Agentic Artificial Intelligence in Business Higher Education -- A Bibliometric Analysis to Highlight the Current Insights and Future Trends
Overview & Synopsis
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.
eric.ed.gov)
Document Information
| Document Title | Agentic Artificial Intelligence in Business Higher Education -- A Bibliometric Analysis to Highlight the Current Insights and Future Trends |
|---|---|
| Author / Organization | Irfan Saleem |
| Subject & Discipline | Higher Education, Artificial Intelligence, Business Education |
| Categories | Education & Pedagogy |
| Publication Year | 2026 |
| License / Rights | Public Domain / Open Access Educational Resource |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
ERIC (Education Resources)
(eric.ed.gov)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-171503 |
| Original Source Link | Visit Source Page on eric.ed.gov » |