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AI exposure report
Will AI replace Soil and Plant Scientists?
Some of your tasks will be automated. People who use AI will have the edge.
Task exposure to today's AI
Moderate exposure
This is the occupation's typical task mix. Your own score can be up to 30 points higher or lower depending on how you work: routine share, people contact, judgment and how much you already use AI.
Get your personal scoreWill AI replace Soil and Plant Scientists?
Not entirely. Today's AI tools can take on about 48% of the typical work in this occupation, mostly: communicate research or project results to other professionals or the public or teach related courses, seminars, or workshops. The parts that stay human include: Conduct experiments to investigate the underlying mechanisms of plant growth and response to the environment.; Communicate research or project results to other professionals or the public or teach related courses, seminars, or workshops.; 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..
People who learn to use AI for the automatable parts keep the edge. The 3-phase plan below shows where to start.
Which tasks AI can take on
The largest tasks in this occupation, their share of the working week, and how much of each today's AI tools can do.
+ 21 more tasks (51% of the week) in the full test.
Your human edge
- Conduct experiments to investigate the underlying mechanisms of plant growth and response to the environment.
- Communicate research or project results to other professionals or the public or teach related courses, seminars, or workshops.
- 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.
AI tools to try
ChatGPT / Claude for literature and writingAI research tools (e.g. Elicit, Consensus, Semantic Scholar)Copilot for data analysis code (Python, R)Related roles
A 3-phase AI learning plan
Phase 1
Faster literature and writing
- Literature search and summaries with AI, always checked against the papers.
- Drafts of methods, reports and grant text.
- Reference management and formatting.
Project
Use AI to summarize 15 recent papers on cover crop erosion control into a 2-page literature brief, then verify each citation against the source.Phase 2
AI for data analysis
- Analysis code in Python or R written with AI help.
- Visualisation and statistics explained step by step.
- Reproducibility: version code and prompts.
Project
Use AI to write Python/R code analyzing one season's soil nutrient dataset, generating 3 visualizations, and document prompts for reproducibility.Phase 3
AI as a research method
- Classification, extraction or modelling with AI on your data.
- Validate against human labels or ground truth.
- Ethics, data protection and disclosure of AI use.
Project
Train an AI model to classify soil samples by texture from your field photos, then validate accuracy against 50 lab-tested ground truth samples.