Artificial Intelligence (AI) is rapidly transforming agri-food systems, accelerating research and innovation to address some of the most pressing challenges in agriculture. This four-hour Side Event will bring together experts and pioneering projects to explore how AI is enhancing research, decision-making, and impact in agri-food systems. The keynote session will set the stage with a high-level overview of the current status of AI in agri-food system research and innovation. Subsequent sessions will showcase key applications, including the use of generative AI to strengthen agricultural advisory services for small-scale producers, AI-powered Earth observation analytics for climate adaptation and natural resource management, and digital phenotyping with AI to accelerate public breeding efforts in the Global South. Together, these sessions will highlight how AI-powered tools and approaches are revolutionizing agri-food systems research and development, creating new opportunities for scalable and impactful solutions.
As generative AI technology rapidly advancing and increasingly accessible, a critical question has emerged in agriculture: How can we harness this powerful technology to strengthen agricultural advisory services for small-scale producers in the Global South? This session will examine practical implementations, emerging frameworks, and strategic opportunities for deploying AI-powered advisory solutions in resource-constrained farming environments. Through case studies and expert discussions, this session will showcase pilot projects, their lessons-learned, and discuss how generative AI can enhance existing advisory systems while addressing accessibility, local context, and ethical use.
Andrea Gardeazabal (CIMMYT)
Jawoo Koo (IFPRI)
Satish Nagaraji (CIMMYT)
The Agriculture Information Exchange Platform (AIEP) is an initiative aimed at bridging the information access gap for low-literacy, low-digital skill smallholder farmers by developing open-source, AI-powered, and gender-sensitive digital advisory tools. Four cohorts (Digital Green, DeHaat with Dalberg, IRRI with CIMMYT, and Viamo) have collaborated to co-design and test AI-powered Minimum Viable Products (MVPs) in Bihar (India) and Kenya, integrating local language interfaces, personalized advisory content, and omni-channel delivery platforms such as WhatsApp, IVR, and SMS. In this session, the AIEP team will present key achievements, share learnings from co-creation and end-user testing, and outline opportunities for scaling this modular, interoperable architecture to improve the livelihoods of underserved farming communities.
Moderator: Kirti Pandey (Open Agri Net)
Christian Merz (GIZ)
Nereah Okanga (Digital Green)
Nancy Winder (Viamo)
Mayank Jain (Sumarth)
Prakashan Chellattan Veettil (IRRI)
Joe Munene (Opportunity International)
Melvin Mutai (Safaricom)
Advancements in AI and Earth observation are revolutionizing how we monitor and manage critical resources in agri-food systems. From tracking water availability and reuse to monitoring biomass changes for climate resilience, AI-powered Earth observation tools help researchers generate new insights at multiple scale from global assessments to farm-level interventions. This presentation will focus on how AI-driven analytics, combined with satellite remote sensing, can enhance decision-making for climate adaptation, agricultural productivity and food systems resilience.
Charles Spillane (University of Galway)
Jemima O’Farrell (University of Galway)
Genebanks are a key resource to conserve, manage and access crop diversity for coping with climate change, yet they are largely underutilized mainly due to lack of information on usefulness of the accessions. By application of AI-based methodologies CGIAR fast-tracks the utilization of genebanks, reducing cost and time to 1/16th and 1/10th, respectively, of the “business as usual” approach. This presentation will increase awareness of this approach.
Venuprasad Ramaiah (IRRI)
This session will showcase the Tanzania-based Artemis project, an AI-powered digital phenotyping platform designed to significantly enhance public breeding efforts in the Global South. The Artemis project utilizes advanced machine learning algorithms to analyze crop images captured by smartphones, eliminating the need for manual visual counting and data recording. This session will highlight the project's transition beyond a project, demonstrating potential for widespread adoption and impact. The event will serve as the launch of evolving Artemis beyond a project, presenting the business model and value proposition to the global agricultural research community and opening up for feedback and collaboration.
David Guerena (Alliance Bioversity-CIAT)
Lennart Woltering (Alliance Bioversity-CIAT)
Violet Lasdun (Alliance Bioversity-CIAT)
Stephen Mutuvi (Alliance Bioversity-CIAT)
Juan Lucas Restrepo (Alliance of Bioversity and CIAT)
Gustavo Teixeira (CIMMYT)
