Bibliometric Study of the Intersection Between Green Energy and Artificial Intelligence: Business- and Economy-Related Studies

Katerina Fotova Čiković; Damira Keček; Veljko Dmitrović

doi:10.31181/ijes1612027303

Authors

Katerina Fotova Čiković University North, Koprivnica, Republic of Croatia Author https://orcid.org/0000-0003-0138-1362
Damira Keček University North, Koprivnica, Republic of Croatia Author https://orcid.org/0000-0003-1555-3655
Veljko Dmitrović University of Belgrade, Faculty of Organizational Sciences, Belgrade, Republic of Serbia Author https://orcid.org/0000-0001-8924-9758

DOI:

https://doi.org/10.31181/ijes1612027303

Keywords:

Artificial intelligence, Green energy, Renewable energy, Bibliometric analysis, Business and economics, Sustainable development

Abstract

The rapid convergence of artificial intelligence (AI) and green energy (GE) is transforming sustainable business practices, energy management, and economic development. Although research in this interdisciplinary field has expanded considerably, its intellectual structure, thematic evolution, and business implications remain insufficiently understood. This study presents a comprehensive bibliometric analysis of AI and GE research from a business and economics perspective. Publications were retrieved from the Scopus and Web of Science databases using an expanded, transparent, and reproducible search strategy. Following PRISMA guidelines and predefined inclusion criteria, a final dataset of 7,301 publications was analyzed using Bibliometrix and VOSviewer to examine publication trends, influential authors, institutions, countries, journals, collaboration networks, and thematic structures. The results reveal a marked increase in scientific production after 2022, reflecting the growing integration of AI into renewable energy systems and sustainable development research. Scientific output is concentrated in countries with strong research capacity, sustained investment in digital innovation, and ambitious sustainability agendas. Keyword co-occurrence analysis identifies four dominant research themes: sustainability and energy policy, AI-driven forecasting and optimization, smart energy systems, and digital transformation for energy efficiency. The findings demonstrate that the field has evolved from predominantly technical applications toward a multidisciplinary research domain integrating business strategy, innovation management, sustainability, and energy economics. Unlike previous bibliometric studies based on narrower search strategies or smaller datasets, this study provides a transparent, large-scale mapping of the field and offers a more comprehensive understanding of its intellectual structure and emerging research directions. The findings provide valuable insights for researchers, policymakers, managers, and investors seeking to accelerate sustainable energy transitions and support long-term economic resilience.

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