Energy creates intelligence: the infrastructural geography of global AI

Does energy create intelligence? If intelligence in the AI era is fundamentally defined by computational capacity, then the geography of this digital intelligence is deeply grounded in material infrastructural conditions. This study investigates the interplay between energy systems, AI readiness, and data center deployment patterns, arguing that the geography of digital intelligence is fundamentally grounded in infrastructural conditions. Through a two-stage, multi-scalar analysis across 84 countries, we first examine how national-level energy consumption and institutional digital capacity (AI readiness) are structurally associated with the presence and scale of data centers. A mediation analysis suggests that energy facilitates data center proliferation both directly and indirectly through AI readiness, highlighting the layered infrastructural logic of digital expansion. At the subnational level, we analyze spatial entropy and clustering patterns in 34 countries with at least 10 data centers, identifying typologies of concentrated versus decentralized infrastructure. Our findings demonstrate that spatial configurations are not solely dictated by economic scale or technological demand, but rather reflect broader national contexts, energy grid structures, and planning paradigms. Countries such as the United States and Canada exhibit distributed spatial patterns likely driven by optimization goals, while others at earlier stages of digital adoption exhibit urban-centric concentration. This study introduces the concept of the infrastructure divide, a structural condition that precedes and shapes the digital divide, as a critical lens for understanding global inequality in the AI era. We argue that energy availability, spatial governance, and institutional alignment are core determinants of digital capacity. As AI becomes more energy-intensive and infrastructure-dependent, addressing disparities in foundational infrastructure is essential for ensuring sustainable participation in the future of intelligence.

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Publication Details

Journal
AI & Society
Published
2026-03-11
DOI
https://doi.org/10.1007/s00146-026-02974-2
Primary Topic
Global Energy and Sustainability Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Energy creates intelligence: the infrastructural geography of global AI

Junfeng Jiao, Ahyoung Chang
AI & Society
Global Energy and Sustainability Research
article

Energy creates intelligence: the infrastructural geography of global AI

Junfeng Jiao, Ahyoung Chang
article en

Abstract

Does energy create intelligence? If intelligence in the AI era is fundamentally defined by computational capacity, then the geography of this digital intelligence is deeply grounded in material infrastructural conditions. This study investigates the interplay between energy systems, AI readiness, and data center deployment patterns, arguing that the geography of digital intelligence is fundamentally grounded in infrastructural conditions. Through a two-stage, multi-scalar analysis across 84 countries, we first examine how national-level energy consumption and institutional digital capacity (AI readiness) are structurally associated with the presence and scale of data centers. A mediation analysis suggests that energy facilitates data center proliferation both directly and indirectly through AI readiness, highlighting the layered infrastructural logic of digital expansion. At the subnational level, we analyze spatial entropy and clustering patterns in 34 countries with at least 10 data centers, identifying typologies of concentrated versus decentralized infrastructure. Our findings demonstrate that spatial configurations are not solely dictated by economic scale or technological demand, but rather reflect broader national contexts, energy grid structures, and planning paradigms. Countries such as the United States and Canada exhibit distributed spatial patterns likely driven by optimization goals, while others at earlier stages of digital adoption exhibit urban-centric concentration. This study introduces the concept of the infrastructure divide, a structural condition that precedes and shapes the digital divide, as a critical lens for understanding global inequality in the AI era. We argue that energy availability, spatial governance, and institutional alignment are core determinants of digital capacity. As AI becomes more energy-intensive and infrastructure-dependent, addressing disparities in foundational infrastructure is essential for ensuring sustainable participation in the future of intelligence.

AI & Society
The University of Texas at Austin (US)
Openalex Percentile: Top 30%
Global Energy and Sustainability Research
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