Artificial intelligence as a driver of the energy transition: potential applications in Azerbaijan’s green energy sector

Abstract

The global transformation of energy markets and the shift toward low-carbon development models are establishing the renewable energy sector as a dominant force within national economies. The increasing technological complexity of renewable energy generation systems creates a demand for fundamentally new management approaches based on next-generation digital solutions. This article examines the potential for applying artificial intelligence (AI) within Azerbaijan’s green energy sector through the lens of economic efficiency.

The author decomposes key areas of AI implementation, substantiating their impact on the optimization of energy infrastructure and the growth of the industry's investment attractiveness. The article demonstrates that the use of intelligent systems acts as a catalyst for the investment attractiveness of renewable energy projects, facilitating the transition to an adaptive and environmentally sustainable energy system. Particular attention is paid to the theoretical foundations and current state of Azerbaijan's energy sector, enabling the identification of specific barriers and promising growth opportunities for the sector's digitalization.

The article proposes an original multifactor model for assessing the economic efficiency of implementing artificial intelligence technologies in the green energy sector. The model accounts for not only traditional investment metrics but also technological, environmental, operational, and market factors. Unlike existing approaches, the proposed model integrates generation dynamics, demand uncertainty, operational cost reductions, and environmental impacts into a unified system. The developed methodology enables a more accurate assessment of the economic feasibility of implementing AI within the renewable energy sector.