Harnessing Artificial Intelligence for Organizational Performance: A Bibliometric and Morphology-Based Cluster Analysis Using VOS Viewer

AI boosts organisational performance (OP), which is an organization's ability to meet its strategic goals. OP includes operational efficiency, innovation, consumer satisfaction, market share, and profitability. This study uses a bibliometric method to examine scholarly studies' current state and progress on Artificial Intelligence and Organizational Performance. The study's primary goal is to look at the conceptual framework of research on Artificial Intelligence and Organizational Performance to identify authors, journals, existing and developing topics, and suggested areas for future research. Many bibliometric studies have been done on artificial intelligence, but the morphology technique has not yet been shown in any study. Morphology analysis provides a deeper understanding of the topic and a detailed description of a subject by breaking it down into smaller components. Researchers conducted a bibliometric analysis on 318 publications using VOSviewer. Also, previous studies have been done with cluster analysis, but no study has shown the analysis with separate clusters. The present study utilized many approaches, including cluster analysis, morphology analysis, citation analysis, bibliographic coupling, and publication growth analysis, specifically addressing three research questions. Investigators classified terms into clusters and identified emerging patterns in Artificial Intelligence. This study also shows the Artificial Intelligence Tools and Technologies used for Organizational Performance based on the Clusters study.