At the ACS Fall 2025 meeting, a joint Agrochemicals (AGRO) and Chemical Information (CINF) division symposium convened international experts to provide insights into the opportunities and challenges of integrating artificial intelligence (AI) and machine learning (ML) in agricultural science.
AI and ML are transforming agriculture by enabling predictive modeling for crop yields and pesticide residues, remote sensing and precision agriculture, automated phenotyping, decision support systems, and supply chain optimization.
These applications are supported by frameworks such as the FAIR data principles, (1) DAMA-DMBOK for data management, (2) and widely adopted machine learning libraries and platforms (TensorFlow, PyTorch, and Scikit-learn).
Despite significant advancements in AI and ML, their adoption, particularly in the regulatory space, relies not only on innovation but also on building trust through robust validation, transparent data practices, and reproducible workflows. This trust is established by implementing practical, systems-based strategies that include rigorous procedures, clear documentation, harmonized data management, and standardized methods.
Together, these best practices form the foundation for scientific confidence, societal acceptance, and a pathway for regulatory integration across the following areas.
- Data Curation and Infrastructure
- AI and ML in Product Discovery
- AI and ML in Product Development
- Emerging Technologies and Future Directions
Acknowledgments
The authors gratefully acknowledge the speakers, presenters, and panelists whose work and insights shaped the content of this work, including Yannick Djoumbou (Corteva Agriscience), Wentao Guo (Atombeat Inc.), Edward Chikwana (Corteva Agriscience), Kushal Doddakula (Creme Global), Wenlin Chen (Syngenta Crop Science), Hannah Rubin (Stone Environmental), Tamsin Mansley (Optibrium Ltd.), Denis Fourches (Oerth Bio), and Anju Yadav (The University of Texas at El Paso), and thank them for their contributions to the joint AGRO CINF symposium, “Agricultural Transformations with AI and ML: Collaboration, Innovation, and Data-Driven Insights”, held during the Fall ACS Meeting on August 19, 2025, in Washington, DC.
Download publication >>
