This study examines how financial intermediaries integrate artificial intelligence (AI) to enable effective and sustained financial inclusion in Global South countries, and how collaboration between government agencies and financial intermediaries shapes the design and governance of AI-enabled inclusion systems.
The study adopts a qualitative multiple-case research design involving four financial intermediaries in a Global South context, selected to provide theoretically relevant variation in AI-enabled inclusion pathways. Data were collected from two main sources: semi-structured in-depth interviews with senior practitioners and experts across the cases, and archival documents including operational, risk, compliance, and governance materials.
The findings indicate that AI supports effective and sustained financial inclusion only when it is integrated as part of a socio-technical system, rather than deployed as a standalone automation solution. Inclusion outcomes are shaped by the alignment between organisational arrangements, technical design, operational practices, and governance processes. The analysis further shows that government–intermediary collaboration functions as a constitutive design and governance mechanism, translating policy priorities into operational constraints and accountability routines, while also creating risks of exclusionary scaling and expanded data use.
This study extends existing literature on AI and financial inclusion by shifting attention from access expansion to sustained inclusion as a socio-technical and governance outcome. It also advances STS-based AI research by integrating collaborative governance as a core analytical dimension, offering a reciprocal framework for understanding how policy strategy, organisational practice, and technical systems co-shape AI-enabled inclusion in Global South contexts.
