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

Abstract

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.

Ähnliche Arbeiten