The Evolution of Artificial Intelligence Applications in Business and Economic Research: A Bibliometric and Science Mapping Approach

In recent years, the application of Artificial Intelligence (AI) and Machine Learning (ML) has transformed how businesses and economies evolve, especially in response to the global digital transformation accelerated by the COVID-19 pandemic. This study applies a bibliometric and science mapping approach to systematically examine 2,428 peer-reviewed articles indexed in Scopus from 2013 to 2024, focusing on AI's role within the domains of economics and business. The methodology includes PRISMA-guided data screening and visualization using VOSviewer and Bibliometrix, highlighting publication trends, co-authorship networks, subject area distribution, and thematic clusters. Findings reveal exponential growth in AI-related publications since 2018, with dominant themes centered on digital marketing, personalization, and business process optimization. Developed countries—particularly the United States, China, India, and the United Kingdom—account for the majority of contributions, while developing countries remain underrepresented. Moreover, limited attention has been given to ethical dimensions of AI in business contexts, suggesting a critical research gap. The study underscores the need for broader, more inclusive collaboration and exploration of under-researched areas such as ethical AI, logistics, and SMEs. Overall, this research offers strategic insights for scholars, policymakers, and industry leaders seeking to understand and shape the evolving AI landscape in business and economic research.