Imagine this scene: you’ve invested in a US debt token product within a DeFi protocol, and suddenly the target company is under investigation by regulatory authorities, causing its credit rating to plummet. What about traditional oracles? They’re still mechanically pushing yesterday’s data. By the time you realize it, the losses are already irrecoverable.

This highlights the pain point of RWA tokenization. No matter how smart on-chain smart contracts are, they only handle digital logic. The real-world asset values are determined by volatile "soft factors" such as financial report quality, regulatory attitudes, judicial risks, and market confidence. The traditional oracle approach of fixed data pushing essentially fails here.

Now, some are looking to use AI to transform oracles. The core idea is—turning data provision from passive reaction into proactive thinking.

Let’s compare the two models simply. Traditional oracles are like courier boys who only deliver "hard data" such as prices and trading volumes on a fixed schedule, with rigid rules and a single task. AI-enhanced oracles are closer to investment bank analysts: they can not only fetch raw data but also analyze dozens of pages of audit reports in real-time, track the latest developments in global regulatory policies, and pre-warn about corporate risks from public opinion, ultimately producing a deeply processed value judgment.

How do they achieve this? AI empowerment relies on several key points. For example, intelligent document analysis—RWA involves大量 unstructured data scattered across PDFs, financial statements, regulatory announcements, which traditional methods cannot handle at all. AI can connect these pieces of information, transforming isolated data islands into a complete picture.