IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-05400153.html

AI-Powered Leadership in Supply Chain Management: Balancing Efficiency and Human Decision-Making

Author

Listed:
  • Abdullah Sheikh

    (Wright State University, Dayton, OH, USA.)

Abstract

Global supply chains are increasingly complex and volatile, and new leadership paradigms require effective integration of artificial intelligence (AI) and human decision-making. While AI-driven forecasting and analytics provide unprecedented opportunities for efficiency and risk reduction, successful deployments require more than technical abilities. This research addresses a critical gap by proposing a conceptual framework for AI-powered leadership in supply chain management, where AI functions as an intelligent advisor that improves human judgment rather than replacing it. The framework demonstrates through case studies that organizations achieving Stage 5 maturity (Cognitive/Autonomous) in the proposed SCM Analytical Maturity Model show 20-30% improvement in operational efficiency while maintaining ethical governance. Results indicate that balanced AI-human collaboration enables faster, more informed decisions while maintaining accountability and ensuring fairness. The findings provide a strategic roadmap for enhancing supply chain resilience and global competitiveness in the Industry 5.0 era.

Suggested Citation

  • Abdullah Sheikh, 2025. "AI-Powered Leadership in Supply Chain Management: Balancing Efficiency and Human Decision-Making," Post-Print hal-05400153, HAL.
    • Handle: RePEc:hal:journl:hal-05400153
    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.

    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:hal:journl:hal-05400153. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.