PAIE Scholars Program 2026

The PAIE Scholars Program supports researchers in low- and middle-income countries in Africa and Asia to develop rigorous, policy-relevant evaluations of artificial intelligence applications for social good and poverty reduction. It is run through Project AI Evidence at the Abdul Latif Jameel Poverty Action Lab (J-PAL). Selected scholars will complete structured training in randomised evaluation and the evaluation of AI-enabled interventions. The programme includes selected J-PAL 102x modules, AI evaluation resources, live online workshops and a PAIE-administered proctored assessment. The initial training is expected to run from November 2026 to January 2027, with an estimated commitment of four to ten hours per week. Scholars who complete their assigned training, pass the assessment and submit an acceptable revised concept note will receive US$1,000. A competitive subset may then receive up to US$10,000 for proposal development and travel, alongside possible research mentorship. Eligible scholars who progress to the pilot stage may compete for up to US$75,000 in pilot funding. Applicants must submit a CV, one to three research examples, brief statements on their research and quantitative experience, and a working concept note for an AI-enabled intervention that could lead to a randomised evaluation. A fully developed project and implementing partner are not required at the initial application stage. Progression between stages is competitive. Selection for the first cohort does not guarantee proposal-development support, mentorship or pilot funding. The proposal-development grant cannot fund human-subject research or data collection from research participants. Applications close on 16 October 2026 at 12:00 ET (16:00 UTC).

Applicants must be resident scholars based in a World Bank-classified low- or middle-income country in Africa or Asia. They must have completed a PhD in economics or another relevant empirical discipline, and their primary professional affiliation must be with a university in an eligible country. Applicants also need advanced quantitative training, such as statistics, econometrics, causal inference, experimental methods or machine learning; an interest in evaluating the social or economic effects of AI-enabled interventions; sufficient English proficiency; and availability to complete all programme requirements. Applicants do not need an existing relationship with a J-PAL-affiliated researcher, a fully developed project or an implementing partner when applying.