Global divide emerges as AI leaders drive green energy transition, leaving others behind

Artificial intelligence is becoming a decisive factor in the global shift toward renewable energy, according to a new international study published in the journal Economies. The research highlights how different aspects of AI adoption are shaping both renewable energy production and consumption.

The study, titled “Nexus Between Artificial Intelligence, Renewable Energy, and Economic Development: A Multi-Method Approach,” examines data from 30 countries, including the European Union’s 27 members, the United States, the United Kingdom, and China, during the period 2020 to 2023. By employing robust regression, Gaussian Graphical Models, and clustering analysis, the researchers identify the precise ways in which AI investments, readiness, and project implementation influence renewable energy outcomes.

AI investments, readiness, and projects: Distinct roles in energy development

The study found that AI affects renewable energy production and consumption in different ways. The analysis shows that AI investments and AI projects strongly support renewable energy production. Countries that channeled more capital into AI and implemented tangible AI-driven initiatives saw measurable increases in renewable energy output. These results suggest that financing and project-based applications are key levers for expanding renewable capacity on the supply side.

In contrast, AI readiness emerged as the most influential factor in boosting renewable energy consumption. Readiness captures a country’s institutional and infrastructural ability to integrate AI, including workforce skills, regulatory frameworks, and data infrastructure. The study found that readiness not only drives the share of renewables in national consumption but does so more decisively than direct investment. In other words, producing renewable energy requires financial and technological commitment, but ensuring that it becomes a larger part of the national energy mix demands institutional preparedness and supportive governance structures.

The distinction underscores the need for tailored policies. Nations aiming to increase renewable output may prioritize AI project financing, while those focused on raising consumption levels should invest in readiness, capacity building, and governance reform.

Carbon emissions and GDP: The uneven dynamics of the transition

The researchers also analyzed how carbon emissions and economic development interact with the AI–energy nexus. The results reveal an asymmetric role for CO₂ emissions. On the one hand, emissions were positively correlated with renewable production. This suggests that countries with higher emissions may be ramping up renewable generation as part of their transition strategies. On the other hand, emissions were negatively associated with renewable consumption, indicating that a higher reliance on renewables in energy use contributes to lowering national emission levels.

Economic growth, as measured by GDP per capita, presented another layer of complexity. Surprisingly, the study found negative associations between GDP per capita and both renewable production and consumption in the sampled countries. This counterintuitive result suggests that wealthier nations may experience structural barriers or transition frictions that slow renewable integration, while middle-income countries could be more aggressively scaling up renewable strategies.

The authors caution that without effective policy frameworks, rapid growth does not necessarily translate into cleaner energy systems. The findings point to the need for policies that align economic expansion with sustainability, particularly in advanced economies where inertia or existing infrastructure may hinder renewable adoption.

Network centrality and country clusters: Mapping the global transition

The study uses Gaussian Graphical Models to map conditional relationships among the variables. The analysis revealed that AI readiness serves as the central mediator linking AI investments and AI projects to renewable outcomes. This centrality highlights readiness as the bridge through which financial and project-based efforts ultimately translate into changes in energy systems. Without robust institutional readiness, investments and projects may yield limited impact on consumption patterns.

The study also employed cluster analysis to identify two distinct groups of countries in 2023. The first cluster included advanced economies such as the United States, China, Germany, the United Kingdom, and France, along with several Western and Nordic EU states. These countries are characterized by higher AI readiness and stronger integration of green energy. The second cluster consisted largely of Eastern and Southern European economies still in the catch-up phase, with lower levels of AI preparedness and slower renewable integration.

This clustering suggests a growing divide between leaders and laggards in the renewable transition. While advanced economies are leveraging AI to consolidate their green energy strategies, emerging economies may require targeted support to bridge gaps in readiness and infrastructure.

Policy Implications and Global Outlook

To scale renewable production, governments must direct resources toward AI investments and projects that expand capacity. However, to ensure that clean energy is consumed at scale, policymakers must strengthen readiness by developing skills, establishing robust regulations, and improving data systems. The researchers emphasize that without a dual focus on production and consumption, renewable gains may be uneven and fall short of their potential in reducing emissions.

The asymmetric role of CO₂ emissions points to a delicate balancing act. Countries need to expand renewable production even as they reduce dependence on carbon-intensive energy in consumption. Aligning both sides of the equation is essential for achieving meaningful progress in climate goals.

Finally, the divergence between high- and middle-income countries underscores the importance of international cooperation. While advanced economies consolidate their positions as green leaders, emerging economies must not be left behind. Building global mechanisms for knowledge transfer, technology sharing, and capacity building will be critical to closing the gap