Toward Web 4.0: Bidirectional Trust between AI Agents and Blockchain

2026-05-09

AI Summary

This study addresses the absence of a bidirectional trust mechanism between AI agents and blockchain systems, which has led to ambiguous interaction designs, missing standards, and inadequate security frameworks. To bridge this gap, the work proposes the first Agent-Blockchain Interaction Model (ABIM), introducing a five-dimensional evaluation framework that treats AI agents as first-class participants at the protocol layer. Leveraging verifiable computation, the model integrates account abstraction, intent-centric execution, tokenized economics, consensus mechanisms, and on-chain governance to systematically analyze how blockchains can provide AI agents with identity, permissioning, and economic infrastructure, while also exploring the roles of AI in security auditing, consensus, and governance. Through a comprehensive review of 70 Ethereum EIPs/ERCs, 20 industry projects, and 118 academic works, the study identifies critical gaps—including immature standardization ecosystems and the lack of formal analysis for intent-based architectures—and delineates nine open research problems.

Abstract

Autonomous AI agents are increasingly deployed on blockchain platforms, yet the design space that governs their interaction remains poorly understood. This convergence, where autonomous agents operate on and within decentralized systems, is a defining feature of the emerging Web~4.0 paradigm. This paper presents a Systematization of Knowledge organized around a bidirectional trust framework. In the B $\boldsymbol{\rightarrow}$ A direction, we examine how blockchain provides trust infrastructure for agents, spanning identity and account abstraction, permission and delegation, intent-centric execution, and tokenized agent economies. In the A $\boldsymbol{\rightarrow}$ B direction, we examine the reverse: how AI agents participate in core blockchain mechanisms including security auditing, consensus, and governance. A Trust Foundation of verifiable computation underpins both directions, with each primitive offering different trade-offs between trust minimality, computational overhead, and deployment readiness. We formalize the interaction as an Agent-Blockchain Interaction Model (ABIM), catalog 70 Ethereum EIPs/ERCs, examine 20 representative industry projects, and review 118 academic papers, applying a five-dimensional framework assessing Verifiability, Minimality of Trust, Expressiveness, Composability, and Maturity. Our analysis uncovers significant gaps: the agent-specific standards ecosystem is overwhelmingly immature, intent architectures lack formal analysis, and while isolated works have begun to explore AI participation in consensus and governance, a unified security framing that treats AI as a first-class actor at the protocol layer remains absent. We propose a three-dimensional taxonomy, identify nine concrete open problems, and highlight the sharpest research opportunities at this intersection.

Problem

• AI Agents
• Blockchain
• Trust
• Web 4.0
• Decentralized Systems

Innovation

• bidirectional trust
• AI agents
• blockchain
• verifiable computation
• Web 4.0