IDEAS home Printed from https://ideas.repec.org/a/bjf/ijltem/v15y2026i3a2280.html

A Study on the Influence of AI on Time Optimization of HR Functions

Author

Listed:
  • Rishashri M

    (MSW HRM student, Madras School of Social Work)

  • Mr. Vasantha Jayaseelan

    (Assistant Professor, Madras School of Social Work)

Abstract

This study examines the influence of Artificial Intelligence (AI) on time optimization within Human Resource (HR) functions, focusing on how AI-driven tools enhance efficiency and organizational outcomes. With HR departments increasingly expected to act as strategic partners, the integration of AI helps automate repetitive tasks such as recruitment, payroll, and performance management, thereby reducing time consumption and improving decision-making. Using a descriptive research design, data was collected from 70\ HR professionals in IT companies in Chennai through a structured questionnaire. The study highlights that AI significantly improves time efficiency, enabling HR professionals to focus more on strategic and employee-centric roles. It also addresses concerns related to adoption, ethical considerations, and human acceptance, emphasizing the need for a balanced, human-cantered approach. Overall, the research contributes to understanding how AI-powered time optimization can transform HR functions and support organizational effectiveness.

Suggested Citation

  • Rishashri M & Mr. Vasantha Jayaseelan, 2026. "A Study on the Influence of AI on Time Optimization of HR Functions," International Journal of Latest Technology in Engineering, Management & Applied Science, RSIS International, vol. 15(3), pages 1364-1381, March.
  • Handle: RePEc:bjf:ijltem:v:15:y:2026:i:3:a:2280
    DOI: 10.51583/IJLTEMAS.2026.150300118
    as

    Download full text from publisher

    File URL: https://www.ijltemas.in/submission/online/article/view/4455/6016
    Download Restriction: no

    File URL: https://www.ijltemas.in/submission/online/article/view/4455
    Download Restriction: no

    File URL: https://libkey.io/10.51583/IJLTEMAS.2026.150300118?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

    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:ijltem:v:15:y:2026:i:3:a:2280. 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. Pawan Verma (email available below). General contact details of provider: https://www.ijltemas.in/ .

    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.