Published 2026-02-02 | Version v1.0
Working PaperOpenPublished

When AI Infrastructure Is Optional but Governance Lock-In Is Not

An AI-SNI Local Governance Diagnostic of the Temple (GA) Data Center Proposal

Description

This working paper applies the AI-Strategic Node Index (AI-SNI) as a local governance diagnostic to the proposed Project Bus data center campus in Temple, Georgia. It distinguishes commercially viable AI-enabling infrastructure from structurally necessary AI system nodes and argues that the proposal shows limited evidence of non-substitutability while generating governance friction and path-dependency risk.

Abstract

As artificial intelligence (AI) infrastructure rapidly expands at sub-national levels, local governments are increasingly asked to approve large-scale data centers under claims of strategic necessity, digital competitiveness, or AI leadership. However, existing evaluation frameworks rarely distinguish between commercially viable infrastructure and structurally necessary AI system nodes. This article applies the AI-Strategic Node Index (AI-SNI), a governance-oriented diagnostic framework originally developed for macro-strategic analysis, to a local infrastructure controversy: the proposed data center campus ("Project Bus") in Temple, Georgia. The analysis demonstrates that while the proposed facility may hold commercial or optional future value, it does not constitute a demonstrably structurally necessary AI node under current evidentiary conditions. Instead, the project exhibits high governance friction and long-term path-dependency risks disproportionate to its demonstrated system indispensability.

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Keywords

  • AI governance
  • data centers
  • infrastructure lock-in
  • local governance
  • AI-SNI
  • AI-Strategic Node Index
  • AI-Strategic Node Framework
  • structural necessity
  • Temple Georgia
  • Project Bus
  • sub-national AI infrastructure
  • governance friction
  • path dependency
  • non-substitutability
  • data center governance
  • infrastructure approval
  • public policy
  • EPINOVA

Subjects

  • Artificial intelligence governance
  • Infrastructure governance
  • Local government
  • Data center policy
  • Public policy
  • Urban and regional planning
  • Technology governance
  • Risk assessment
  • Institutional design
  • AI infrastructure

Recommended citation

Wu, Shaoyuan. (2026). When AI Infrastructure Is Optional but Governance Lock-In Is Not: An AI-SNI Local Governance Diagnostic of the Temple (GA) Data Center Proposal (EPINOVA Working Paper No. EPINOVA–WP–D–2026–01). Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.5281/zenodo.18463740. DOI: To be assigned after Crossref membership approval.

APA citation

Wu, S. (2026). When AI infrastructure is optional but governance lock-in is not: An AI-SNI local governance diagnostic of the Temple (GA) data center proposal (EPINOVA Working Paper No. EPINOVA–WP–D–2026–01). Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.5281/zenodo.18463740. DOI: To be assigned after Crossref membership approval.

Alternate identifiers

SchemeIdentifierDescription
DOIhttps://doi.org/10.5281/zenodo.18463740Zenodo DOI landing page
Local identifierEPINOVA–WP–D–2026–01EPINOVA Working Paper D-Series publication number

Related works

RelationIdentifierTypeDescription
References10.5281/zenodo.18452803White BookAI-Strategic Node Framework (AI-SNF) conceptual and methodological white book used as the methodological basis for AI-SNI
IsSupplementedByhttps://apps.dca.ga.gov/DRI/Government recordGeorgia Department of Community Affairs Development of Regional Impact application summary for Project Bus (DRI #4606)
References10.6028/NIST.AI.100-1Technical reportNIST AI Risk Management Framework used as a governance and risk-management reference

References

  1. Wu, S.-Y. (2026). AI-Strategic Node Framework (AI-SNF): Conceptual and methodological white book (Version 0.1; EPINOVA-IWB-2026-01). Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.5281/zenodo.18452803
  2. Georgia Department of Community Affairs. (2026). Development of regional impact (DRI) application summary: Project Bus (DRI #4606). State of Georgia. https://apps.dca.ga.gov/DRI/
  3. Organisation for Economic Co-operation and Development. (2019). Artificial intelligence in society. OECD Publishing. https://doi.org/10.1787/eedfee77-en
  4. National Institute of Standards and Technology. (2023). Artificial intelligence risk management framework (AI RMF 1.0) (NIST AI 100-1). U.S. Department of Commerce. https://doi.org/10.6028/NIST.AI.100-1
  5. UNESCO. (2021). Recommendation on the ethics of artificial intelligence. United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000381137