Agentic artificial intelligence in business higher education – a bibliometric analysis to highlight the current insights and future trends

Purpose This study explores the evolving landscape of agentic artificial intelligence (AI) and its transformative impact on higher education with a focus on business education. Design/methodology/approach This bibliometric analysis evaluates publications from the Scopus database using the student life cycle (SLC) model and the teaching triad. Findings This study reveals a rising trend in the publication of agentic AI in business education and recommends future research using time-series analysis, thematic mapping and clustering by coupling, followed by a use case for software developers. Originality/value This bibliometric analysis identifies key challenges and applications in business education and highlights the current insights.