Track: Artificial Intelligence

Abstract

The study literature on Artificial Intelligence and digital business models has grown in recent years. As artificial intelligence technology advances, it increasingly overlaps with the discipline of digital business model science. Using bibliometric mapping, this study attempts to comprehensively evaluate research trends in digital transformation and future research potential in the area. We visualized Artificial Intelligence for Digital Business Models research published in the previous ten years, from 2012 to 2021, using bibliometric analytic methodologies. For our investigation, 576 publications from Scopus were chosen. This study pulls data from the Scopus database, employs the Scopus online analysis tool, and using Vosviewer to display the bibliometric network. The process is divided into five stages: keyword selection, first search results, search result refining, initial compilation, and data analysis. According to our major line of study, papers published by scholars in the United States have the most publications, with 64 scientific publications. The topic area “Computer Science” has the most documents (N=324) 28.3%. The number of publications increased from 2016 to the maximum level in 2021, with 207 papers. The analyzed data reveals patterns and trends in worldwide Scopus-indexed articles. The analyzed data reveals patterns and trends in worldwide Scopus-indexed articles. This study suggests integrating research subjects: Digital Technology, Automation, Algorithm, and AI Technology, abbreviated as DTAAAT.