Artificial Intelligence and Sustainable Energy Transition: Innovation–Utilization Pathways and the Contingent Roles of Political, Financial, and Economic Stability

ABSTRACT Artificial intelligence (AI) is increasingly linked to sustainable energy transitions, but its role can be highly contextual on country‐specific technological pathways and macro‐level stability. Using balanced panel data for 60 countries from 2010 to 2022, this study examines the relationship between AI indices and renewable energy consumption outcomes through fixed‐effects models, dynamic panel threshold models, and scenario‐based regressions. The results support the positive association between AI development and renewable energy consumption share, with stronger effects in high‐income countries than in middle‐income countries. The technology channel yields a stronger impact than the application channel, while AI application is insignificant in middle‐income countries, suggesting constraints from weak digital infrastructure and absorptive capacity. Threshold results indicate that political and financial stability strengthen the AI–energy transition relationship, whereas economic stability shows a diminishing marginal pattern. Scenario analysis further suggests that AI is most effective under jointly low political, financial, and economic risks. These findings highlight that intelligence‐enabled energy transition requires not only AI development, but also stable governance, resilient finance, and adaptive macroeconomic policies.

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Publication Details

Journal
Sustainable Development
Published
2026-09-30
DOI
https://doi.org/10.1002/sd.71691
Primary Topic
Energy, Environment, Economic Growth
Type
article
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Artificial Intelligence and Sustainable Energy Transition: Innovation–Utilization Pathways and the Contingent Roles of Political, Financial, and Economic Stability

Yuanfan Li, Qiang Wang, Rongrong Li
Sustainable Development
Energy, Environment, Economic Growth
article

Artificial Intelligence and Sustainable Energy Transition: Innovation–Utilization Pathways and the Contingent Roles of Political, Financial, and Economic Stability

Yuanfan Li, Qiang Wang, Rongrong Li
article en

Abstract

ABSTRACT Artificial intelligence (AI) is increasingly linked to sustainable energy transitions, but its role can be highly contextual on country‐specific technological pathways and macro‐level stability. Using balanced panel data for 60 countries from 2010 to 2022, this study examines the relationship between AI indices and renewable energy consumption outcomes through fixed‐effects models, dynamic panel threshold models, and scenario‐based regressions. The results support the positive association between AI development and renewable energy consumption share, with stronger effects in high‐income countries than in middle‐income countries. The technology channel yields a stronger impact than the application channel, while AI application is insignificant in middle‐income countries, suggesting constraints from weak digital infrastructure and absorptive capacity. Threshold results indicate that political and financial stability strengthen the AI–energy transition relationship, whereas economic stability shows a diminishing marginal pattern. Scenario analysis further suggests that AI is most effective under jointly low political, financial, and economic risks. These findings highlight that intelligence‐enabled energy transition requires not only AI development, but also stable governance, resilient finance, and adaptive macroeconomic policies.

Sustainable Development
St Petersburg University (RU), China University of Petroleum, East China (CN)
Openalex Percentile: Top 5%
Energy, Environment, Economic Growth
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Artificial Intelligence and Sustainable Energy Transition: Innovation–Utilization Pathways and the Contingent Roles of Political, Financial, and Economic Stability — Yuanfan Li, Qiang Wang, et al. · Sustainable Development (2026) | TGRS Research Map | TGRS