From Field Data to Policy Decisions: Using AI to Turn Evaluations into Actionable Insights in Education and Youth Employment

Across West Africa, evaluators and NGOs collect rich quantitative and qualitative data on program in education, youth employment, agriculture, and climate, yet decision-makers often receive these insights too late, in formats that are difficult to use. At the same time, AI tools now offer powerful options for cleaning datasets, identifying patterns, and generating tailored summaries for different audiences but their use raises questions of quality, ethics, and trust. This session will walk through a concrete data-to-decision pathway, using examples from impact evaluations and mixed-methods studies in Benin, to illustrate where AI can add real value and where human judgment remains irreplaceable.
We will demonstrate how AI can support instrument design, field-data processing, exploratory analysis, and the production of differentiated products: technical reports for researchers, policy briefs for ministries, and accessible evidence stories for NGOs and communities. We will also discuss safeguards to avoid misleading findings, protect sensitive data, and maintain the integrity of counterfactual and quasi-experimental designs when using AI-assisted analytics. The session is designed for researchers, public officials, and civil society organizations who want to move beyond generic discussions of AI and see, step-by-step, how it can be embedded in evaluation practice to produce timely, credible, and policy-relevant evidence