Blockchain-based Trust Mechanisms for Artificial Intelligence Agents: A Brief Survey

Abstract

Artificial intelligence agents have evolved from passive content generators into autonomous execution systems capable of invoking external tools, coordinating with peer agents, and conducting transactions across organizational boundaries. Existing security mechanisms, however, are designed primarily for single-agent threat models within single-organization deployments, offering no shared substrate for establishing trust in multi-agent, cross-organizational contexts. Blockchain has been proposed as such a substrate, given its capacity for decentralized identity anchoring, tamper-evident audit trails, and programmable authorization, yet the extent to which it can support trust across the full agent lifecycle, from identity establishment to execution verification, remains insufficiently examined. This survey offers a structured analysis of blockchain-based trust mechanisms for AI agents, organized around a five-layer lifecycle taxonomy: identity, authorization, behavioral control, audit, and execution verification. Using this lifecycle framework, we arrive at a central finding: while individual mechanisms achieve promising results within specific layers, no integrated system has yet demonstrated the complete trust lifecycle in a production-validated setting. On this basis, we delineate the systemic gaps constituting the current research frontier, and outline promising directions for future work at the intersection of blockchain and AI agent trust.