IDEAS home Printed from https://ideas.repec.org/a/bjf/journl/v10y2025i7p1425-1430.html
   My bibliography  Save this article

Exploring the Potential and Limitations of Artificial Intelligence and Machine Learning in Improving Decision-Making Processes in Various Industries

Author

Listed:
  • Adeleye Dupe Ayesha

    (International Islamic University, Malaysia)

  • Prof. Abd. Rahman Ahlan

    (International Islamic University, Malaysia)

  • Dr. Najhan Muhamad Ibrahim

    (International Islamic University, Malaysia)

  • Bello Bariz Holaitan

    (International Islamic University, Malaysia)

  • Yusuf Abdulkadir

    (International Islamic University, Malaysia)

  • Alijafar Umar

    (International Islamic University, Malaysia)

  • Abdulrahman Usman Liman

    (International Islamic University, Malaysia)

Abstract

The study assesses the application of AI and ML in decision-making across four sectors: healthcare, banking, manufacturing, and retail. To measure the utilization in actual situations, the form of a mixed method unites expert interviews and questionnaires with simulated case studies. AI and ML serve to improve the accuracy of predictions, automate routine tasks, and customize processes. But there are issues with providing assurance information is unbiased and with model transparency and ethics concerns. Towards this end, the study advocates for implementing industry-specific regulations and human-machine collaboration in realizing optimal benefits optimally in a fair manner while limiting associated risks. Thus, the analysis’ top priority is still in adopting responsible and ethical approaches under each sector’s framework.

Suggested Citation

  • Adeleye Dupe Ayesha & Prof. Abd. Rahman Ahlan & Dr. Najhan Muhamad Ibrahim & Bello Bariz Holaitan & Yusuf Abdulkadir & Alijafar Umar & Abdulrahman Usman Liman, 2025. "Exploring the Potential and Limitations of Artificial Intelligence and Machine Learning in Improving Decision-Making Processes in Various Industries," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 10(7), pages 1425-1430, July.
    • Handle: RePEc:bjf:journl:v:10:y:2025:i:7:p:1425-1430
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijrias/digital-library/volume-10-issue-7/1425-1430.pdf
    Download Restriction: no
    File URL: https://rsisinternational.org/journals/ijrias/articles/exploring-the-potential-and-limitations-of-artificial-intelligence-and-machine-learning-in-improving-decision-making-processes-in-various-industries/
    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:bjf:journl:v:10:y:2025:i:7:p:1425-1430. 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: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrias/ .

    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.