News Overview

As climate pressures intensify across food, land, and water systems, AI presents an opportunity to keep pace for agricultural research. But only if institutions are prepared to change with it. Here, we identify four priorities to make this happen.

A consultation workshop in Vietnam highlighted how digitalizing agricultural mechanization and deploying suitability maps can optimize machinery investment, connect farmers with service providers, and build a unified database to drive the Mekong Delta’s low-emission, modern, and sustainable rice production goals.

CGIAR’s AI Hub transforms decades of cutting-edge agricultural research into practical AI products, placing them directly in the hands of smallholder farmers, policymakers, and researchers.

By building an AI-powered “digital brain” that analyzes field data from across the globe, CGIAR and Google aim to improve breeding efficiency, standardize agricultural data, and deliver better crop varieties faster, while also strengthening food security monitoring in vulnerable regions.

The International Food Policy Research Institute (IFPRI), with support from the CGIAR Accelerator on Digital Transformation, and Farm Radio International (FRI) have partnered to develop Longa—an artificial intelligence (AI) powered speech recognition tool designed to strengthen agricultural communication and inclusivity across sub-Saharan Africa.

Through AICCRA and CGIAR support, Kenya Agricultural Observatory Platform (KAOP) has been enhanced with a national AgData Hub integrating diverse data sources (climate, soil, market, crop info) to provide advisories to over 700,000 farmers to boost productivity and strengthen resilience.