Generative artificial intelligence for management education: applications, benefits, challenges and future research directions

Purpose Generative artificial intelligence (GenAI) has received significant traction in recent years for its ability to generate content based on human inputs. The aim of this study is to examine the existing literature on GenAI in management education by conducting a combination of bibliometric analysis and systematic literature review and provide future research directions, which can help management educators to train management students who are potential future managers. Design/methodology/approach Utilizing a total of 141 articles obtained from multiple databases, this study conducts a systematic literature review and synthesizes the existing literature on GenAI across management functions and industries. Further, this study provides future research directions specific to each group that will help in the advancement of context-specific management education. Findings The study synthesized the applications, benefits, challenges and future research directions of GenAI across different management domains, including marketing, finance and accounting, operations and human resource management. Overall, the study found that GenAI can promote academic performance enhancement, personalized learning, programming skills development, improved student motivation and effective learning. Originality/value The study provides an avenue for management education teachers to train their students in multiple management domains to get a comprehensive idea about the current work on GenAI in that particular domain, using which they can proceed to work in the domain. For management students who are potential emerging managers, the results of the study provide a comprehensive overview of the applications of GenAI across various management verticals, which provides a basis for benchmarking against the applications of GenAI.