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Conference contributions 1
A COMPARATIVE ANALYSIS OF AI STARTUP ECOSYSTEM FUNDING DISPARITIES BETWEEN THE GLOBAL SOUTH AND GLOBAL NORTH
The rapid growth of investment in artificial intelligence (AI) has created a highly uneven global funding landscape, with capital concentrated largely in a small number of high-income economies. Despite increasing interest in AI's potential contribution to development, comparatively little is known about how AI investment is distributed across the Global South. This paper presents a secondary data analysis of funding disparities within AI startup ecosystems in Sub-Saharan Africa, Latin America and Southeast Asia, benchmarked against investment patterns in OECD member states, which are used here as a proxy for high-income innovation economies. Data were drawn from publicly available venture capital datasets, harmonised to United States dollars and deduplicated across sources. The findings reveal significant inequalities in AI investment across regions. As of mid-2025, 159 AI startups in Sub-Saharan Africa had collectively raised US$803.2 million in external funding between 2020 and mid-2025. The analysis also highlights disparities in funding concentration, sectoral focus and investment stage progression. In Sub-Saharan Africa, more than 55% of AI startup activity is concentrated in fintech, talent technology and education, while investment in firms developing foundational AI technologies remains limited. Similar patterns of application-layer concentration and pre-seed stage dominance are evident in Latin America and Southeast Asia. Drawing on decolonial AI theory, this paper argues that these disparities reflect broader patterns of structural exclusion within the global innovation economy. The study concludes by outlining policy recommendations to strengthen Global South participation in AI development through targeted investment and improved access to AI infrastructure.