Working paper examines data center expansion in the South, suggesting infrastructure governance challenges.
This working paper examines the spatial reorganization of large-scale data center infrastructure in the United States in the AI and hyperscale computing era. While conventional explanations emphasize coastal agglomeration, energy costs, or fiscal incentives, recent expansion has increasingly concentrated in the American South and selected interior regions. The paper advances a structural explanation centered on institutional feasibility. It introduces a three-axis analytical framework capturing local institutional friction, utility buildability, and network interconnection, and develops the concept of an Infrastructure Friction Boundary (IFB) to describe a dynamic phase boundary separating regions capable of rapid hyperscale deployment from those constrained by governance or delivery limits. Through comparative state-level illustrations, the analysis shows that data center expansion follows contiguous low-friction corridors rather than isolated point-optimal sites. The findings highlight an emerging infrastructure–governance asymmetry in which deployment speed outpaces the adaptive capacity of local regulatory and political institutions. The paper contributes to debates on digital infrastructure, governance, and AI compute by linking infrastructure geography to institutional capacity under conditions of scale and irreversibility.
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Shaoyuan Wu (2026) studied this question.
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