Generative AI and Digital Entrepreneurship Business Models: A Systematic Literature Review (2020–2026)

Aldino Ismail Valentino; Feri Setyowibowo

doi:10.61255/jeemba.v4i3.1558

Authors

Aldino Ismail Valentino Universitas Sebelas Maret, Indonesia
Feri Setyowibowo Universitas Sebelas Maret, Indonesia

DOI:

https://doi.org/10.61255/jeemba.v4i3.1558

Keywords:

Generative Artificial Intelligence, Digital Entrepreneurship, Business Model, Dynamic Capabilities, Systematic Literature Review

Abstract

Purpose – This research focuses on exploring how Generative Artificial Intelligence (GenAI) is reshaping business models in digital entrepreneurship and intends to compile existing evidence through a systematic review of the literature.

Design/methodology/approach – This study employed a Systematic Literature Review (SLR) following the PRISMA 2020 guidelines. Articles published between 2020 and 2026 were collected from Scopus and Google Scholar. After the screening process, 10 eligible studies were analyzed using thematic analysis and synthesized through the integration of Timmons' Entrepreneurial Model and Dynamic Capabilities Theory.

Finding/Results – The review identified five major themes: democratization of innovation, structural business model transformation, the enablement–dependence paradox, ethical dilemmas, and the evolution of entrepreneurial cognition and skills. The reviewed studies suggest that GenAI enhances opportunity recognition, accelerates business model innovation, and improves value creation.

Originality/Value – This study proposes an integrated conceptual framework that illustrates how GenAI may transform digital entrepreneurship business models by linking entrepreneurial elements with dynamic capabilities. Rather than offering conclusive or generalizable claims, the findings provide preliminary theoretical propositions for future research and indicative practical implications for startups, SMEs, and policymakers in leveraging GenAI for sustainable innovation.

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