Exploring the Intersection of AI, Big Data and Business Networks: A Bibliometric and Scientific Mapping Study

The combination between Artificial Intelligence (AI), Big Data and Business Networks has substantially transformed the system of performance of organizations and has enhanced inter-firm cooperation leading to innovation in various industries. This current bibliometric and scientific mapping research paper examines the intellectual environment of this interdisciplinary discipline in terms of the PRISMA model. The analysis is based on meta-data obtained on Web of Science (2015 to 2025). A package of visualizations (geographical distribution, annual publication patterns, author productivity, major journals, country output and keyword co-occurrence) are done by using RStudio and Vos viewer are used to map the central research topics and developing areas. Important groups draw the major themes and transformational research patterns. The ten most influential papers are put in the spotlight, which provides a selective reference to the background and breakthrough articles. The interpretation of the results on the collected data allows one to have a general picture of the evolution of the field among scholars. The findings indicate the constant growth of the academic contributions toward the entire world, with countries such as the United States, China and the United Kingdom taking the top table in terms of matters regarding research production. Key journals and authors are proposed, confirming the increased significance of AI and Big Data in optimization of the business networks in terms of its agility and efficiency. This work provides valuable lessons to artists and scholars due to its ability to capture the most up-to-date trends and highlight potential future directions of research that could benefit the resilience, scale and innovation in Networked Business context.

Artificial Intelligence, Big data, Business Network, Bibliometric Analysis, Innovation trends

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