Web3 x AI Agents: Landscape, Integrations, and Foundational Challenges
Yiming Shen, Jiashuo Zhang, Zhenzhe Shao, Wenxuan Luo, Yanlin Wang, Ting Chen, Zibin Zheng, Jiachi Chen

TL;DR
This paper provides a comprehensive analysis of the Web3 and AI agents intersection, exploring five key dimensions, analyzing 133 projects, and identifying integration patterns and foundational challenges for future decentralized systems.
Contribution
It offers the first systematic taxonomy and mapping of Web3-AI integrations, highlighting key patterns and foundational challenges in security, governance, and trust.
Findings
Identified distinct project distribution and capitalization patterns.
Analyzed AI roles in DeFi, governance, and security enhancements.
Outlined critical challenges in scalability, security, and ethics.
Abstract
The convergence of Web3 technologies and AI agents represents a rapidly evolving frontier poised to reshape decentralized ecosystems. This paper presents the first and most comprehensive analysis of the intersection between Web3 and AI agents, examining five critical dimensions: landscape, economics, governance, security, and trust mechanisms. Through an analysis of 133 existing projects, we first develop a taxonomy and systematically map the current market landscape (RQ1), identifying distinct patterns in project distribution and capitalization. Building upon these findings, we further investigate four key integrations: (1) the role of AI agents in participating in and optimizing decentralized finance (RQ2); (2) their contribution to enhancing Web3 governance mechanisms (RQ3); (3) their capacity to strengthen Web3 security via intelligent vulnerability detection and automated smart…
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