Anjali Kaur
Next week’s World Bank and International Monetary Fund (IMF) meetings will focus on rebuilding economic resilience in a fragile global economy. Yet amid these discussions in Washington, one issue risks being overlooked : The AI infrastructure and governance frameworks being built right now will shape development trajectories for decades. Whether that transformation is designed with the Global South or merely delivered to it will depend on decisions being made now on infrastructure, governance, and priorities.
AI is not just technology, it’s infrastructure. It depends on compute clusters, energy grids, and network connectivity—assets rooted in specific geographies that determine where value is created and risks accumulate.
Treating the Global South as a unified category obscures more than it reveals. China has invested heavily in building domestic AI capacity—from chips to cloud platforms. India generates roughly one-fifth of the world’s data but holds only about 3 percent of global data center capacity; it is data rich but infrastructure poor.
These disparities will determine who captures value from AI and who gets left behind. The IMF warns that AI could exacerbate cross-country income inequality, with growth impacts in advanced economies potentially more than double those in low-income countries. South Asia alone has nearly 100,000 young people entering the labor market daily, with almost half the region’s 1.8 billion population under age 24. That demographic momentum could be a dividend or a disaster. Without compute infrastructure and workforce transition strategies, AI may erode the very labor advantages that once underpinned growth.
The India-hosted AI Impact Summit in 2026 will test whether the international system can address these dynamics. Success depends on three issues: infrastructure access, governance influence, and local adaptation.
Infrastructure: Access as a Foundation, Not an Afterthought
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