New World Bank Report Examines AI Applications In Global Agrifood Systems
28 November 2025, Philippines: A just-released landmark report by the World Bank explores how AI, or artificial intelligence, is dynamically transforming agrifood systems around the world. Titled Harnessing Artificial Intelligence for Agricultural Transformation and published by the Agriculture and Food Global Department of the World Bank, in collaboration with the Gates Foundation, Microsoft, and other partners, the report provides a development-oriented overview of the high-impact deployment of AI in agrifood systems, with a focus on Low and Middle-Income Countries (LMICs), and provides a roadmap of applications, requirements, and investment priorities focusing on ethical, inclusive, and scalable use.
Unlocking genebanks through machine learning
IRRI is cited as a leading case study in the report for its groundbreaking application of AI in genebank utilization, particularly for the International Rice Genebank (IRG), the world’s largest repository of rice genetic diversity.
The initiative addressed a long-standing challenge of utilizing plant genetic resources, where traditional or manual screening methods of germplasm are slow, expensive, and tedious. This resulted in the active use of only around five percent of the 132,000 rice samples conserved in the genebank.
To overcome these constraints, IRRI developed a computer vision and machine learning system that analyzes seed images to accurately identify, classify, and group germplasm accessions based on key traits and characteristics. During the first year of the pilot project, the AI model enabled the screening of approximately 60,000 accessions in just one season, over three times more than the preceding five decades.
This highly accelerated process is expected to complete the screening of the whole collection in about two years and at one-sixth of the cost of traditional methods. This scalable system also offers a global template for genebank utilization, significantly boosting the use of conserved genetic resources and contributing to the achievement of the UN Sustainable Development Goals.
In this video in support of this initiative, IRRI Director General Dr. Yvonne Pinto talks about how AI fits into the institute’s five-year strategy.
Helping farmers plant smarter
Beyond scientific discovery, IRRI is also leveraging AI to improve agricultural extension and farm management through digital decision-support tools.
Rice Crop Manager (RCM), an IRRI digital app deployed in various countries including the Philippines, India, and Bangladesh, provides farmers with personalized recommendations on fertilizer types, quantities, and application timings based on farmers’ responses to a set of agronomic questions. IRRI is actively integrating AI and machine learning into RCM to enhance its accuracy and user experience, thereby reducing the number of required farmer inputs by leveraging supplementary data sources such as satellite imagery, soil databases, and historical crop performance. Accessible through smartphones, computers, and extension services, RCM use has been proven to help farmers increase yields, optimize costs, and boost livelihoods.
Similarly, IRRI is part of the DynAG platform within the Agriculture Information Exchange Platform (AIEP) initiative. Available via text message, voice chatbots, or mobile apps in India and Kenya, the platform utilizes Generative AI and Large Language Models to deliver customized farming advice in local languages for a variety of crops, including rice, wheat, and maize.
The future of AI in agriculture
The World Bank report underscores the transformative potential of AI across agriculture. Through its innovative uses of AI, IRRI is helping accelerate the pace of scientific discovery and empowering farmers with smarter, more sustainable practices. As AI continues to evolve, collaboration and innovation across research institutions, governments, and technology partners will be crucial in unlocking AI’s future potential in agriculture around the world.
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