Bibliometric Analysis of Accounting Literature on Artificial Intelligence (AI) Adoption in Organizational Functions

Abstract

Artificial intelligence (AI) is a powerful technology with a high potentiality of transformative drive from traditional analog to digitalized organizational seamless decision processes efficiently and effectively. AI is an emerging area in organizational decision-making with limited number of studies across the globe. However, AI is now gaining considerable attention from the researcher, both at the local and international level. This study aims at providing a systematic review and biometric analysis on AI adoption in organizational functions using Google Scholar databases as the source of data. The study employs the steps of Prepare Reporting Items for Systematic Literature Review and Meta-Analysis Techniques PRISMA (2020) and bibliometric analysis techniques using VOS-View as a tool for analysis of publications performance over time with a view to determining the most influential articles, publication productivity, and direction of studies on AI Adoption in organizational functions for a period of ten years from 2015 to 2024. The analysis reveals that articles published in 2016 by Sage Journal recorded the highest citation of 2707, followed by MDPI Journal with total citations of 1922 in 2021, while Elsevier presents the lowest citation of 87 citations over the period of 10 years in the database used. These articles were written on more than 20 areas of application of AI in organizational functions.