IDEAS home Printed from https://ideas.repec.org/a/etm/ijsrst/v11y2024i4id304.html

A Review of AI and ML Adoption in Businesses Worldwide

Author

Listed:
  • Nithyananda B Devadiga

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are the two emerging technologies adopted by most of the business companies worldwide. The use of advanced technologies is highly effective on businesses and capable of improving overall performance of companies. Examining the potential effects, opportunities, challenges and scopes of adopting AI and ML in businesses worldwide is the main purpose of this study. In regard to this, secondary qualitative methods have been used for gathering authentic and reliable data from several scholarly articles and peer-reviewed journals. All the findings are discussed briefly and it has been identified that AI and ML have great influence towards workplace efficiency, productivity and profitability of business companies. It also helps to boost customer satisfaction and gain competitiveness in the global market.

Suggested Citation

  • Nithyananda B Devadiga, 2024. "A Review of AI and ML Adoption in Businesses Worldwide," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 11(4), pages 393-399, August.
    • Handle: RePEc:etm:ijsrst:v11:y2024:i4:id:304
    DOI: 10.32628/IJSRST24114136
    as

    Download full text from publisher

    File URL: https://ijsrst.com/home/article/view/IJSRST24114136
    File Function: Abstract page
    Download Restriction: no
    File URL: https://ijsrst.com/home/article/download/IJSRST24114136/IJSRST24114136
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.32628/IJSRST24114136?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:etm:ijsrst:v11:y2024:i4:id:304. 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: Pankaj Sharma (email available below). General contact details of provider: https://ijsrst.com/home .

    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.