IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-080-0_24.html

Artificial Intelligence Augmented Project Management

In: Proceedings of the International Conference on Technology and Innovation Management (ICTIM 2022)

Author

Listed:
  • Muhammad Hisham Salleh

    (Menara TM One
    Multimedia University, Faculty of Management)

  • Kamarulzaman Ab. Aziz

    (Multimedia University, Faculty of Business)

Abstract

Project Management (PM) is a critical function for organizations and businesses. Whilst projects are important and continue to be important, the failure rate is still alarmingly high. The emerging technologies in this Fourth Industrial Revolution (IR 4.0) era, particularly Artificial Intelligence (AI) continues to grow rapidly around the globe. This trend is fueled by technological advancements such as decreasing computational cost, increasing communication speed, inexpensive sensors, and advanced materials. The importance of AI-based project management is acknowledged by practitioners and there is a recognition of how these technology evolutions can enhance project management functions. However, little is known about AI requirements and implementation in project management. The most important question is how to implement AI in project management as the domain knowledge itself is difficult & highly complex. At present, there is no widely recognized model or framework for coming up with AI applications in Project Management. This research intends to address this research gap by proposing possible use cases for AI-augmented PM (AI-PM). It is envisioned that this research will pave the way toward the development of a suitable framework and generate findings that will benefit developers as well as users.

Suggested Citation

  • Muhammad Hisham Salleh & Kamarulzaman Ab. Aziz, 2022. "Artificial Intelligence Augmented Project Management," Advances in Economics, Business and Management Research, in: Arnifa Asmawi (ed.), Proceedings of the International Conference on Technology and Innovation Management (ICTIM 2022), pages 274-284, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-080-0_24
    DOI: 10.2991/978-94-6463-080-0_24
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Huan Cai & Ziqing Lu & Catherine Xu & Weiyu Xu & Jie Zheng, 2026. "Artificial Superintelligence May be Useless: Equilibria in the Economy of Multiple AI Agents," Papers 2603.00858, arXiv.org.

    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:spr:advbcp:978-94-6463-080-0_24. 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.