Report of CGIAR’s Digital Transformation Accelerator side event–AI-powered innovation: Acceleration research for agri-food system transformation
CGIAR’s Digital Transformation Accelerator Side Event: Digital innovations for advancing agri-food systems research, held during Science Week 2025 showcased how artificial Intelligence (AI) is reshaping agri-food systems research, innovation, and advisory services, particularly in the Global South....
| Main Authors: | , |
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| Format: | Informe técnico |
| Language: | Inglés |
| Published: |
International Livestock Research Institute
2025
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| Online Access: | https://hdl.handle.net/10568/176498 |
| _version_ | 1855525007988359168 |
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| author | Ojanji, Wandera Dhulipala, Ram |
| author_browse | Dhulipala, Ram Ojanji, Wandera |
| author_facet | Ojanji, Wandera Dhulipala, Ram |
| author_sort | Ojanji, Wandera |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | CGIAR’s Digital Transformation Accelerator Side Event: Digital innovations for advancing agri-food systems research, held during Science Week 2025 showcased how artificial Intelligence (AI) is reshaping agri-food systems research, innovation, and advisory services, particularly in the Global South. Attended by over 250 participants both in person and online, the four-hour session highlighted frontier AI applications while addressing critical institutional, ethical, and localization challenges in scaling digital innovation.
Keynote addresses by Aisha Walcott-Bryant, head of Google Research Africa presented real-world applications of AI for climate resilience, including flood forecasting, field boundary detection, and hyper-local weather prediction.
These solutions underscored the transition from experimentation to wide-scale operational deployment.
Thematic sessions demonstrated AI’s versatility across the following agricultural domains:
• Generative AI for advisory services: The International Maize and Wheat Improvement Center (CIMMYT) and partners showcased how AI tools are being localized to provide multilingual, personalized, and voice-enabled farming advice. Innovative uses of large language models (LLMs), Interactive Voice Response (IVR) systems, and WhatsApp-based tools emphasized accessibility for low-literacy and digitally marginalized users.
• Earth observation and AI for climate adaptation: The University of Galway introduced tracking adaptation progress in agriculture and food security (TAPAS), a platform leveraging satellite data and machine learning to monitor adaptation outcomes, assess investment impacts, and guide climate resilience strategies.
• AI in genebank management: The International Rice Research Institute (IRRI) presented transformative use cases of AI in managing rice genetic resources, from automating seed phenotyping to enhancing genetic diversity analysis through image-based classification models and natural language interfaces.
• Artemis: AI-powered phenotyping: The Tanzania-based Artemis project was launched as a scalable, AIenabled
platform using smartphone-based digital phenotyping. The project combines frugal innovation,
interdisciplinary collaboration, and speech recognition to empower breeding programs and integrate farmer voices into research workflows.
• The Agricultural Information Exchange Platform (AIEP): A multi-organization initiative piloted AI-powered advisory tools tailored for smallholder farmers in Kenya and India. Co-designed with end users, the platform supports voice, SMS, and chatbot interfaces to deliver timely, localized, and gender-sensitive agricultural information.
Throughout the event, discussions emphasized the shift from proof-of-concept pilots to institutional readiness and sustainable models for AI adoption. Key takeaways included the need for interdisciplinary partnerships, participatory design, open-source data infrastructure, and responsible governance to ensure that AI contributes to equitable and impactful transformation of agri-food systems.
The event concluded with calls for broader collaboration across public, private, and research sectors to codevelop AI solutions that are inclusive, context-aware, and scalable. |
| format | Informe técnico |
| id | CGSpace176498 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | International Livestock Research Institute |
| publisherStr | International Livestock Research Institute |
| record_format | dspace |
| spelling | CGSpace1764982025-09-20T06:00:47Z Report of CGIAR’s Digital Transformation Accelerator side event–AI-powered innovation: Acceleration research for agri-food system transformation Ojanji, Wandera Dhulipala, Ram agrifood systems food systems digital innovation transformation artificial intelligence CGIAR’s Digital Transformation Accelerator Side Event: Digital innovations for advancing agri-food systems research, held during Science Week 2025 showcased how artificial Intelligence (AI) is reshaping agri-food systems research, innovation, and advisory services, particularly in the Global South. Attended by over 250 participants both in person and online, the four-hour session highlighted frontier AI applications while addressing critical institutional, ethical, and localization challenges in scaling digital innovation. Keynote addresses by Aisha Walcott-Bryant, head of Google Research Africa presented real-world applications of AI for climate resilience, including flood forecasting, field boundary detection, and hyper-local weather prediction. These solutions underscored the transition from experimentation to wide-scale operational deployment. Thematic sessions demonstrated AI’s versatility across the following agricultural domains: • Generative AI for advisory services: The International Maize and Wheat Improvement Center (CIMMYT) and partners showcased how AI tools are being localized to provide multilingual, personalized, and voice-enabled farming advice. Innovative uses of large language models (LLMs), Interactive Voice Response (IVR) systems, and WhatsApp-based tools emphasized accessibility for low-literacy and digitally marginalized users. • Earth observation and AI for climate adaptation: The University of Galway introduced tracking adaptation progress in agriculture and food security (TAPAS), a platform leveraging satellite data and machine learning to monitor adaptation outcomes, assess investment impacts, and guide climate resilience strategies. • AI in genebank management: The International Rice Research Institute (IRRI) presented transformative use cases of AI in managing rice genetic resources, from automating seed phenotyping to enhancing genetic diversity analysis through image-based classification models and natural language interfaces. • Artemis: AI-powered phenotyping: The Tanzania-based Artemis project was launched as a scalable, AIenabled platform using smartphone-based digital phenotyping. The project combines frugal innovation, interdisciplinary collaboration, and speech recognition to empower breeding programs and integrate farmer voices into research workflows. • The Agricultural Information Exchange Platform (AIEP): A multi-organization initiative piloted AI-powered advisory tools tailored for smallholder farmers in Kenya and India. Co-designed with end users, the platform supports voice, SMS, and chatbot interfaces to deliver timely, localized, and gender-sensitive agricultural information. Throughout the event, discussions emphasized the shift from proof-of-concept pilots to institutional readiness and sustainable models for AI adoption. Key takeaways included the need for interdisciplinary partnerships, participatory design, open-source data infrastructure, and responsible governance to ensure that AI contributes to equitable and impactful transformation of agri-food systems. The event concluded with calls for broader collaboration across public, private, and research sectors to codevelop AI solutions that are inclusive, context-aware, and scalable. 2025-04-30 2025-09-15T17:40:25Z 2025-09-15T17:40:25Z Report https://hdl.handle.net/10568/176498 en Open Access application/pdf International Livestock Research Institute Ojanji, W. and Dhulipala, R. 2025. Report of CGIAR’s Digital Transformation Accelerator side event–AI-powered innovation: Acceleration research for agri-food system transformation. Nairobi, Kenya: ILRI. |
| spellingShingle | agrifood systems food systems digital innovation transformation artificial intelligence Ojanji, Wandera Dhulipala, Ram Report of CGIAR’s Digital Transformation Accelerator side event–AI-powered innovation: Acceleration research for agri-food system transformation |
| title | Report of CGIAR’s Digital Transformation Accelerator side event–AI-powered innovation: Acceleration research for agri-food system transformation |
| title_full | Report of CGIAR’s Digital Transformation Accelerator side event–AI-powered innovation: Acceleration research for agri-food system transformation |
| title_fullStr | Report of CGIAR’s Digital Transformation Accelerator side event–AI-powered innovation: Acceleration research for agri-food system transformation |
| title_full_unstemmed | Report of CGIAR’s Digital Transformation Accelerator side event–AI-powered innovation: Acceleration research for agri-food system transformation |
| title_short | Report of CGIAR’s Digital Transformation Accelerator side event–AI-powered innovation: Acceleration research for agri-food system transformation |
| title_sort | report of cgiar s digital transformation accelerator side event ai powered innovation acceleration research for agri food system transformation |
| topic | agrifood systems food systems digital innovation transformation artificial intelligence |
| url | https://hdl.handle.net/10568/176498 |
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