AI powers energy transition across BRICS nations, but financial systems hold back progress

Economic growth, human capital, and financial globalization also contribute to the transition but to a much smaller extent. The authors argue that the digitalization of energy systems and the integration of AI into decision-making frameworks remain the most potent levers for sustainable progress in the BRICS economies.

Artificial intelligence is reshaping the global energy landscape, and new research highlights its defining role in helping emerging economies pivot toward low-carbon futures. A peer-reviewed study provides one of the most comprehensive analyses to date of how AI interacts with financial systems and innovation capacity to accelerate energy transition in the BRICS bloc.

The paper, titled “Unpacking Artificial Intelligence’s Role in the Energy Transition: The Mediating and Moderating Roles of Knowledge Production and Financial Development” and published in Energies, analyzes panel data from 2005 to 2020 across Brazil, Russia, India, China, and South Africa. It concludes that AI is not only a key enabler of renewable adoption but also the primary driver of efficiency gains that underpin the entire transition. The findings assert that the impact of AI is highly sensitive to national conditions, particularly the strength of research systems and the orientation of financial markets.

How artificial intelligence shapes explicit and implicit transitions

The study distinguishes between two dimensions of the energy transition. Explicit energy transitions (EET) involve visible changes such as a greater share of renewables in the energy mix, while implicit energy transitions (IET) refer to behind-the-scenes efficiency improvements, digitalization, and reductions in transmission losses.

AI plays a dominant role in both dimensions. The technology enhances renewable integration by forecasting variable generation from wind and solar, stabilizing grids, and enabling demand-side management. Equally critical, it drives implicit gains through predictive maintenance, smarter industrial processes, and optimized grid automation.

The analysis demonstrates that AI’s effect on explicit renewable deployment is fully mediated by efficiency improvements. In practice, this means countries that invest in AI to enhance system-level efficiency eventually achieve faster renewable adoption. Efficiency is therefore not a by-product but the crucial channel through which AI influences structural energy transformation.

Economic growth, human capital, and financial globalization also contribute to the transition but to a much smaller extent. The authors argue that the digitalization of energy systems and the integration of AI into decision-making frameworks remain the most potent levers for sustainable progress in the BRICS economies.

Financial development and knowledge production: The moderating forces

The study highlights the uneven role of financial systems in shaping the outcomes of AI-led transitions. Financial development, while often assumed to support clean energy, is shown to weaken AI’s positive effect. The authors found that in advanced financial markets, investments often continue to flow toward fossil fuel sectors and short-term profitable ventures, crowding out the capital needed for green transformation. Without policy reforms, deep financial markets may inadvertently slow progress by reinforcing carbon-intensive structures.

By contrast, knowledge production emerges as a decisive factor that amplifies AI’s impact. Countries with stronger research capacity, higher patenting activity, and well-established innovation ecosystems benefit far more from AI integration. In these contexts, AI is not only used for operational efficiency but also for breakthrough advances in clean technology. China and India, for example, leverage their robust R&D systems to maximize AI’s green potential, whereas weaker innovation environments in Russia, Brazil, and South Africa limit transformative outcomes.

The findings underline that AI cannot deliver sustainable energy futures in isolation. Its benefits depend on whether financial capital is directed toward clean projects and whether national research ecosystems can supply the intellectual infrastructure to sustain digital innovation.

Cross-border spillovers and policy pathways for BRICS

The research analyses cross-border spillover effects. AI advances in one BRICS nation can generate both positive and negative consequences for its peers. The study found that rapid AI adoption in China and India often draws capital and talent away from other members, producing competitive disadvantages that hinder their progress. At the same time, efficiency improvements and clean-tech innovation in one country can inspire demonstration effects that accelerate renewable uptake elsewhere.

These dynamics underscore the need for coordinated strategies within the bloc. Without collaboration, resource competition could deepen inequality in transition outcomes. The authors recommend establishing joint AI–energy R&D consortia, harmonizing green finance standards, and creating talent-exchange platforms. Shared data governance and cross-border pilot projects would also help to turn initial competition into collective advancement.

The policy recommendations extend beyond regional cooperation. The study calls for governments to phase AI adoption through efficiency pathways, focusing first on pilot smart grid and demand-response projects before scaling to national energy-management platforms. It stresses the importance of reforming financial systems by mandating minimum green lending quotas and expanding green bond markets to counteract fossil fuel lock-in. Human capital development and targeted support for patenting are also identified as essential for sustaining long-term gains.

The study further highlights urbanization, environmental regulations, and differentiated national strategies. Densely populated cities can serve as test beds for AI-enabled microgrids, while regulatory tightening ensures that efficiency and renewable integration become enforceable standards rather than aspirational goals.