A bibliometric review of ESG and artificial intelligence in the financial sector
Abstract
The integration of Artificial Intelligence (AI) and Environmental, Social, and Governance (ESG) principles is increasingly shaping the future of sustainable finance. AI technologies, including machine learning and predictive analytics, offer financial institutions powerful tools to enhance ESG-related decision-making, such as automated ESG scoring, risk assessment, and portfolio optimization. A bibliometric analysis is particularly valuable in this context, as it systematically maps the intellectual landscape of the field, identifies influential research, and reveals emerging trends. By analysing 145 peer-reviewed articles published between 2020 and 2025 from the Scopus database using VOSviewer,this study captures the evolution of research on AI-driven ESG integration in financial practices. The findings identify key research trends, emerging themes, influential authors, the most productive countries, and leading academic journals. The analysis reveals a growing focus on AI-driven ESG scoring, risk assessment, and sustainable investment strategies while highlighting persistent challenges related to data quality, lack of standardization, and limited empirical evidence, particularly in emerging markets. This study emphasizes the need for harmonized ESG metrics and more transparent, explainable AI models to support responsible financial decision-making. By providing a comprehensive and detailed analysis of the existing literature, this research deepens our understanding of the integration of AI into ESG criteria within the financial sector, offering novel insights and identifying promising directions for future studies. It delivers strategic guidance for both academic researchers and financial institutions aiming to leverage AI for sustainable finance. The study highlights opportunities to design innovative AI tools and frameworks that promote transparency, accountability, and resilient investment strategies, ultimately advancing long-term sustainability and responsible financial practices.