IDEAS home Printed from https://ideas.repec.org/a/bum/cactus/v5y2023i1p53-63.html
   My bibliography  Save this article

Business Use: Is Ai Surpassing Human Creativity?

Author

Listed:
  • Andrei Daniel Niculae

    (Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

This study aims to assess people’s perceptions regarding AI-generated images compared to those made by humans. This study used quantitative research in the form of a survey to find out how much respondents prefer AI-generated images. The findings indicated that most respondents favoured artificial intelligence (AI)- generated visuals. Age and time spent online were key determinants of this choice. These discoveries have important implications for organisations and people who produce and consume visual content in their jobs. It implies that as people become familiar to them and as technology advances, AI-generated images are likely to gain popularity in the future. It also emphasises how critical it is to be aware of audience preferences and adjust to the evolving state of technology and visual media. In conclusion, this study offers insightful information about the prospective effects of AI-generated images on the creative sectors and the larger society.

Suggested Citation

  • Andrei Daniel Niculae, 2023. "Business Use: Is Ai Surpassing Human Creativity?," Cactus - The tourism journal for research, education, culture and soul, Bucharest University of Economic Studies, vol. 5(1), pages 53-63.
    • Handle: RePEc:bum:cactus:v:5:y:2023:i:1:p:53-63
    as

    Download full text from publisher

    File URL: https://www.cactus-journal-of-tourism.ase.ro/Pdf/vol_5_1/II_5.Niculae.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Artificial Intelligence; Artificial Intelligence Tools; AI-generated images; Human perception; Images;
    All these keywords.

    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

    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:bum:cactus:v:5:y:2023:i:1:p:53-63. 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: Daniel Bulin (email available below). General contact details of provider: https://edirc.repec.org/data/fcasero.html .

    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.