Generative AI Use in Entrepreneurship: An Integrative Review and an Empowerment-Entrapment Framework

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Lu, Jackson G., Zhao, Gerui Gloria, Zheng, Anna Manyi
Natura: Preprint
Pubblicazione: 2026
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866908934504185856
author Lu, Jackson G.
Zhao, Gerui Gloria
Zheng, Anna Manyi
author_facet Lu, Jackson G.
Zhao, Gerui Gloria
Zheng, Anna Manyi
contents Despite the growing use of generative artificial intelligence (GenAI) in entrepreneurship, research on its impact remains fragmented. To address this limitation, we provide an integrative review of how GenAI influences entrepreneurs at each stage of the entrepreneurial process: (1) opportunity recognition and ideation, (2) opportunity evaluation and commitment, (3) resource assembly and mobilization, and (4) venture launch and growth. Based on our review, we propose the Empowerment-Entrapment Framework to understand how GenAI can both empower and entrap entrepreneurs, highlighting GenAI's role as a double-edged sword at each stage of the entrepreneurial process. For example, GenAI may improve venture idea quality but introduce hallucinations and training data biases; boost entrepreneurial self-efficacy but heighten entrepreneurial overconfidence; increase functional breadth but decrease relational embeddedness; and boost productivity but fuel "workslop" and erode critical thinking, learning, and memory. Moreover, we identify core features of GenAI that underlie these empowering and entrapping effects. We also explore boundary conditions (e.g., entrepreneurs' metacognition, domain expertise, and entrepreneurial experience) that shape the magnitude of these effects. Beyond these theoretical contributions, our review and the Empowerment-Entrapment Framework offer practical implications for entrepreneurs seeking to use GenAI strategically throughout the entrepreneurial process while managing its risks.
format Preprint
id arxiv_https___arxiv_org_abs_2604_02567
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Generative AI Use in Entrepreneurship: An Integrative Review and an Empowerment-Entrapment Framework
Lu, Jackson G.
Zhao, Gerui Gloria
Zheng, Anna Manyi
Computers and Society
Artificial Intelligence
Emerging Technologies
Human-Computer Interaction
Despite the growing use of generative artificial intelligence (GenAI) in entrepreneurship, research on its impact remains fragmented. To address this limitation, we provide an integrative review of how GenAI influences entrepreneurs at each stage of the entrepreneurial process: (1) opportunity recognition and ideation, (2) opportunity evaluation and commitment, (3) resource assembly and mobilization, and (4) venture launch and growth. Based on our review, we propose the Empowerment-Entrapment Framework to understand how GenAI can both empower and entrap entrepreneurs, highlighting GenAI's role as a double-edged sword at each stage of the entrepreneurial process. For example, GenAI may improve venture idea quality but introduce hallucinations and training data biases; boost entrepreneurial self-efficacy but heighten entrepreneurial overconfidence; increase functional breadth but decrease relational embeddedness; and boost productivity but fuel "workslop" and erode critical thinking, learning, and memory. Moreover, we identify core features of GenAI that underlie these empowering and entrapping effects. We also explore boundary conditions (e.g., entrepreneurs' metacognition, domain expertise, and entrepreneurial experience) that shape the magnitude of these effects. Beyond these theoretical contributions, our review and the Empowerment-Entrapment Framework offer practical implications for entrepreneurs seeking to use GenAI strategically throughout the entrepreneurial process while managing its risks.
title Generative AI Use in Entrepreneurship: An Integrative Review and an Empowerment-Entrapment Framework
topic Computers and Society
Artificial Intelligence
Emerging Technologies
Human-Computer Interaction
url https://arxiv.org/abs/2604.02567