Digital Transformation in Supply Chain Management: Artificial Intelligence (AI) and Machine Learning (ML) as Catalysts for Value Creation
Open accessAbstract
In the rapidly evolving landscape of supply chain management (SCM), digital transformation has become a cornerstone for achieving competitive advantage. This paper explores the pivotal role of Artificial Intelligence (AI) and Machine Learning (ML) as catalysts in this transformation, driving significant value creation across various facets of SCM. Through a comprehensive literature review, including an analysis of 12 key papers, this study examines the integration of AI and ML in enhancing supply chain operations, from predictive analytics in demand forecasting to real-time decision-making in logistics and inventory management. The findings highlight the transformative impact of these technologies in optimizing efficiency, reducing costs, and improving overall supply chain resilience. The paper also addresses the challenges and ethical considerations inherent in implementing AI and ML, such as data privacy and workforce implications. Concluding with a look towards the future, this study underscores the growing importance of AI and ML in shaping the next generation of SCM practices. This research not only contributes to the academic discourse on digital supply chain transformation but also offers practical insights for industry professionals navigating this digital shift.
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Embedding AI in supply chain management helps reach sustainability targets by minimizing operational costs and enhancing organizational performance.
“The embedding of AI in supply chain management aids in the reaching of sustainability targets because it minimizes operational costliness and enhances organizational performance53,54.”
From A decision-support framework for evaluating AI-enabled ESG strategies in the context of sustainable manufacturing systems (2025) · cites this paper as [53]
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- Authors
- Singh, P. K.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Singh, Pratyush Kumar
- Venue
- International Journal of Supply Chain Management
- Publisher
- ExcelingTech
- Published
- 2023-12-30
- Volume
- 12
- Issue
- 6
- Pages
- 57-63
- ISSN
- 2050-7399 (ISSN-L)
- 2051-3771
- OpenAlex
- W4390442894
- Cited by
- 58
- References
- 8
- Citations by year
- 2026: 13 · 2025: 32 · 2024: 13
- FWCI
- 10.69
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by-nc
- Locations
- International Journal of Supply Chain Management (publishedVersion, cc-by-nc)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Business, Management and Accounting › Management Information Systems › Supply Chain and Inventory Management
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Keywords
- digital transformation, supply chain management, artificial intelligence, machine learning, value creation, demand forecasting, predictive analytics, logistics decision-making, inventory management, supply chain resilience, data privacy, workforce implications, ethical considerations
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