Does a country’s energy security increase with advances in government AI readiness? An empirical panel study
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DOIhttp://dx.doi.org/10.21511/ee.16(4).2025.12
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Article InfoVolume 16 2025, Issue #4, pp. 182-196
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Type of the article: Research Article
Abstract
Recent assessments by the IEA, IRENA, and the World Bank indicate that data- and algorithm-driven operations can enhance energy security by increasing efficiency, reducing curtailment, and stabilizing grids as the renewable share grows, while also warning of ecological trade-offs from rising digital electricity use. Against this backdrop, government AI readiness emerges as a crucial enabling condition, providing the institutional and technological capacity to translate climate and sustainability targets into day-to-day energy system performance. Framed through an environmental lens, the study examines whether government AI readiness acts as an ecological enabler that strengthens energy security by supporting the integration of renewable energy, reducing emissions, and enhancing system resilience. To test this ecological proposition, we assemble a balanced panel of 125 countries (2020–2023), combining the Oxford Insights Government AI Readiness Index with the World Energy Council’s Energy Security Score as an operational proxy for environmentally robust energy systems. Using panel methods (fixed and random effects), with diagnostics for serial correlation, cross-sectional dependence, and heteroskedasticity, and Driscoll-Kraay standard errors for robust inference, we find that in the random-effects specification, a one-point rise in AI readiness is associated with a 0.1104-point improvement in the energy security score (p < 0.001). The effect remains statistically significant after accounting for temporal and cross-sectional dependencies, supporting the view that institutional preparedness to use AI can act as an enabling ecological instrument, facilitating the integration of renewable energy, demand-side efficiency, and system resilience, which together underpin cleaner, more secure energy.
Acknowledgment
This study was prepared as part of the project 101127491-EnergyS4UA-ERASMUS-JMO2023-HEI-TCH-RSCH. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or European Education and Culture Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.
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JEL Classification (Paper profile tab)Q01, Q41, Q48, O33
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References58
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Tables7
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Figures0
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- Table 1. Descriptive statistics of the Energy Security and the Government AI Readiness Index Score for 125 countries, 2020–2023
- Table 2. Fixed-effects (within) panel model estimating the impact of Government AI Readiness Index on the Energy Security Score, 125 countries, 2020–2023
- Table 3. Random-effects panel model (Swamy-Arora transformation) of the relationship between Government AI Readiness Index and the Energy Security Score, 125 countries, 2020–2023
- Table 4. Random-effects panel model of Energy Security Score with conventional standard errors for the Government AI Readiness Index, 125 countries, 2020–2023
- Table 5. Random-effects panel model of Energy Security Score with Driscoll-Kraay robust standard errors for the Government AI Readiness Index, 125 countries, 2020–2023
- Table 6. Country-specific random intercepts (re_effect) and Energy Security Score intercepts: Top 10 and bottom 10 countries by structural energy security, controlling for Government AI Readiness Index
- Table A1. Sample of countries
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