# Will bots take over the supply chain? Revisiting Agent-based supply chain automation

arXiv: https://arxiv.org/abs/2109.01703 · HTML: https://mlsanity.com/paper/2109.01703/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 161 references that are in the map.
- First posted on arXiv 3 Sep 2021.

## Builds on (most cited first, 1 of 1)

- [A Review of Platforms for the Development of Agent Systems](https://mlsanity.com/paper/2007.08961/) (2020)

## Built on by (most cited first, 7 of 7)

- [From Glue-Code to Protocols: A Critical Analysis of A2A and MCP Integration for Scalable Agent Systems](https://mlsanity.com/paper/2505.03864/) (2025)
- [Fair collaborative vehicle routing: A deep multi-agent reinforcement learning approach](https://mlsanity.com/paper/2310.17485/) (2023)
- [Towards Autonomous Supply Chains: Definition, Characteristics, Conceptual Framework, and Autonomy Levels](https://mlsanity.com/paper/2401.14183/) (2023)
- [Helicase: Uncertainty-Guided Supply Chain Knowledge Graph Construction with Autonomous Multi-Agent LLMs](https://mlsanity.com/paper/2605.26835/) (2026)
- [LLM Agents for Combinatorial Efficient Frontiers: Investment Portfolio Optimization](https://mlsanity.com/paper/2601.00770/) (2026)
- [Agentic AI Autonomy Assessment: A Decision-Support Framework Towards Governed Supply Chain Systems](https://mlsanity.com/paper/2607.25405/) (2026)
- [A Hybrid Agentic AI Framework for Intelligent Supply Chain Analytics](https://mlsanity.com/paper/2609.13561/) (2026)

## Abstract (arXiv)

Agent-based systems have the capability to fuse information from many distributed sources and create better plans faster. This feature makes agent-based systems naturally suitable to address the challenges in Supply Chain Management (SCM). Although agent-based supply chains systems have been proposed since early 2000; industrial uptake of them has been lagging. The reasons quoted include the immaturity of the technology, a lack of interoperability with supply chain information systems, and a lack of trust in Artificial Intelligence (AI). In this paper, we revisit the agent-based supply chain and review the state of the art. We find that agent-based technology has matured, and other supporting technologies that are penetrating supply chains; are filling in gaps, leaving the concept applicable to a wider range of functions. For example, the ubiquity of IoT technology helps agents "sense" the state of affairs in a supply chain and opens up new possibilities for automation. Digital ledgers help securely transfer data between third parties, making agent-based information sharing possible, without the need to integrate Enterprise Resource Planning (ERP) systems. Learning functionality in agents enables agents to move beyond automation and towards autonomy. We note this convergence effect through conceptualising an agent-based supply chain framework, reviewing its components, and highlighting research challenges that need to be addressed in moving forward.