Bridging the Divide: An Interdisciplinary Systematic Literature Review on the Evolution of Artificial Intelligence in Management and Technology Literature

Research on artificial intelligence (AI) has escalated in recent years driven by, first, the dramatic advances of AI in the wider technical field (e.g., information technology, operations research, analytics), and second, the diverse applications of AI in the wider management field. A comprehensive understanding of AI requires that scholars provide insights that bridge the technical and management (non-technical) fields, thus benefiting the further evolution of AI. However, such a task is challenging given the amount and complexity of the literature across these two different disciplines. We address this challenge by conducting an interdisciplinary systematic literature review (SLR) of a total of 1,472 studies from leading technical and non-technical/management scholarly journals from 2006 to 2022. We employ an integrated approach: two advanced analytical algorithms — bibliometric and topic modelling analyses — complemented by our own reading of identified topic articles. Our study’s contributions are threefold: empirical, theoretical, and methodological.