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Autonomous Supply Chains

Yunbo Long 540 words 3 minutes Multi-Agent LLM Automation

Autonomous supply chains (ASCs) represent a transformative direction in supply chain management, where decision-making, execution, and continuous learning are increasingly enabled by intelligent systems—with minimal human intervention. Powered by advances in artificial intelligence (particularly large language models and AI agents), the Internet of Things (IoT), and digital twins, ASCs aim to deliver real-time responsiveness, resilience, and operational efficiency across increasingly complex and dynamic networks.

In contrast to traditional supply chains—often reliant on manual coordination and rigid planning—ASCs are designed to sense, interpret, and act on data streams in real time. Capabilities such as adaptive demand forecasting, automated procurement, self-optimising logistics, and predictive risk management illustrate the shift from reactive to proactive operations.

Recent scholarly work—led by researchers such as Dr Yunbo Long and Prof Alexandra Brintrup—has laid the conceptual foundation for this field. Their research introduces formal definitions and a framework outlining multiple levels of autonomy in supply chains, from basic automation to fully autonomous systems. These levels offer organisations a roadmap for evaluating and advancing their autonomy capabilities.

For new researchers and PhD students, ASCs present a rich landscape of socio-technical questions, including trust in AI systems, data interoperability, organisational readiness, and the ethical dimensions of automation. As industries seek smarter, more resilient, and more sustainable solutions, autonomous supply chains are rapidly emerging as a key area for research, innovation, and long-term impact.

We invite you to explore our curated collection of key publications below, offering a gateway into this exciting and evolving field.

List of Publications

  1. Xu, L., Mak, S., Proselkov, Y. and Brintrup, A., 2024. Towards autonomous supply chains: Definition, characteristics, conceptual framework, and autonomy levels. Journal of Industrial Information Integration, 42, p.100698. [PDF]
  2. Xu, L., Mak, S., Minaricova, M. and Brintrup, A., 2024. On implementing autonomous supply chains: A multi-agent system approach. Computers in Industry, 161, p.104120. [PDF]
  3. Xu, L., Almahri, S., Mak, S. and Brintrup, A., 2024. Multi-agent systems and foundation models enable autonomous supply chains: Opportunities and challenges. IFAC-PapersOnLine, 58(19), pp.795-800. [PDF]
  4. Nitsche, B., 2021. Exploring the Potentials of automation in logistics and supply chain management: Paving the way for autonomous supply chains. Logistics, 5(3), p.51. [PDF]
  5. Calatayud, A., Mangan, J. and Christopher, M., 2019. The self-thinking supply chain. Supply Chain Management: An International Journal, 24(1), pp.22-38. [PDF]
  6. Wu, L., Yue, X., Jin, A. and Yen, D.C., 2016. Smart supply chain management: a review and implications for future research. The international journal of logistics management, 27(2), pp.395-417. [PDF]
  7. Butner, K., 2010. The smarter supply chain of the future. Strategy & leadership, 38(1), pp.22-31. [PDF]