Artificial intelligence (AI) and corporate governance: systematic and bibliometric review

This chapter explores the intersection of artificial intelligence (AI) and corporate governance (CG), highlighting how AI technologies, such as machine learning and natural language processing, can optimize decisionmaking, compliance, risk management, and business performance. The study aims to systematically and bibliometric review the existing literature on AI and CG, map current trends, and identify future research agendas in this interdisciplinary field. A dataset of 445 publications was curated using the PRISMA framework, focusing on AI’s application in corporate settings. The study employs bibliometric analysis to explore the contributions of authors, sources, and countries, along with co-citation, thematic map, and keyword co-occurrence analyses to uncover contextual relationships and themes shaping the field. The review identifies a significant increase in publications in recent years, driven by advancements in AI. Key themes include AI-driven decision support systems, ethical considerations, and AI’s role in enhancing corporate transparency and fraud detection. The findings also highlight the diverse academic contributions from scholars in computer science, business ethics, and financial management. AI has the potential to transform CG, but ethical and legislative challenges must be addressed. The study emphasizes the need for multidisciplinary research to explore AI’s practical implications in governance, ensuring responsible and effective implementation. This review provides valuable insights into the emerging context of AI in CG, proposing future research directions to further investigate AI’s impact on governance structures and stakeholder relationships.