Note on the Four Lenses of AI Adoption in Developing Economies

By Romi Bhatia, Federico Antoni, Stephen Ciesinski
2025 | Case No. E933 | Length 13 pgs.
Entrepreneurship

Artificial intelligence is diffusing across developing economies along a path distinct from that of the United States and China. Rather than being driven primarily by hyperscale infrastructure investments or geopolitical competition, AI adoption in the Global South is unfolding in a decentralized, mobile-first, and bottom-up manner. From Brazilian edtech platforms such as Teachy.AI to African language model developers like Vambo AI and WhatsApp-native commerce platforms such as Lua, entrepreneurs are embedding generative AI into everyday workflows, often leapfrogging legacy infrastructure constraints. This Academic Note introduces a structured framework, the Four Lenses of AI Adoption: Adoption, Data, Economic, and Ecosystem, to analyze how AI creates value in developing economies.

By synthesizing case examples from Latin America, Africa, South Asia, and the Middle East, the Note highlights how AI can serve as a catalyst for technological leapfrogging, while also exposing structural bottlenecks in capital access, regulatory clarity, and data governance.

Learning Objective

This Note equips students and practitioners with an analytical toolkit to assess AI ventures beyond hype cycles, enabling them to evaluate where defensible advantages may emerge, how business models must adapt to fragmented markets, and what ecosystem conditions are necessary for AI to scale sustainably across the Global South. It further challenges students to analyze the interaction between digital public infrastructure, private capital, and entrepreneurial strategy in shaping AI diffusion across emerging markets. Students are challenged to compare adoption pathways across regions, assess the risks of infrastructure and investment gaps, and formulate context-sensitive strategies for building and financing AI ventures in resource-constrained environments.
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