The Application of Artificial Intelligence in Supply Chain Management: A Case Study of Amazon
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The Application of Artificial Intelligence in Supply Chain Management: A Case Study of Amazon

Tianyu Luo 1*
1 University of Warwick
*Corresponding author: luotianyu0328@163.com
Published on 4 July 2025
Volume Cover
AEMPS Vol.195
ISSN (Print): 2754-1177
ISSN (Online): 2754-1169
ISBN (Print): 978-1-80590-169-3
ISBN (Online): 978-1-80590-170-9
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Abstract

With the rapid development of global information technology, supply chain management has transitioned from traditional models to AI-driven intelligent systems. The application of artificial intelligence (AI) in supply chain management has become a key factor in enhancing corporate competitiveness. As a leading e-commerce platform, Amazon extensively integrates AI technologies into its supply chain, significantly improving operational efficiency and cost control. This paper examines how Amazon leverages AI to optimize various aspects of its supply chain, focusing on demand forecasting, warehouse automation, intelligent algorithms, and robotics. The study finds that the application of artificial intelligence has significantly enhanced Amazon's efficiency and cost control in supply chain management, including improvements in customer demand and other areas. However, in the face of a complex market environment, Amazon still needs to address challenges related to customer privacy, technology integration, and handling emergencies. This paper provides reference value for global e-commerce companies, explores the potential of artificial intelligence in supply chain management, and offers insights for future research.

Keywords:

Artificial Intelligence, Supply Chain Management, Amazon, E-Commerce

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Luo,T. (2025). The Application of Artificial Intelligence in Supply Chain Management: A Case Study of Amazon. Advances in Economics, Management and Political Sciences,195,192-198.

References

[1]. Gartner. (2022). The Role of AI in Supply Chain Digital Transformation. Retrieved March 10, 2025, from https://www. gartner. com

[2]. Amazon Web Services. (2023). 2023 supply chain optimization & AI integration report. Retrieved March 10, 2025, from https://aws. amazon. com/whitepapers/2023-supply-chain-ai-report/

[3]. Financial Times. (2024, January 15). Amazon bets on AI to optimize supply chain efficiency. Financial Times. Retrieved March 10, 2025, from https://www. ft. com

[4]. Murphy, K. P. (2022). Probabilistic Machine Learning: An Introduction. MIT Press.

[5]. Hastie, T. , Tibshirani, R. , & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed. ). Springer.

[6]. Business Insider. (2023, December 12). Amazon's AI-powered robotics could cut $10 billion in costs by 2030. Business Insider. Retrieved March 10, 2025, from https://www. businessinsider. com

[7]. MIT Technology Review. (2023, September 22). Amazon's AI supply chain strategy: Strengths and challenges. MIT Technology Review. Retrieved March 10, 2025, from https://www. technologyreview. com

[8]. Dehghan, A. , Cevik, M. , & Bodur, M. (2023). Dynamic AGV task allocation in intelligent warehouses. arXiv preprint arXiv:2312. 16026.

[9]. McKinsey & Company. (2023). AI in supply chain: The next big leap. Retrieved March 10, 2025, from https://www. mckinsey. com

[10]. World Economic Forum. (2023). How AI is revolutionizing supply chains. Retrieved March 10, 2025, from https://www. weforum. org

[11]. European Commission. (2023). AI and data regulations in supply chain management. Brussels: European Commission. Retrieved March 10, 2025, from https://ec. europa. eu

[12]. U. S. Federal Trade Commission. (2023). Data privacy and AI in logistics. Washington, D. C. : FTC. Retrieved March 10, 2025, from https://www. ftc. gov

References

[1]. Gartner. (2022). The Role of AI in Supply Chain Digital Transformation. Retrieved March 10, 2025, from https://www. gartner. com

[2]. Amazon Web Services. (2023). 2023 supply chain optimization & AI integration report. Retrieved March 10, 2025, from https://aws. amazon. com/whitepapers/2023-supply-chain-ai-report/

[3]. Financial Times. (2024, January 15). Amazon bets on AI to optimize supply chain efficiency. Financial Times. Retrieved March 10, 2025, from https://www. ft. com

[4]. Murphy, K. P. (2022). Probabilistic Machine Learning: An Introduction. MIT Press.

[5]. Hastie, T. , Tibshirani, R. , & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed. ). Springer.

[6]. Business Insider. (2023, December 12). Amazon's AI-powered robotics could cut $10 billion in costs by 2030. Business Insider. Retrieved March 10, 2025, from https://www. businessinsider. com

[7]. MIT Technology Review. (2023, September 22). Amazon's AI supply chain strategy: Strengths and challenges. MIT Technology Review. Retrieved March 10, 2025, from https://www. technologyreview. com

[8]. Dehghan, A. , Cevik, M. , & Bodur, M. (2023). Dynamic AGV task allocation in intelligent warehouses. arXiv preprint arXiv:2312. 16026.

[9]. McKinsey & Company. (2023). AI in supply chain: The next big leap. Retrieved March 10, 2025, from https://www. mckinsey. com

[10]. World Economic Forum. (2023). How AI is revolutionizing supply chains. Retrieved March 10, 2025, from https://www. weforum. org

[11]. European Commission. (2023). AI and data regulations in supply chain management. Brussels: European Commission. Retrieved March 10, 2025, from https://ec. europa. eu

[12]. U. S. Federal Trade Commission. (2023). Data privacy and AI in logistics. Washington, D. C. : FTC. Retrieved March 10, 2025, from https://www. ftc. gov

Cite this article

Luo,T. (2025). The Application of Artificial Intelligence in Supply Chain Management: A Case Study of Amazon. Advances in Economics, Management and Political Sciences,195,192-198.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICMRED 2025 Symposium: Effective Communication as a Powerful Management Tool

ISBN: 978-1-80590-169-3(Print) / 978-1-80590-170-9(Online)
Editor: Lukáš Vartiak
Conference website: https://2025.icmred.org/Bratislava.html
Conference date: 30 May 2025
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.195
ISSN: 2754-1169(Print) / 2754-1177(Online)

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