| Issue |
E3S Web Conf.
Volume 712, 2026
2026 16th International Conference on Future Environment and Energy (ICFEE 2026)
|
|
|---|---|---|
| Article Number | 06008 | |
| Number of page(s) | 9 | |
| Section | Energy and Climate Policy: Economy, Society, and Governance | |
| DOI | https://doi.org/10.1051/e3sconf/202671206008 | |
| Published online | 19 May 2026 | |
The influence of artificial intelligence readiness on energy consumption patterns: Panel evidence from high-income countries
Center of Innovation in Economics Finance and Investment, Faculty of Economics, Chiang Mai University, Chaing Mai, Thailand, 50202
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
This study examines the effect of AI readiness, proxied by the Government AI Readiness Index developed by Oxford Insights, on primary energy consumption in high-income countries. Using balanced panel dataset covering 30 high-income economies over the period 2019-2023, the analysis employs panel regression techniques to assess how government-led preparedness for artificial intelligence adoption influences aggregate energy demand while controlling for income levels and structural characteristics. The empirical results reveal a positive and statistically significant relationship between AI readiness and primary energy consumption, indicating that the expansion of AI-related infrastructure, data capacity, and computational intensity currently outweighs potential energy-efficiency gains associated with AI applications. In contrast, GDP per capita exhibits a negative association with energy consumption, consistent with efficiency improvements and structural transitions toward less energy-intensive activities in advanced economies, while industry share does not display a systematic effect. These findings suggest that, even in relatively energy-efficient high-income countries, advancing AI readiness may exert upward pressure on national energy demand. Consequently, policies promoting AI development should be closely aligned with energy efficiency strategies, low-carbon electricity deployment, and sustainable digital infrastructure planning to ensure that technological progress supports long-term environmental and climate objectives.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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