AI Adoption in NGOs: A Systematic Literature Review

Artificial Intelligence (AI) has the potential to significantly improve how Non-Governmental Organizations (NGOs) utilize their limited resources for societal benefits, but evidence about how NGOs adopt AI remains scattered. In this study, we systematically investigate the types of AI adoption use cases in NGOs and identify common challenges and solutions, contextualized by organizational size and geographic context. We review primary literature on AI adoption in NGOs related to social impact between 2020 and August 2025 in English. Following the PRISMA protocol, two independent reviewers conduct study selection, resulting in a final literature body of 65 studies. Leveraging a thematic and narrative approach, we identify six AI use case categories in NGOs – Engagement, Creativity, Decision-Making, Prediction, Management, and Optimization – and extract common challenges and solutions within the Technology–Organization–Environment (TOE) framework. By integrating our findings, this review provides a novel understanding of AI adoption in NGOs, linking specific use cases and challenges to organizational and environmental factors. Our results demonstrate that while AI is promising, adoption among NGOs remains uneven and biased toward larger organizations. Nevertheless, following a roadmap grounded in literature can help NGOs overcome initial barriers to AI adoption, which may ultimately improve effectiveness, engagement, and social impact.