Compressed professionalization in informal economies: a socio-technical analysis of youth-led artificial intelligence adoption in the Democratic Republic of the Congo

Artificial intelligence (AI) is increasingly shaping development trajectories across the Global South, yet limited attention has been paid to how AI is appropriated within highly informal and institutionally fragile economies. This article advances a conceptually driven, theory-building analysis supported by qualitative field insights used as illustrative grounding rather than for statistical generalization. Drawing on 125 semi-structured interviews conducted in Kinshasa, Lubumbashi, and Goma, and integrating Information and Communication Technologies for Development (ICT4D), socio-technical systems theory, and the capability approach, the study examines how infrastructural constraints, fragmented governance, and uneven skill ecosystems interact with youth-driven innovation to shape AI adoption in the Democratic Republic of the Congo (DRC). The article introduces compressed professionalization, defined as the accelerated acquisition and immediate market enactment of professional-level digital capabilities outside formal institutional pathways. Empirical observations show that youth mobilize AI tools for translation, content creation, customer engagement, and micro-entrepreneurial activities, enabling partial and situational approximation of selected formal-sector practices. The analysis further conceptualizes AI as a conditional capability amplifier, expanding agency while producing uneven inclusion shaped by disparities in connectivity, skills, and infrastructure. Rather than following policy-led or infrastructure-first trajectories, AI adoption emerges through hybrid socio-technical interactions between bottom-up youth innovation and weakly coordinated institutional frameworks. The article concludes by proposing a Strategic Action Framework to support more inclusive and context-responsive AI ecosystems. While grounded in the DRC, the findings offer broader insights into AI adoption dynamics across informal economies in Sub-Saharan Africa and beyond.