Published 2026-09-01 | Version v1.0
Working PaperOpenPublished

Two Structures of AI Power

National Capacity, Relational Boundary Control, and Systemic Influence in the Emerging AI Order

Description

This working paper develops a two-structure framework for analyzing AI power in the emerging AI order. It distinguishes AI National Power, defined as the usable capacity of a national system to generate, mobilize, govern, and sustain AI-relevant resources, from AI Boundary Power, defined as an actor-level relational capacity to alter another actor's access to AI-relevant resources at a specified interface. The paper further separates boundary control from target-side boundary autonomy and from systemic influence as a later outcome. Through mechanism illustrations involving advanced-computing export controls and European Union AI regulation, it argues that national depth and boundary control are distinct but potentially complementary forms of AI power.

Abstract

Artificial intelligence competition is often measured through models, compute, investment, and adoption, yet these indicators conflate resources, relational leverage, and system-level outcomes. This article develops a two-structure framework that distinguishes AI National Power (ANP) from AI Boundary Power (ABP). ANP is the usable capacity of a national system to generate, mobilize, govern, and sustain AI-relevant resources. ABP is an actor-level relational capacity to alter the conditions under which another actor can obtain, transfer, integrate, deploy, or continue using an AI-relevant resource at a specified interface. The framework further separates boundary control from target-side boundary autonomy and from systemic influence as a later outcome. Through conceptual synthesis, operationalization, and mechanism illustrations involving advanced-computing export controls and European Union AI regulation, the article identifies effective control, interface criticality, enforceability, substitutability, and organizational conversion as key conditioning mechanisms. It argues that national depth and boundary control are distinct but potentially complementary forms of AI power. Their interaction helps explain why technologically capable states may remain externally constrained, why narrower actors can exercise consequential leverage, and why durable influence depends on more than possession of advanced AI.

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Keywords

  • AI power
  • AI National Power
  • AI Boundary Power
  • ANP
  • ABP
  • national power
  • boundary power
  • boundary autonomy
  • systemic influence
  • technological interdependence
  • AI sovereignty
  • structural power
  • AI governance
  • compute
  • data
  • models
  • platforms
  • cloud infrastructure
  • technical standards
  • procurement
  • finance
  • security authorization
  • advanced-computing export controls
  • EU AI Act
  • Brussels Effect
  • target substitutability
  • organizational conversion
  • EPINOVA

Subjects

  • AI governance
  • International political economy
  • Strategic studies
  • Technology sovereignty
  • Network power
  • Structural power
  • Digital regulation
  • Export controls
  • European Union AI regulation
  • Artificial intelligence policy
  • Power theory
  • Public policy

Recommended citation

Wu, Shaoyuan. (2026). Two Structures of AI Power: National Capacity, Relational Boundary Control, and Systemic Influence in the Emerging AI Order (EPINOVA Working Paper No. EPINOVA–WP–T–2026–02). Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.67037/epinova.wp.t.2026.002

APA citation

Wu, S. (2026). Two structures of AI power: National capacity, relational boundary control, and systemic influence in the emerging AI order. EPINOVA Working Paper Series, EPINOVA-WP-T-2026-002. Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.67037/epinova.wp.t.2026.002.

Alternate identifiers

SchemeIdentifierDescription
URLhttps://epinova.org/working-papersOfficial EPINOVA working papers page
EPINOVA working paper numberEPINOVA–WP–T–2026–02Working paper number printed in the PDF
File nameTwo Structures of AI Power National Capacity, Relational Boundary Control, and Systemic Influence in the Emerging AI Order.pdfSource PDF file name
Framework acronymANPAI National Power
Framework acronymABPAI Boundary Power
Analytical conceptBoundary autonomyTarget-side capacity to reduce exposure to another actor's boundary control through switching, bypass, substitution, localization, or internalization
Analytical conceptSystemic influencePersistent and sufficiently broad change in feasible option sets, network connections, or governing rules within a pre-specified domain

Related works

RelationIdentifierTypeDescription
IsPartOfhttps://epinova.org/working-papersPublication seriesEPINOVA Working Paper Series
IsSupplementedByhttps://github.com/EPINOVALLC/EPINOVA-ResearchRepositorySupplementary repository and structural archive
ReferencesWu, S. (2026a). Beyond centrality: Conditional connectivity and boundary control in interdependent networksWorking paperReferenced as the general conditional-connectivity and boundary-control framework adapted to AI-specific interfaces
ReferencesBradford, A. (2020). The Brussels effectBookReferenced for regulatory power through market access
ReferencesFarrell, H., & Newman, A. L. (2019). Weaponized interdependenceJournal articleReferenced for jurisdictional and institutional conversion of network position into coercive leverage
ReferencesEuropean Parliament & Council of the European Union. (2024). Regulation (EU) 2024/1689RegulationReferenced for EU AI Act general-purpose AI obligations
ReferencesNVIDIA Corporation. (2025a, 2025b)Corporate filingsUsed for the advanced-computing export-control mechanism illustration

References

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