Impact of artificial intelligence in international business – a comprehensive review

Abstract

The aim of this research article is to review the existing literature on the impact of artificial intelligence (AI) on the international business (IB) phenomena. In particular, a comprehensive bibliometric method as well as a literature review is conducted, followed by focused future research directions for scholars. This study adopts a systematic literature review approach, in which we conducted a thorough bibliometric analysis as well as a systematic literature review by analyzing each of the papers. Bibliometric analysis is performed using the Biblioshiny software, which merges data from the Scopus and Web of Science databases. In some cases, where the merged data do not show significant results, we used the VOSviewer software for analysis. Furthermore, we read the selected papers and created a detailed spreadsheet of the papers and then crafted themes to present our literature review. We then analyzed the gaps in existing literature to provide future research directions. We could identify trends and patterns of AI's influence on IB scholarship, where there is a sudden jump in the articles post-COVID, i.e., 2020 onward. Furthermore, there is a diverse range of streams currently publishing on this topic indicates the infancy of an evolving research domain. In addition, there is a wide range of countries that are publishing on this topic, which suggests growing awareness and adoption of AI; however, several African, Asian and South American countries require significant catch-up. Next, our themes derived from the findings of the literature reveal that AI is driving innovation and efficiency, amplifying cultural and behavioral dynamics, facilitating critical knowledge and improving governance for MNEs to impact IB. Finally, we suggest five future research directions, i.e., geopolitical environment, regulatory frameworks, dark side of AI, ESG and culture, which are critical to any MNE's success in a foreign country. We encourage scholars to study IB through the lens of AI's impact on these research agendas. To the best of the authors’ knowledge, this is one of the first systematic and bibliometric analyses of AI's influence on the IB. Furthermore, ours is one of the few attempts to merge the two databases, i.e., Scopus and the Web of Science, to provide a comprehensive set of articles for the bibliometric analysis. We also provide the R-code on how to merge the two databases. Finally, we review the existing literature by providing four novel themes and present five unique future research directions.