AI-enabled entrepreneurship: The entrepreneurial pyramid, minimum viable organization, and entrepreneurial scaffolding

America’s startup surge includes a growing population of solopreneurs and lean firms that use AI in venture work. Treating the United States as a motivating context, this paper develops AI-enabled entrepreneurship as a construct describing how entrepreneurs use AI to identify and enact opportunities, organize venture work, and scale selected activities with fewer initial resources. The analysis focuses on broadly accessible generative AI. We distinguish the construct from digital entrepreneurship, AI entrepreneurship, and AI-native ventures; specify when AI use materially affects a venture; and identify five mechanisms: augmentation, substitution, automation, capability extension, and orchestration. Drawing on general-purpose technology theory, the external enabler framework, the entrepreneurial pyramid, and a design science view of scaffolding artifacts, we propose that broadly accessible AI simplifies the minimum viable organizational architecture required for entrepreneurial action. This change widens the base of the entrepreneurial pyramid. Whether entrepreneurial attempts become viable ventures, however, depends on complementary founder capabilities, structured human-AI interaction, and contextual boundary conditions. Seven propositions, organized across founder, venture, firm, and ecosystem levels, address entry, lean organization and contingent hiring, experimentation, outcome dispersion, complementarity-based advantage, and scaffolding. Evidence is consistent with faster launch and leaner organization, but not with AI as the sole cause of the surge or an automatic source of performance. We outline a measurement architecture and a research agenda, and draw implications for MSMEs, educators, and policymakers.