners regarding ways in which they can best use land, promote plant growth, or avoid or correct problems such as erosion.
- Conduct experiments to develop new or improved varieties of field crops, focusing on characteristics such as yield, quality, disease resistance, nutritional value, or adaptation to specific soils or climates.
- Investigate soil problems or poor water quality to determine sources and effects.
- Investigate responses of soils to specific management practices to determine the use capabilities of soils and the effects of alternative practices on soil productivity.
- Conduct experiments to investigate the underlying mechanisms of plant growth and response to the environment.
- Identify degraded or contaminated soils and develop plans to improve their chemical, biological, or physical characteristics.
- Develop new or improved methods or products for controlling or eliminating weeds, crop diseases, or insect pests.
- Provide advice regarding the development of regulatory standards for land reclamation or soil conservation.
- Study soil characteristics to classify soils on the basis of factors such as geographic location, landscape position, or soil properties.
- Develop improved measurement techniques, soil conservation methods, soil sampling devices, or related technology.
- Conduct research to determine best methods of planting, spraying, cultivating, harvesting, storing, processing, or transporting horticultural products.
- Develop environmentally safe methods or products for controlling or eliminating weeds, crop diseases, or pests.
- Study ways to improve agricultural sustainability, such as the use of new methods of composting.
- Consult with engineers or other technical personnel working on construction projects about the effects of soil problems and possible solutions to these problems.
- Perform chemical analyses of the microorganism content of soils to determine microbial reactions or chemical mineralogical relationships to plant growth.
- Develop ways of altering soils to suit different types of plants.
- Conduct experiments investigating how soil forms, changes, or interacts with land-based ecosystems or living organisms.
- ⚠️ None — every core task is at least partly within AI's reach. The job won't vanish, but almost all of it changes.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.