Since its start in 2019, the Challenge Fund for Youth Employment (CFYE or ‘The Fund’) has generated vast amounts of data, from job outcome numbers and implementing partner narratives, to youth surveys and focus group discussions. Yet the capacity to analyse and connect these varied data streams rarely keeps pace with the volume collected.
This gap limits what we can learn, how quickly we can adapt, and how effectively we can reach our goal of connecting 230, 000 young women and men with decent employment opportunities.
Artificial Intelligence (AI) offers a practical way to close that gap. CFYE became an early adopter of AI for programme learning, using it not to replace human judgement, but to expand what the team can learn across varied sources and contexts. Through pilots in several learning workstreams, including a Pathways to Employment (PTE) study, implementing partner Theory of Change (TOC) reviews, and gender research, CFYE developed approaches that are replicable, rigorous, and grounded in the practical realities of working with programme data.
This brief shares key insights, practical challenges, and actionable guidance for implementers and practitioners considering AI-enabled learning in their own programmes.
