The ability to anticipate and prevent hunger crises is facing growing challenges due to disruptions in key data and early warning systems. Many traditional tools used by humanitarian agencies and governments to monitor food insecurity have experienced reduced capacity, limiting the availability of timely and reliable data. As a result, food crisis forecasting systems that previously provided early alerts are now under significant strain, and essential data streams are becoming increasingly scarce.
To help address this gap, artificial intelligence is emerging as a promising tool. With support from Google.org, researchers at International Food Policy Research Institue and other organizations under the "Accelerator on Digital Transformation" project is advancing the use of AI in agricultural research and food security monitoring. A core component of this initiative is the development of an AI-Driven Food Security Monitoring and Predictive Model. This model uses high-frequency datasets and machine learning algorithms to assess and forecast food crisis risks across 60 countries. The project also includes an interactive online dashboard, updated bi-monthly, to make these assessments accessible to decision-makers and practitioners. Leveraging CGIAR’s global research network, this initiative aims to deliver more accurate, timely, and cost-effective early warning tools, particularly in data-scarce and high-risk regions.
Devex Artice: As famine data dries up, can AI step in?
As traditional famine early warning systems face data shortages, IFPRI researchers have developed an AI model to help fill the gap. Trained on over 13,000 subnational observations from 38 countries, the model forecasts crisis-level food insecurity using secondary data such as prices, weather, and conflict events. It can predict Integrated Food Security Phase Classification (IPC) levels up to a year in advance and has shown promising accuracy, even outperforming established systems in some regions. IFPRI emphasizes the model complements—not replaces—field data, offering a valuable tool for anticipatory action where timely, ground-based assessments are limited or unavailable.
Control Panel for Risk Monitoring
The control panel for real-time monitoring of risk factors is an innovative tool that brings together information on various drivers of food crises, including conflict and climate-related shocks.
Food Price Shocks Tool
The Food Security Portal's Price Shocks Tool provides an interactive way to explore the impact of price changes on poverty. When you set hypothetical price shock(s) using the tool, net impacts of selected price changes are generated per household and the impact on poverty is automatically calculated accordingly.