Global South AI adoption patterns reveal practical resource efficiency models

Utrecht University research shows how necessity-driven AI implementations in Global South countries—like India’s low-cost digital infrastructure and Chinese micro-dramas—could improve resource efficie

Payal Arora’s 2026 analysis of AI adoption patterns identifies a divergence in how Western and Global South nations approach AI. The research observes that 83% of Chinese respondents, 80% of Indonesian respondents, and 77% of Thai respondents in 2025 surveys viewed AI products as net beneficial, while 17% of U.S. adults anticipated AI’s positive impact on the country over the next two decades. These patterns emerge alongside practical examples: India’s India Stack—a public digital infrastructure for identity and payments built with limited resources—and the EU’s EuroStack response to it. The analysis also highlights low-cost AI applications like a Chinese micro-drama film created for under $500 by a rural wedding photographer that gained tens of millions of views, and Anghami’s Middle Eastern music platform that pays musicians per stream rather than after thresholds. Crucially, 90% of the world’s young people reside outside Western nations, suggesting these models could scale resource efficiency for basic needs like digital access and creative expression without Western infrastructure demands. This contrasts with Western AI adoption patterns that often prioritize high-cost solutions. The movement toward necessity-driven AI—where tools solve immediate needs rather than speculative futures—could free up resources for other basic needs by reducing digital friction. What to watch: Whether Global South-led AI models accelerate adoption in resource-constrained settings before Western frameworks dominate. Caveats: All statistics are from specific 2025 surveys; the author presents these as observed patterns, not causal relationships; 'Global South' refers to countries outside Western nations in this context.

Source: Rest of World