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Generative AI Integration in Entrepreneurship Education

Intesar Almugren et al.

Journal of Global Information Management2026https://doi.org/10.4018/jgim.402747article
AJG 2ABDC A
Weight
0.50

Abstract

Generative AI holds promise for venture-creation curricula, yet faculty adoption remains hindered by poorly understood incentives and barriers. This study employs a three-stage mixed-methods design to clarify those drivers. A systematic review identified 28 factors, refined by expert panel to 16 key variables. A fuzzy-DEMATEL survey revealed that faculty training, institutional support, and curricular integration exert the strongest causal influence. Clustering these factors yields three intervention domains—pedagogical, organizational, and technological—suggesting a phased adoption strategy. This framework shifts focus from tool access to educator-led implementation, offering academic leaders an evidence-based roadmap for cost-effective AI integration.

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https://doi.org/https://doi.org/10.4018/jgim.402747

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@article{intesar2026,
  title        = {{Generative AI Integration in Entrepreneurship Education}},
  author       = {Intesar Almugren et al.},
  journal      = {Journal of Global Information Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.4018/jgim.402747},
}

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Generative AI Integration in Entrepreneurship Education

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.