The evolution of entrepreneurship education in the digital era: a bibliometric roadmap of AI-driven experiential learning (2016–2026)

Ghandour, R orcid iconORCID: 0000-0002-2284-0671 (2026) The evolution of entrepreneurship education in the digital era: a bibliometric roadmap of AI-driven experiential learning (2016–2026). Higher Education, Skills and Work-Based Learning. pp. 1-17. ISSN 2042-3896

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Abstract

Purpose
The purpose of this paper is to examine the evolution of artificial intelligence (AI)-driven experiential learning in entrepreneurship education in the digital era and to identify the main research trends, intellectual foundations and future directions shaping the field.

Design/methodology/approach
The study adopts a bibliometric approach using 204 Web of Science-indexed articles and reviews published between 2016 and June 2026. Performance analysis and science mapping were conducted using VOSviewer 1.6.20, including publication trajectory, source performance, co-citation, document citation, author productivity, keyword co-occurrence and overlay analyses.

Findings
The findings show that the field has shifted from limited early activity to rapid expansion during 2024–2026, driven by growing attention to generative AI, AI literacy and educational technology. Three knowledge bases are identified: educational technology and digital pedagogy; entrepreneurship, business and management education; and sustainability-oriented transformation. Five thematic clusters further highlight behavioural competency, AI integration in higher education, socio-technical adaptation, crisis-driven experiential learning and student-centred instructional design.

Originality/value
The paper contributes a bibliometric research roadmap for AI-driven experiential entrepreneurship education by identifying the field's intellectual structure, thematic development and future research directions. It positions AI not only as a digital tool, but as part of a wider pedagogical shift toward adaptive, responsible and precarity-aware entrepreneurial learning ecosystems.

Item Type: Article
Uncontrolled Keywords: 3903 Education systems
Subjects: H Social Sciences > HF Commerce > HF5001 Business
L Education > L Education (General)
Q Science > QA Mathematics > QA76 Computer software
Divisions: Liverpool Business School
Publisher: Emerald
Date of acceptance: 28 September 2026
Date of first compliant Open Access: 31 October 2026
Date Deposited: 30 Oct 2026 14:46
Last Modified: 31 Oct 2026 00:50
DOI or ID number: 10.1108/heswbl-06-2026-0474
URI: https://researchonline.ljmu.ac.uk/id/eprint/29784
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