OKX’s Gracie Lin Says AI Agents Need Sub-Cent Payments as Bank Rails Slow Tasks

Global laws are still trailing the technology when it comes to determining who is liable if an artificial intelligence (AI) agent is hacked or makes a faulty purchase. Gracie Lin says that with legal frameworks still being drafted, accountability needs to be built into the infrastructure from day one, not bolted on later.

The modern internet is plagued by a quiet, fundamental friction. For decades, the architecture of web security and electronic payments has been built on a single, binary premise: “Prove you are human.”

According to Gracie Lin, CEO of OKX SG, this collision represents a critical turning point for digital infrastructure.

“Yes, it’s a real tension,” Lin notes. “Every friction point we encounter online was designed with a human on the other end. CAPTCHAs, one-time codes, redirect pages—all assume someone is sitting there reading and clicking. When the actor is an AI agent, those same mechanisms become blockers.”

In an ecosystem built for humans, an AI agent faces an existential crisis at checkout. Behavioral biometrics mistake an agent’s structured programmatic interactions for malicious hacking. Multi-factor authentication loops destroy automation by demanding a human-in-the-loop to input a text code. Meanwhile, web application firewalls flag high-velocity price comparisons as distributed denial-of-service, or DDoS, attacks.

“I’ll be upfront: I’m not a legal expert, and this is genuinely one of those areas where the law is still catching up to the technology,” Lin admits. “What I can speak to is the responsibility question at the infrastructure level. For any player in this space, it’s important to bake accountability into AI tools from day one.”

While global regulators scramble to draft legal definitions, users cannot be left vulnerable. The solution requires hardcoded boundaries.

“Control has to be designed in from the start,” Lin emphasizes. “The agent should only have access to what it needs for the task at hand, not a blank check. That means permissioned access: if an agent isn’t authorized to trade, it simply shouldn’t be able to attempt it.”

Second, before an agent’s payload executes, it must run in an isolated sandbox to unmask the exact movement of funds. “Transactions… can be simulated before execution happens and anything flagged as high-risk can be blocked automatically,” Lin explains.

As the machine economy hardens, a pivotal question emerges: Will a handful of Big Tech companies control how AI agents spend our money, or will the future remain open? Proprietary, closed-loop agent layers risk creating corporate gatekeepers that monopolize user data and restrict merchant access.

Lin warns that this risk is imminent: “There’s a real version of this future where a few platforms control the agent layer and by extension how AI spends your money. It should be open, and at OKX we are trying to set a good example.”

“If the payment rails and protocols are built as open standards now, while the architecture is still being decided, the competitive landscape stays open for everyone,” Lin says. “The window to get this right is now.”