Tap to Trade in Gate Square, Win up to 50 GT & Merch!
Click the trading widget in Gate Square content, complete a transaction, and take home 50 GT, Position Experience Vouchers, or exclusive Spring Festival merchandise.
Click the registration link to join
https://www.gate.com/questionnaire/7401
Enter Gate Square daily and click any trading pair or trading card within the content to complete a transaction. The top 10 users by trading volume will win GT, Gate merchandise boxes, position experience vouchers, and more.
The top prize: 50 GT.
![Spring Festival merchandise](https://exampl
Final warning! The AI giant is about to take over your wallet. Are $BTC and $ETH the only "rules cages" that can lock it down? This is your last chance to act before it's too late!
AI agents choosing cryptocurrency payments is not about chasing trends. The fundamental reason is that only the characteristics of crypto infrastructure can match their operational mode: 24/7 operation, global reach, and programmability. Traditional financial systems are designed for humans, relying on accounts, approvals, business hours, and fragmented jurisdictions. AI agents, on the other hand, are inherently global, operate around the clock, and coordinate dozens of services at internet speed.
When AI shifts from “providing advice” to “executing tasks,” it becomes a new type of economic actor. It can discover opportunities, run workflows, pay fees, route orders, and manage risks. At this point, what limits it will be not just model quality but user trust. For example, when you ask it to plan an overseas trip, you must trust that it will make the best decision in your interest. Payment is the first point where trust issues surface, and the core is ensuring different systems can reliably collaborate and fulfill their functions.
A recent example is OpenClaw, an open-source agent that gained 100,000 GitHub stars in a week. It became popular for automating daily tasks like email handling, scheduling, and travel planning. But this also exposed critical security vulnerabilities. Cisco security team pointed out that OpenClaw had run malicious plugins that secretly sent user data to external servers. The problem isn’t with the agent itself but with its trust model. When you grant it access to emails and calendars, you are giving an unconditional, unverifiable, and unauditable trust.
Trust issues intensify with increased risk. Currently, agents handle low-risk tasks like scheduling meetings and summarizing emails. But when they move into high-value actions like payments, legal, and business operations, granting access to all personal credentials becomes extremely dangerous. You cannot audit their behavior, verify whether they are acting within instructions, or prove to counterparts that they are authorized. The risks of unauthorized activities also increase accordingly.
Existing tech giants are building trust through brand reputation and closed ecosystems. But their agents are limited by isolated integrations, restricted partnerships, and centralized automation control. AI running within these traditional channels is constrained by these limitations. APIs may be revoked, access throttled, or blocked when automation threatens existing interests.
Crypto infrastructure, however, is permissionless and peer-to-peer. An agent can discover services, pay, and settle directly without platform approval. This makes crypto not only a lower-cost channel but also a neutral pathway for autonomous commerce. It transforms value transfer into a foundational module available to developers. A wallet is a programmable entity. Crypto supports 24/7 settlement, global interoperability, composability across services, and atomic execution.
More importantly, it provides verifiability for AI agents. Blockchain offers post-facto verifiability and auditability at the foundational level. But in an ideal agent economy, the greater benefit is proactive verifiability—that is, transactions cannot be finalized unless they meet user-defined rules and constraints. This strategy-constrained execution makes it possible for trust to be placed in agents handling high-risk economic activities.
Users and enterprises need more than audit trails; they need mechanisms to constrain agent behavior within strategic boundaries. Basic tools like spending limits can minimize risk but cannot capture intent in specific contexts. For example, “Book a refundable, under $500 flight from San Francisco to New York on a specified date” is not a simple rule; it requires external contextual information. The real challenge is how to incorporate contextual data into settlement in a scalable way without reintroducing third-party intermediaries.
In the long run, AI models will tend to homogenize, infrastructure will commoditize, and chat interfaces will become standard. Value will accumulate in the control plane that AI relies on: identity, permissions, routing, settlement, and reputation. The lasting winners will not be “a particular agent,” but those control plane systems that enable agents to operate reliably in the real world.
The “Uber moment” for agents will not just come from their intelligence. It will come from transforming trust from “I’m unsure whether I can trust” to “I can delegate because it can execute under my rules and safeguards.” The biggest AI companies will not just be “better models,” but those that make delegation safe.
This is where entrepreneurial opportunities lie. Existing giants will dominate major distribution interfaces, but they tend to build walled gardens structurally. Startups can succeed by becoming a trusted execution layer between user intent and real-world results: a strategy and permission control plane for delegation; a neutral router for optimal execution across tools and venues; a trust layer that makes autonomous workflows safe through hosting, escrow, dispute resolution, and auditable states.
The largest market driver is relieving users of burdens. AI agents will eliminate friction from high-frequency, high-cost workflows that are still manual due to trust and coordination costs—such as payments and fund management, cross-border commerce, invoice reconciliation, procurement approval, dispute claims, and personal affairs management.
As AI agents become the default operators of economic activities, crypto will serve as their settlement backbone, enabling them to trade, coordinate, and prove their actions within an open ecosystem. AI will become cheaper and more widespread. The real question is: in which systems are people willing to let AI act on their behalf? That’s why secure, reliable channels for delegation are critical—and why the biggest opportunities will be in systems that enable safe delegation.