Matolwandile M. Mtotywa
Abstract
This bibliometric analysis study aims to understand the use of artificial intelligence (AI) in business education. The Scopus and Web of Science databases were the main sources of publication metadata and citation metrics (416 documents). The findings reveal that the research on Al in business education was almost non-existent until 2010, then increased exponentially after 2018. The conceptual structure keywords trend-specific phrases from about 2010 to 2022 were decision support systems, and more recently, ChatGPT and computational linguistics. Themes that exhibited a high level of development that organised the study field were AI in decision support systems and decision-making. Others included linkage of AI to other transformative technologies, humans (human-technology interaction), student, teaching, and e-learning, and then artificial intelligence, learning, systems, and deep learning which cut both the motor and basic themes. Additionally, analyses of intellectual structure and social structure maps show low levels of scientific collaboration and relationships between researchers, institutions, and countries. This research contributes to shaping the future agenda, which includes integrative thinking to resolve the dilemma of AI in business education. It also contributes to understanding the need for ethical use and governance and strengthening AI in education with other transformative technologies. Finally, in research that will help develop guidelines to maximise human-computer cognitive efficiency and grounding theories of AI use in business education.