Generative AI and the Future of Entrepreneurship: Opportunities, Disruptions & Ethical Dilemmas

Abstract

Purpose: This paper aims to examine the multifaceted impact of Generative Artificial Intelligence (GenAI) on entrepreneurship by exploring the opportunities it presents, the disruptions it causes, and the ethical dilemmas it raises. The study proposes a conceptual framework — the GenAI-Entrepreneurship Integration Model (GEIM) — to guide entrepreneurs and policymakers toward responsible and strategic adoption of GenAI.

Methodology: This study adopts a conceptual and analytical research design based entirely on secondary data. It draws upon recent peer-reviewed journal articles, Harvard Business School working papers, IZA discussion papers, industry reports, and preprint studies from 2023–2025. Thematic synthesis and conceptual framework development are used as the primary analytical approaches.

Results & Analysis: The study finds that GenAI democratises ideation, lowers entry barriers, and enables new business models — with global GenAI investment rising from $2.8 million median seed rounds in 2020 to $7 million in 2024. However, its benefits are unevenly distributed: high-performing entrepreneurs gain over 15% in revenues from AI assistance, while low performers experience an 8% decline. Ethical challenges, including bias, intellectual property uncertainty, and data privacy risks, further moderate GenAI's impact on organisational performance.

Originality: This paper makes an original contribution by proposing the GenAI-Entrepreneurship Integration Model (GEIM) — a novel four-pillar framework comprising Strategic Opportunity Identification, Human-AI Collaboration Design, Ethical Governance and Compliance, and Adaptive Learning and Upskilling. The GEIM synthesises insights from multiple disciplinary streams to provide a structured yet adaptive lens for entrepreneurial GenAI adoption.

Value: This paper offers practical value to entrepreneurs, business educators, and policymakers navigating the rapidly evolving GenAI landscape. It highlights that AI-driven growth must be balanced with ethical governance, equitable access, and continuous skill development to achieve sustainable entrepreneurial outcomes.

Type of Paper: Conceptual Paper based on Secondary Data Analysis.