AI Hyper-Scaling Digital Inequality
IEEE Spectrum AI Danica Radovanović
Artificial intelligence is concentrating computational power and decision-making authority in a few wealthy countries and firms, while most nations remain primarily consumers rather than creators of AI systems. The United States hosts over 5,000 data centers and accounted for 87 percent of global cloud computing exports in 2023, while skills gaps persist with only 36 percent of tertiary-educated workers versus 18 percent of those with upper secondary education engaging in AI training. Countries like Indonesia and South Africa are developing localized AI approaches, but without broader participation in AI governance and design, most nations risk losing opportunities to build innovation ecosystems and ensure their languages and priorities shape global AI systems.
Why it matters
Artificial intelligence is rapidly becoming part of everyday infrastructure–in some places. It helps write emails and software code, filters job applications, powers recommendation systems, and is increasingly being integrated into education, healthcare, finance, and public administration. Industry leaders talk about “AI for everyone,” while governments rush to publish national AI strategies and build sovereign compute.Yet over the past decade, working on digital inclusion and digital literacy projects in regions from Europe to sub-Saharan Africa and Southeast Asia, I’ve seen the same pattern repeat: each new wave of “transformative” technology lands on a landscape already stratified by connectivity, skills, and institutional capacity. The current AI wave is no exception. If anything, it amplifies those underlying fractures.Still, some countries areexploring ways of participating in AI development without directly replicating the frontier model race dominated by the United States and C
