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Soil and Plant Scientists

SOC: 19-1013.00 · Job Zone: 5

AI Impact Score: 48/100 — Partial Automation Likely
By Meo Advisors Editorial, Editorial Team
AI Score
48/100
Partial Automation Likely
Employment
17K
Median Wage
$71,410
per year
Timeline
5-10 years
to significant impact

Key Takeaways

  • AI Impact Score: 48/100Partial Automation Likely. Partial automation is likely for key tasks in this occupation.
  • 17K workers currently employed.
  • Mean annual wage: $71,410.
  • 1 of 15 key tasks can already be performed by AI tools today.

What Soil and Plant Scientists Do

Conduct research in breeding, physiology, production, yield, and management of crops and agricultural plants or trees, shrubs, and nursery stock, their growth in soils, and control of pests; or study the chemical, physical, biological, and mineralogical composition of soils as they relate to plant or crop growth. May classify and map soils and investigate effects of alternative practices on soil and crop productivity.

Also known as

Common HR-system job titles that map to this O*NET occupation (19-1013.00). Use these terms in resumes, postings, and org charts to match this AI-replaceability profile.

Agricultural SpecialistAgriculturistAgronomistApiculturistArboreal ScientistArboriculture ResearcherArboriculturistArboristBiological Science Technician (Biological Science Tech)Botanist

Have a job title that doesn't appear here? Upload your org chart to score your full headcount against AI replaceability.

AI Impact Analysis

Soil and Plant Scientists represent a specialized workforce of 16,600 professionals earning an average of $71,410 annually, conducting critical research in crop breeding, soil composition, and agricultural productivity. This highly educated field (Job Zone 5/5) sits at the intersection of traditional agricultural science and emerging digital technologies, making it particularly susceptible to AI-driven transformation over the next decade.

AI tools are already automating several key tasks in this field. Data analysis and information processing, which scored 4.48/5 in importance, are being revolutionized by platforms like R with integrated AI packages and IBM SPSS Statistics with machine learning capabilities. GPT-4 and Claude are handling routine report writing and documentation tasks (importance: 4.2/5), while computer vision models integrated with ESRI ArcGIS are automating soil classification and mapping activities. Automated experimental design platforms are beginning to handle portions of crop breeding experiments, and AI-powered sensors combined with machine learning algorithms are streamlining soil testing and quality assessment.

However, critical human-essential tasks remain firmly in the domain of scientists. Complex problem solving (importance: 3.88/5) requiring deep understanding of biological systems cannot be replicated by current AI. The development of new conservation methods and regulatory standards demands human judgment, ethical considerations, and stakeholder communication that AI cannot provide. Field work, hands-on experimentation, and the nuanced interpretation of biological phenomena in real-world agricultural settings require human expertise, intuition, and adaptability.

The automation timeline shows clear phases: 1-3 years will see widespread adoption of AI-assisted data analysis, automated report generation, and enhanced soil mapping tools. 3-5 years will bring more sophisticated experimental design automation, predictive modeling for crop yields, and AI-powered pest identification systems. However, core research design, field supervision, and strategic agricultural planning will remain human-driven throughout this period.

Major agricultural companies like Monsanto (now Bayer), John Deere, and Cargill are already deploying AI agents for soil analysis, crop monitoring, and yield prediction. Research institutions are implementing AI-assisted laboratory management systems, while consulting firms are using automated tools for soil conservation recommendations. The integration is happening gradually but consistently across the industry.

Task-by-Task AI Analysis

TaskAI Status
Communicate research or project results to other professionals or the public or teach related courses, seminars, or workshops.
AI can help draft presentations and reports, but human expertise is needed for nuanced communication and teaching.
AI Assists
Now
Develop methods of conserving or managing soil that can be applied by farmers or forestry companies.
Requires deep understanding of local ecosystems and stakeholder needs that AI cannot replicate.
Human Essential
5+ years
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 can process data and suggest recommendations, but human judgment is crucial for site-specific advice.
AI Assists
1-2 years
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.
AI assists with experimental design and data analysis, but hypothesis generation requires human creativity.
AI Assists
3-5 years
Investigate soil problems or poor water quality to determine sources and effects.
AI can analyze patterns in soil data, but field investigation and problem diagnosis need human expertise.
AI Assists
1-2 years
Investigate responses of soils to specific management practices to determine the use capabilities of soils and the effects of alternative practices on soil productivity.
Statistical analysis is AI-enhanced, but interpreting real-world agricultural implications requires human insight.
AI Assists
1-2 years
Conduct experiments to investigate the underlying mechanisms of plant growth and response to the environment.
Fundamental research requires human creativity, hypothesis formation, and experimental intuition.
Human Essential
5+ years
Identify degraded or contaminated soils and develop plans to improve their chemical, biological, or physical characteristics.
AI can identify patterns in soil data, but remediation planning requires human judgment and local knowledge.
AI Assists
3-5 years
Develop new or improved methods or products for controlling or eliminating weeds, crop diseases, or insect pests.
AI assists with pattern recognition and testing, but innovation requires human creativity and safety assessment.
AI Assists
3-5 years
Provide advice regarding the development of regulatory standards for land reclamation or soil conservation.
Regulatory development requires human judgment, ethical considerations, and stakeholder engagement.
Human Essential
5+ years
Study soil characteristics to classify soils on the basis of factors such as geographic location, landscape position, or soil properties.
Pattern recognition and classification tasks are well-suited for current AI capabilities.
AI Can Do This
Now
Develop improved measurement techniques, soil conservation methods, soil sampling devices, or related technology.
Innovation and engineering design require human creativity and practical understanding.
Human Essential
5+ years
Conduct research to determine best methods of planting, spraying, cultivating, harvesting, storing, processing, or transporting horticultural products.
AI can optimize processes through data analysis, but field testing and validation need human oversight.
AI Assists
3-5 years
Develop environmentally safe methods or products for controlling or eliminating weeds, crop diseases, or pests.
AI helps with literature review and initial screening, but safety assessment requires human expertise.
AI Assists
3-5 years
Study ways to improve agricultural sustainability, such as the use of new methods of composting.
AI can model sustainability impacts, but developing practical solutions requires human innovation.
AI Assists
3-5 years

AI Tools Disrupting Soil and Plant Scientists

GPT-4medium impact
AI Assistant
Report writing, documentation, and research communication tasks
IBM SPSS Statistics with AIhigh impact
Analytics Platform
Statistical analysis and data interpretation for soil and crop studies
ESRI ArcGIS with Machine Learninghigh impact
GIS Software
Soil classification, mapping, and spatial analysis tasks
Computer Vision APIsmedium impact
Image Recognition
Visual soil assessment and crop monitoring activities
R with AI Packageshigh impact
Statistical Software
Data analysis, modeling, and experimental design support
Predictive Analytics Platformsmedium impact
Data Science
Crop yield prediction and agricultural optimization tasks

Key Skills

Reading Comprehension
4.0 / 5
Speaking
4.0 / 5
Science
4.0 / 5
Critical Thinking
4.0 / 5
Active Learning
4.0 / 5
Active Listening
3.9 / 5
Writing
3.9 / 5
Complex Problem Solving
3.9 / 5
Judgment and Decision Making
3.8 / 5
Systems Analysis
3.5 / 5
Systems Evaluation
3.5 / 5
Mathematics
3.3 / 5

Key Tasks

  • 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.

Technology Skills Used

Microsoft ExcelMicrosoft Office softwareRAutodesk AutoCADESRI ArcGIS softwareIBM SPSS StatisticsMicrosoft AccessMicrosoft Active Server Pages ASPMicrosoft PowerPointMicrosoft WordSAS3dMapperErosion Productivity Impact Calculator EPICEuropean Soil Erosion Model EUROSEMGAEA Technologies WinSieveGEOEASGeographic information system GIS softwareGeographic information system GIS systemsGSLIBGstatLandSerfLeica Geosystems ERDAS IMAGINENational Resources Conservation Service NRCS PEDON Description Program PDPNational Resources Conservation Service NRCS Soils ExplorerNational Soil Information System NASIS

Hot + In Demand  Hot Technology  In Demand   ↗ = View AI replaceability analysis

Salary Range

N/A
N/A
Median: $71,410
10th percentile90th percentile

Career Transition Guidance

Soil and Plant Scientists facing AI disruption have several viable transition paths within related scientific fields. Conservation Scientists (19-1031.00) represent the closest transition, requiring minimal additional training as the core skills in environmental assessment, data analysis, and field research directly transfer. The shift to Precision Agriculture Technicians (19-4012.01) offers opportunities to specialize in the technology side of agriculture, leveraging existing knowledge of soil science while gaining expertise in GPS, sensors, and automated farming systems.

Microbiologists (19-1022.00) and Industrial Ecologists (19-2041.03) present medium-term transition options that build on the biological sciences foundation. These roles require 1-2 years of additional training in specialized laboratory techniques or environmental impact assessment, but the analytical skills, research methodology, and scientific writing capabilities transfer directly. Agricultural Engineers (17-2021.00) offer a higher-paying path for those willing to pursue additional engineering coursework, combining soil science knowledge with technology development.

For immediate career security, professionals should focus on developing expertise in AI-augmented soil analysis tools, stakeholder communication, and field research management. Those planning longer-term transitions should begin acquiring complementary skills in data science, environmental consulting, or agricultural technology development. The 6-12 month timeline for basic AI tool proficiency, combined with 2-3 years for specialized retraining, provides a realistic pathway for career evolution in this changing field.

Related Occupations

Conservation Scientists
19-1031.00
Precision Agriculture Technicians
19-4012.01
Industrial Ecologists
19-2041.03
Microbiologists
19-1022.00
Agricultural Engineers
17-2021.00
Biologists
19-1029.04
Geoscientists, Except Hydrologists and Geographers
19-2042.00
Range Managers
19-1031.02
Hydrologists
19-2043.00
Environmental Scientists and Specialists, Including Health
19-2041.00
Agricultural Technicians
19-4012.00
Animal Scientists
19-1011.00

Frequently Asked Questions

Will AI replace Soil and Plant Scientists?

No, AI will not replace Soil and Plant Scientists entirely. With only a 48/100 AI impact score, this role faces partial automation over 5-10 years. The 16,600 professionals in this field will see their analytical and documentation tasks automated, but core research, field work, and strategic planning remain human-essential.

What AI tools are used in Soil and Plant Scientists roles?

Current tools include R with AI packages, IBM SPSS Statistics, ESRI ArcGIS with machine learning capabilities, and SAS for statistical analysis. Emerging tools include GPT-4 for report writing, computer vision for soil classification, and predictive analytics platforms for crop optimization.

What is the salary outlook for Soil and Plant Scientists with AI?

The current mean annual wage of $71,410 may increase for professionals who adapt to AI tools. Those who integrate AI capabilities into their workflow will likely command premium salaries, while those who resist automation may face stagnant wages as routine tasks become automated.

What skills should Soil and Plant Scientists develop for the AI era?

Focus on developing critical thinking (importance: 4/5), complex problem solving (3.88/5), and active learning (4/5) skills that AI cannot replicate. Additionally, learn to work with AI tools like R, SPSS, and GIS software to augment analytical capabilities while maintaining expertise in field research and stakeholder communication.

How many Soil and Plant Scientists jobs are there in the US?

There are currently 16,600 Soil and Plant Scientists employed in the US. While specific projected growth data is not available, the integration of AI tools will likely reshape rather than eliminate these positions, with demand shifting toward AI-augmented specialists.