Evolution of AI in Information Systems: A Bibliometric Study

Journal: Journal of Information Systems and Informatics

Publication: 2024-12-31 · Vol. 6 No. 4 · pp. 2837–2855

DOI: 10.51519/journalisi.v6i4.928

Abstract

Significant challenges for traditional information systems are posed due to the ever-growing volume and complexity of data. Artificial intelligence has emerged as a powerful solution to address these challenges by adapting and making intelligent decisions. Valuable insights can be gained from data to automate repetitive tasks and optimize the operations. This study examines how the researchers are concentrating to explore multifaceted impact of AI on the design, implementation, and optimization of information systems. AI is transforming the landscape of information systems with progresses in machine learning, text mining, cognitive computing and other AI technologies by enhancing the efficiency and adaptability across various domains. This study delves into this emerging landscape by conducting a comprehensive bibliometric analysis of Artificial intelligence in Information systems research. This bibliometric study retrieved a dataset of publications from Scopus database spanning from 1960 to 2023 to find out the insights hidden within the scientific papers. The analysis encompasses key bibliometric indicators, such as citation patterns, co-authorship networks, and thematic clusters etc. to represent historical development of research in Artificial intelligence within the context of Information systems. This study fills a gap in AI and IS literature, drawing on 306 publications, with key contributions from the USA, China, UK, Germany, India and leading authors like OGIELA L (Lidia Ogiela) and CIMINO JJ ( James J.  Cimino). Co-authorship networks highlight the dominance of collaborative research hubs in countries like USA, China, Canada, Australia, while citation patterns underscore the influence of seminal works and cross-disciplinary contributions. The findings presented in this paper offer valuable insights for researchers, practitioners, and policymakers seeking a deeper understanding of the growing AI-IS landscape. As this is the first paper which takes the attempt to conduct a bibliometric analysis on artificial intelligence in information systems, this paper serves as a roadmap for navigating the rich tapestry of research, fostering collaboration, and guiding future investigations in this rapidly evolving and interdisciplinary field.