IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2502.00009.html
   My bibliography  Save this paper

The Solo Revolution: A Theory of AI-Enabled Individual Entrepreneurship

Author

Listed:
  • Venkat Ram Reddy Ganuthula

Abstract

This paper presents the AI Enabled Individual Entrepreneurship Theory (AIET), a theoretical framework explaining how artificial intelligence technologies transform individual entrepreneurial capability. The theory identifies two foundational premises: knowledge democratization and resource requirements evolution. Through three core mechanisms skill augmentation, capital structure transformation, and risk profile modification AIET explains how individuals can now undertake entrepreneurial activities at scales previously requiring significant organizational infrastructure. The theory presents five testable propositions addressing the changing relationship between organizational size and competitive advantage, the expansion of individual entrepreneurial capacity, the transformation of market entry barriers, the evolution of traditional firm advantages, and the modification of entrepreneurial risk profiles. Boundary conditions related to task characteristics and market conditions define the theory's scope and applicability. The framework suggests significant implications for entrepreneurship theory, organizational design, and market structure as AI capabilities continue to advance. This theory provides a foundation for understanding the evolving landscape of entrepreneurship in an AI-enabled world.

Suggested Citation

  • Venkat Ram Reddy Ganuthula, 2025. "The Solo Revolution: A Theory of AI-Enabled Individual Entrepreneurship," Papers 2502.00009, arXiv.org.
  • Handle: RePEc:arx:papers:2502.00009
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2502.00009
    File Function: Latest version
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2502.00009. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.