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AI Agents Meet Blockchain: A Survey on Secure and Scalable Collaboration for Multi-Agents

Author

Listed:
  • Md Monjurul Karim

    (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China)

  • Dong Hoang Van

    (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China)

  • Sangeen Khan

    (Department of Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Qiang Qu

    (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China)

  • Yaroslav Kholodov

    (Faculty of Computer Science and Engineering, Innopolis University, 420500 Innopolis, Russia)

Abstract

In recent years, the interplay between AI agents and blockchain has enabled secure and scalable collaboration among multi-agent systems, promoting unprecedented levels of autonomy and interoperability. AI agents play a vital role in facilitating complex decision making and improving operational efficiency in blockchain systems. This collaborative synergy is particularly evident in how multi-agent systems collectively tackle complex tasks to ensure seamless integration within these frameworks. While significant efforts have been made to integrate AI agents and blockchain, most studies overlook the broader potential of AI agents in addressing challenges such as interoperability, scalability, and privacy issues. In this paper, we bridge these gaps by illustrating the interplay between AI agents and blockchain. Specifically, we explore how AI agents enhance decentralized systems and examine blockchain’s role in enabling secure and scalable collaboration. Furthermore, we categorize practical applications across domains, such as Web3, decentralized finance (DeFi), asset management, and autonomous systems, providing practical insights and real-world use cases. Additionally, we identify key research challenges, including the complexities of multi-agent coordination, interoperability across diverse systems, and privacy maintenance in decentralized frameworks. Finally, we offer future directions in terms of governance, sovereignty, computation, and interpretability to promote a secure and responsible ecosystem.

Suggested Citation

  • Md Monjurul Karim & Dong Hoang Van & Sangeen Khan & Qiang Qu & Yaroslav Kholodov, 2025. "AI Agents Meet Blockchain: A Survey on Secure and Scalable Collaboration for Multi-Agents," Future Internet, MDPI, vol. 17(2), pages 1-30, February.
    • Handle: RePEc:gam:jftint:v:17:y:2025:i:2:p:57-:d:1582291
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    References listed on IDEAS

    as
    1. Andrei Tara & Hjalmar K. Turesson & Nicolae Natea, 2024. "Dynamic Storage Optimization for Communication between AI Agents," Future Internet, MDPI, vol. 16(8), pages 1-13, August.
    2. Abhimanyu Nag & Samrat Gupta & Sudipan Sinha & Arka Datta, 2024. "Multi Agent Influence Diagrams for DeFi Governance," Papers 2402.15037, arXiv.org, revised Oct 2024.
    3. Eleftheria Papageorgiou & Christos Chronis & Iraklis Varlamis & Yassine Himeur, 2024. "A Survey on the Use of Large Language Models (LLMs) in Fake News," Future Internet, MDPI, vol. 16(8), pages 1-29, August.
    4. Andry Alamsyah & Gede Natha Wijaya Kusuma & Dian Puteri Ramadhani, 2024. "A Review on Decentralized Finance Ecosystems," Future Internet, MDPI, vol. 16(3), pages 1-29, February.
    5. Igor Calzada, 2024. "Decentralized Web3 Reshaping Internet Governance: Towards the Emergence of New Forms of Nation-Statehood?," Future Internet, MDPI, vol. 16(10), pages 1-29, October.
    6. Yao Du & Zehua Wang & Cyril Leung & Victor C. M. Leung, 2024. "Towards Collaborative Edge Intelligence: Blockchain-Based Data Valuation and Scheduling for Improved Quality of Service," Future Internet, MDPI, vol. 16(8), pages 1-23, July.
    Full references (including those not matched with items on IDEAS)

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