A Comprehensive Bibliometric Study on Exploring the Frontier of Artificial Intelligence Sustainability in Business

Gan Connie; Abdul Rahman Bin S Senathirajah; Shaikhah  Al-Ainati; Sayeeduzzafar Qazi; Rasheedul Haque; Ayma Fatima

doi:10.3991/ijim.v20i07.61079

Authors

Gan Connie INTI International University, Nilai, Malaysia https://orcid.org/0009-0005-3682-1788
Abdul Rahman Bin S Senathirajah INTI International University, Nilai, Malaysia; Shinawatra University, Bang Toei, Thailand; Wekerle Business School, Budapest, Hungary https://orcid.org/0009-0000-2064-5365
Shaikhah Al-Ainati College of Business Studies, Public Authority for Applied Education and Training (PAAET), Ardiya, Kuwait https://orcid.org/0000-0003-0955-0124
Sayeeduzzafar Qazi University of Business and Technology, Jeddah, Saudi Arabia https://orcid.org/0000-0003-1458-3166
Rasheedul Haque MILA University, Nilai, Malaysia https://orcid.org/0000-0001-8170-5413
Ayma Fatima INTI International University, Nilai, Malaysia https://orcid.org/0009-0001-3210-8580

DOI:

https://doi.org/10.3991/ijim.v20i07.61079

Keywords:

AI (Artificial Intelligence)

Abstract

The aim of the study is to investigate features of the current literature on how businesses have adopted AI to develop sustainable models and processes that comprise types of publications, volumes, keywords related to the study, and areas of theme. The paper shall also determine the countries that have been conducting research on AI sustainability in business by searching articles contained in the Scopus database between the years 2008–2025 using the search keys AI sustainability in business. Scopus was selected as the main tool of literature search because it is the largest indexed database in the business sphere and covers all the commercial journals. VOSviewer will be used to conduct a bibliometric analysis that would allow drawing up a map of research trends and a research network of the authors of the identified articles. According to the findings of this study, the most considerable five countries on the number of co-authored articles included Italy, China, Cyprus, the Russian Federation, and Thailand. The overall number of various keywords that were utilized in the papers analyzed in Scopus was 84, but the most common keywords that were shared by both articles were: artificial intelligence (AI) and sustainability. The study offers a complete overview of the worldwide research landscape on AI sustainability in the business sphere and will serve as a reference point for future research in the same field. The investigation will also contribute to the existing literature by being a distinct bibliometric review model and hence offer a point of view that is not similar to the traditional systematic literature review techniques.