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

Abdullah Sheikh
Additional contact information
Abdullah Sheikh: Wright State University, Dayton, OH, USA.

Post-Print from HAL

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.

Date: 2025-12-03
References: Add references at CitEc
Citations:

Published in Journal of Global Economics, Management and Business Research, 2025, 17 (3), pp.476-485

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05400153

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().