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

Feb 2, 2025·
Md Monjurul Karim, Dong Hoang Van, Sangeen Khan, Qiang Qu and Yaroslav Kholodov
· 2 min read
Abstract
In this paper, we illustrate 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.
Publication
Future Internet (JCR-Q2, 2023 IF 2.8)

Brief Summary

This paper presents a comprehensive survey on the integration of AI agents and blockchain, addressing the challenges and opportunities in secure and scalable multi-agent collaboration. The novelty of this study lies in its exploration of the intersection between decentralized AI (DeAI) and blockchain, emphasizing how AI agents enhance blockchain-based ecosystems through decision-making, consensus optimization, and autonomous collaboration. Unlike previous works that focus on either blockchain security or AI trustworthiness in isolation, this survey offers an integrated perspective on their synergistic relationship.

The paper solves key challenges related to interoperability, scalability, and privacy in decentralized environments. It highlights how AI agents can improve the efficiency of blockchain consensus mechanisms, reduce transaction latency, and optimize resource allocation. Furthermore, the study discusses blockchain’s role in ensuring secure agent interactions through decentralized governance, immutable audit trails, and cryptographic safeguards. By categorizing various applications across domains such as Web3, DeFi, asset management, and autonomous systems, the survey provides insights into real-world implementations of AI-agent-enhanced blockchain solutions.

In terms of contributions, the paper systematically evaluates AI agents’ impact on blockchain scalability, security, and operational efficiency. It introduces zero-shot learning for AI-driven blockchain operations, explores novel intelligent consensus mechanisms like Proof-of-Thought (PoT) and Proof-of-Compute (PoC), and discusses practical use cases in DeFi governance, DAO automation, and decentralized supply chain management. The paper also identifies future directions, including decentralized quantum computing, privacy-preserving AI-agent coordination, and self-sovereign AI agent governance.

Overall, this study bridges the gap between AI-driven decision-making and blockchain-based security, positioning AI agents as fundamental components in next-generation decentralized ecosystems. It serves as a critical reference for researchers and practitioners looking to explore scalable and secure AI-agent-blockchain integrations.