AI-Governed Agent Architecture for Web-Trustworthy Tokenization of Alternative Assets
Ailiya Borjigin, Wei Zhou, Cong He

TL;DR
This paper introduces an AI-governed multi-agent architecture integrating blockchain to enhance trustworthiness, security, and compliance in web-based tokenization of alternative assets, demonstrated through a real estate case study.
Contribution
It presents a novel AI-driven governance framework combining intelligent agents and blockchain for trustworthy asset tokenization, addressing trust, security, and regulatory challenges.
Findings
Improved transparency and security in asset tokenization.
Effective mitigation of fraud and money laundering risks.
Enhanced compliance through real-time AI monitoring.
Abstract
Alternative Assets tokenization is transforming non-traditional financial instruments are represented and traded on the web. However, ensuring trustworthiness in web-based tokenized ecosystems poses significant challenges, from verifying off-chain asset data to enforcing regulatory compliance. This paper proposes an AI-governed agent architecture that integrates intelligent agents with blockchain to achieve web-trustworthy tokenization of alternative assets. In the proposed architecture, autonomous agents orchestrate the tokenization process (asset verification, valuation, compliance checking, and lifecycle management), while an AI-driven governance layer monitors agent behavior and enforces trust through adaptive policies and cryptoeconomic incentives. We demonstrate that this approach enhances transparency, security, and compliance in asset tokenization, addressing key concerns around…
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Taxonomy
TopicsBlockchain Technology Applications and Security · FinTech, Crowdfunding, Digital Finance · Cybercrime and Law Enforcement Studies
