CGIAR: Science for Humanity's Greatest Challenges

CGIAR is the world’s largest global agricultural innovation network. We provide evidence to policy makers, innovation to partners, and new tools to harness the economic, environmental and nutritional power of agriculture. Our research generates international public goods that support sustainable agriculture, food security, nutrition, climate resilience, and inclusive development, particularly for low and middle income countries. CGIAR operates through a network of international research centers including Africa Rice Center, International Center for Agricultural Research in the Dry Areas (ICARDA), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), International Food Policy Research Institute (IFPRI), International Institute of Tropical Agriculture (IITA), International Livestock Research Institute (ILRI), International Maize and Wheat Improvement Center (CIMMYT), International Potato Center (CIP), International Rice Research Institute (IRRI), International Water Management Institute (IWMI), The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), The Center for International Forestry Research and World Agroforestry (CIFOR-ICRAF), and WorldFish.

Advancing Open, Responsible AI for Agrifood Systems and Global Development

CGIAR offers the AI community open research corpus, data, models, tools, and domain expertise in agrifood systems.

1. Open Research Corpus for AI & LLMs

CGIAR publishes a large and growing body of open access research outputs, including:

• Peer-reviewed journal articles
• Working papers, reports, and policy briefs
• Metadata, abstracts, and structured research outputs

Unless otherwise indicated, these materials are made available under Creative Commons Attribution 4.0 International (CC BY 4.0) and are intended to function as international public goods. Leveraging these materials, CGIAR is developing a CGIAR Open Research Corpus designed for machine readability and large-scale reuse, including:

• Clean, text-extractable full text
• Rich, standardized metadata
• Persistent identifiers (e.g. HandleIDs and DOIs)
• Clear, machine-readable licensing

This corpus is intended to support analytical uses such as text and data mining, information retrieval, and the development and evaluation of applying AI and large language models in agrifood systems.

2. Data Assets, Models, and Tools

Beyond publications, CGIAR produces and curates:

• High-value agrifood, climate, nutrition, and socioeconomic datasets
• Dynamic agrifood system models
• Open-source code, APIs, and analytical tools
• Geospatial and remote-sensing data and analysis products

These assets are managed under the FAIR (Findable, Accessible, Interoperable, Reusable) principles and, where possible, released under permissive, machine-readable licenses.

3. Domain Expertise for Responsible AI

CGIAR brings deep, interdisciplinary expertise that is critical for responsible AI development, including:

• Agrifood systems science
• Climate change adaptation and mitigation
• Food security and nutrition
• Poverty, livelihoods, and gender
• Policy analysis and impact evaluation

We welcome engagement with AI developers, researchers, and institutions seeking to ground models and applications in real-world development contexts, particularly in the Global South.

AI & LLM Use Statement

CGIAR makes its research outputs available as international public goods in accordance with its CGIAR Open and FAIR Data Assets Policy. Unless otherwise indicated, CGIAR publications and associated materials are made available under the Creative Commons Attribution 4.0 International license (CC BY 4.0). This license permits use, sharing, adaptation, and reproduction in any medium or format, provided appropriate credit is given to the original authors and CGIAR. Consistent with the terms of CC BY 4.0, CGIAR does not restrict the use of its open access publications for lawful analytical purposes, including text and data mining and computational analysis. Such uses may include research, indexing, information retrieval, and the development and evaluation of automated systems, provided applicable laws, ethical standards, and license requirements are respected. Where materials are subject to third-party rights, confidentiality, or ethical restrictions, such limitations are indicated in accompanying metadata and take precedence.