Why the South?
Institutional Friction and the Spatial Reorganization of Data Center Infrastructure in the United States
- Wu, Shaoyuan
Global AI Governance and Policy Research Center, EPINOVA LLC
https://orcid.org/0009-0008-0660-8232
Description
This working paper explains why recent large-scale data center infrastructure expansion in the United States has increasingly clustered in the American South and selected interior regions. It advances a structural explanation centered on institutional feasibility, introducing a structural belt model and a three-axis framework of local institutional friction, utility buildability, and network interconnection to explain corridor-based hyperscale growth and its governance implications.
Abstract
Despite common assumptions that large-scale data center infrastructure should concentrate in coastal technology hubs, low-tax jurisdictions, or energy-abundant regions, recent expansion in the United States follows a different spatial pattern. In the AI and hyperscale era, new large-scale development has increasingly clustered in the American South and selected interior regions. This paper addresses this puzzle by advancing a structural explanation centered on institutional feasibility rather than factor endowments alone. The paper introduces a structural belt model and a three-axis framework—local institutional friction, utility buildability, and network interconnection—to explain why certain regions function as low-resistance infrastructure zones. It shows that data center expansion follows a logic of friction minimization across governance, permitting, and power delivery systems, producing contiguous corridors of growth rather than isolated point-optimal sites. This spatial reorganization carries important governance implications. Rapid infrastructure lock-in in low-friction regions can outpace the adaptation of regulatory and political oversight, generating infrastructure–governance asymmetries. The findings contribute to debates on AI compute governance, infrastructure planning, and the political economy of large-scale digital systems.
Files
| Name | Type | |
|---|---|---|
| Why the South.pdf Primary PDF file for EPINOVA Working Paper D–2026–02 | application/pdf | Download |
Keywords
- Infrastructure friction
- Data centers
- Institutional feasibility
- Governance
- Political economy
- Artificial intelligence
- Infrastructure lock-in
- Spatial reorganization
- hyperscale infrastructure
- AI compute governance
- utility buildability
- network interconnection
- local institutional friction
- Infrastructure Friction Boundary
- Growth Attractiveness Index
- Infrastructure–Governance Asymmetry Pressure Index
- American South
- Southeast United States
- subnational governance
- EPINOVA
Subjects
- Artificial intelligence governance
- Data center infrastructure
- Infrastructure governance
- Political economy
- Urban and regional planning
- Energy policy
- Utility regulation
- Technology governance
- Subnational governance
- Spatial analysis
- Public policy
- Institutional design
- Infrastructure lock-in
- AI compute infrastructure
Recommended citation
Wu, Shaoyuan. (2026). Why the South? Institutional Friction and the Spatial Reorganization of Data Center Infrastructure in the United States (EPINOVA Working Paper No. EPINOVA–WP–D–2026–02). Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.5281/zenodo.18572133. DOI: To be assigned after Crossref membership approval.
APA citation
Wu, S. (2026). Why the South? Institutional friction and the spatial reorganization of data center infrastructure in the United States (EPINOVA Working Paper No. EPINOVA–WP–D–2026–02). Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.5281/zenodo.18572133. DOI: To be assigned after Crossref membership approval.
Alternate identifiers
| Scheme | Identifier | Description |
|---|---|---|
| DOI | https://doi.org/10.5281/zenodo.18572133 | Zenodo DOI landing page |
| Local identifier | EPINOVA–WP–D–2026–02 | EPINOVA Working Paper D-Series publication number |
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References
- Ansell, C., Trondal, J., & Øgård, M. (2017). Turbulence and new institutionalism: Governance in times of turbulence. Governance, 30(1), 3–22. https://doi.org/10.1111/gove.12217
- Armond, C., & Manning, S. (2023). Governing hyperscale data centers: Energy, land, and regulatory politics. Energy Research & Social Science, 98, 102987. https://doi.org/10.1016/j.erss.2023.102987
- Crawford, K. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press.
- Graham, S., & Marvin, S. (2001). Splintering urbanism: Networked infrastructures, technological mobilities and the urban condition. Routledge.
- Henderson, J., Dicken, P., Hess, M., Coe, N., & Yeung, H. W.-C. (2020). Global production networks and the globalisation of data centres. Geoforum, 108, 1–13. https://doi.org/10.1016/j.geoforum.2019.10.012
- International Energy Agency. (2023). Data centres and data transmission networks. IEA. https://www.iea.org/reports/data-centres-and-data-transmission-networks
- Pierson, P. (2000). Increasing returns, path dependence, and the study of politics. American Political Science Review, 94(2), 251–267. https://doi.org/10.2307/2586011
- Unruh, G. C. (2000). Understanding carbon lock-in. Energy Policy, 28(12), 817–830. https://doi.org/10.1016/S0301-4215(00)00070-7
