<![CDATA[Despite growing scholarly attention to the political economy of artificial intelligence (AI) infrastructure, no study has yet empirically tested whether the expansion of AI data centers in a specific Global South location reproduces structural dependency patterns using an integrated, operational framework derived from World-Systems Theory, this is the gap the present study addresses. Focusing on São Paulo, Brazil (2022-2025), the research operationalizes three constructs from Immanuel Wallerstein's World-Systems Theory; (1) surplus value extraction, (2) capital accumulation, and (3) systemic marginalization of peripheral economies, as coding indicators applied through qualitative document and content analysis. Data were drawn from government reports, industry publications, international organization data, and peer-reviewed literature, then systematically coded against the three indicators to trace patterns of ownership, value distribution, and resource allocation. The findings show an asymmetrical core-periphery relationship: Brazil supplies land, energy, water, and fiscal incentives, while the highest value, arising from technological control, platform ownership, and capital accumulation, remains concentrated among core-country technology firms, with Brazilian policy reinforcing foreign firms' positions without generating commensurate technology transfer. By bridging classical dependency theory with contemporary digital-economy analysis, this study offers the first empirical operationalization of World-Systems Theory in the AI infrastructure context, contributing a replicable analytical framework to international political economy and AI governance scholarship.]]>
Copyrights © 2026
