As large language models (LLMs) begin to influence how evidence is generated, synthesized, and communicated, new opportunities are emerging for policymakers and analysts working in food systems. This webinar explores how generative AI tools can support policy design, analysis, and dialogue—bridging technical modeling and real-world decision-making. 

Askar Mukashov, Research Fellow at IFPRI, will introduce RIAPA-AI, an extension of the Rural Investment and Policy Analysis (RIAPA) framework that integrates LLMs to support interactive exploration of policy scenarios. He will demonstrate how the tool enhances accessibility and responsiveness in economic modeling, enabling users to query and visualize model outputs in real time. 

Jonathan Mockshell, Senior Scientist at the Alliance of Bioversity International and CIAT, will present PEPA-AI, a generative AI platform that synthesizes research evidence and policy narratives for informing agrifood policy decisions and scaling innovations. Drawing from CGIAR’s global research and policymaking experiences, he will discuss how LLMs can help interpret diverse data sources, identify insights, and foster more inclusive and transparent policy processes. 

Together, the speakers will examine how AI-powered tools like RIAPA-AI and PEPA-AI are reshaping evidence generation for policy, highlighting both their promise and the ethical, methodological, and institutional questions they raise for the future of food systems governance. 

Speakers

• Askar Mukashov, Research Fellow, IFPRI
• Jonathan Mockshell, Senior Scientist, Alliance of Bioversity International and CIAT 

Discussant  

• Clemens Breisinger, Director of the CGIAR Policy Innovations Program

Moderator

• Eliot Jones-Garcia, Senior Research Analyst, IFPRI; PhD Candidate, Wageningen University