IDEAS home Printed from https://ideas.repec.org/a/spr/joiaen/v14y2025i1d10.1186_s13731-025-00527-3.html
   My bibliography  Save this article

Comparative analysis of leading artificial intelligence chatbots in the context of entrepreneurship

Author

Listed:
  • Firuz Kamalov

    (Canadian University Dubai)

  • David Santandreu Calonge

    (Mohamed Bin Zayed University of Artificial Intelligence)

  • Patrik T. Hultberg

    (Kalamazoo College)

  • Linda Smail

    (Zayed University)

  • Dima Jamali

    (Canadian University Dubai)

Abstract

Artificial intelligence (AI) chatbots show remarkable abilities across applications. Despite a growing literature, their capability in the field of entrepreneurship is not fully understood. The aim of this study is to empirically evaluate and compare capabilities of five major AI chatbots—GPT-3.5, GPT-4, Gemini 1.0, Llama 2, and Claude—in the context of entrepreneurship theory, using a benchmark entrepreneurship test. In particular, the performance of the chatbots on a set of multiple-choice questions, short-answer questions, and essay questions related to entrepreneurship is assessed. The results indicate that GPT-4 delivers the strongest overall performance. Meanwhile, Llama 2 offers precise responses with a significantly lower word count compared to the GPT models. Although chatbots do not always provide correct or precise answers to questions or complex prompts, they still prove to be valuable analytical tools for entrepreneurs. While the study offers compelling insights into chatbots’ grasp of entrepreneurship concepts, the findings are somewhat limited by the scarce availability of data.

Suggested Citation

  • Firuz Kamalov & David Santandreu Calonge & Patrik T. Hultberg & Linda Smail & Dima Jamali, 2025. "Comparative analysis of leading artificial intelligence chatbots in the context of entrepreneurship," Journal of Innovation and Entrepreneurship, Springer, vol. 14(1), pages 1-27, December.
  • Handle: RePEc:spr:joiaen:v:14:y:2025:i:1:d:10.1186_s13731-025-00527-3
    DOI: 10.1186/s13731-025-00527-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s13731-025-00527-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1186/s13731-025-00527-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:spr:joiaen:v:14:y:2025:i:1:d:10.1186_s13731-025-00527-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.