The Potential of Large Language Models in Supply Chain Management: Advancing Decision-Making, Efficiency, and Innovation
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Abstract (arXiv)
The integration of large language models (LLMs) into supply chain management (SCM) is revolutionizing the industry by improving decision-making, predictive analytics, and operational efficiency. This white paper explores the transformative impact of LLMs on various SCM functions, including demand forecasting, inventory management, supplier relationship management, and logistics optimization. By leveraging advanced data analytics and real-time insights, LLMs enable organizations to optimize resources, reduce costs, and improve responsiveness to market changes. Key findings highlight the benefits of integrating LLMs with emerging technologies such as IoT, blockchain, and robotics, which together create smarter and more autonomous supply chains. Ethical considerations, including bias mitigation and data protection, are taken into account to ensure fair and transparent AI practices. In addition, the paper discusses the need to educate the workforce on how to manage new AI-driven processes and the long-term strategic benefits of adopting LLMs. Strategic recommendations for SCM professionals include investing in high-quality data management, promoting cross-functional collaboration, and aligning LLM initiatives with overall business goals. The findings highlight the potential of LLMs to drive innovation, sustainability, and competitive advantage in the ever-changing supply chain management landscape.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Jan 2025.
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Citing papers per year: 2025: 2; 2026: 1.
3 papers.
- 2025A Detailed Study on LLM Biases Concerning Corporate Social Responsibility and Green Supply Chainscited by 0
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- 2025Strategic Innovation Management in the Age of Large Language Models Market Intelligence, Adaptive R&D, and Ethical Governance18 Nov 2025
- 2025A Detailed Study on LLM Biases Concerning Corporate Social Responsibility and Green Supply Chains3 Nov 2025