AI and Crypto: The Emergence of Value Networks as AI Becomes an Action Agent

Over the past two years, AI has become an unavoidable topic across nearly every industry. From large models to AI agents, from content generation to automated office workflows, AI is rapidly entering real-world business scenarios. When discussing AI, many focus on model capabilities, computational costs, data quality, and who will become the next super app.

But in the crypto industry, discussions about AI often go further: if AI in the future is not just answering questions but can proactively perform tasks, invoke services, process payments, manage assets, and even collaborate with other AIs, what kind of underlying system would it require?

AI addresses the issue of "intelligence," while crypto addresses the issue of "value flow." When intelligence begins to participate in economic activities, the importance of value networks will be reemphasized.

Early AI functioned more like a tool: users posed questions, and AI provided answers; users gave commands, and AI completed tasks. During this phase, AI primarily served to process information and enhance efficiency. However, the emergence of AI agents has begun to change this dynamic.

The AI agent does more than passively answer questions—it can break down goals, plan, and execute tasks. For example, it can help users filter information, invoke external tools, complete subscriptions, manage workflows, and even make decisions within a defined scope of authority. This means AI is evolving from “generating content” to “executing tasks.”

But once AI begins executing tasks, it encounters a practical issue: many tasks are not free. Calling APIs costs money, using computing power costs money, accessing data costs money, cross-platform collaboration requires settlement, and in the future, AI systems invoking each other’s services may also require an automated mechanism for value exchange.

Traditional internet payment systems can certainly address some issues, but they were primarily designed for humans and businesses, not for high-frequency, low-value, global transactions between machines. For AI to truly participate in economic activity, a more open, real-time, and automation-friendly payment and settlement network is needed.

In the past, many people thought of Crypto primarily in terms of asset price fluctuations: how much BTC has risen, whether ETH can break through, and when the altcoin season will arrive. These are indeed part of the market, but they do not represent the full scope of Crypto. At a more fundamental level, Crypto provides a global, open, and programmable network of value.

The development of stablecoins has given on-chain payments a more practical foundation. Stablecoins do not require the layered intermediaries of traditional banking systems, nor are they inherently limited by the payment networks of any single country or region. They enable near-real-time transfers on-chain and are better suited for cross-border, low-value, high-frequency settlement scenarios—conditions that closely align with the needs of AI agents.

In the future, an AI agent may need to complete multiple payments within seconds: purchasing a segment of data, paying for a model invocation, renting short-term computing power, invoking another agent’s service, or distributing earnings after completing an automated task. If each payment relied on bank cards, bank accounts, manual confirmation, and traditional clearing systems, efficiency would be extremely low.

However, if on-chain stablecoins and smart contracts are used, the entire process can be automatically executed by software. This does not mean that all AI applications must use crypto—scenarios such as writing copy, creating presentations, generating images, or handling customer service inquiries may not require on-chain systems.

What truly needs Crypto are AI scenarios involving open networks, automated payments, cross-platform collaboration, and global settlement. As AI evolves from being a standalone tool to participating in an open economic network, its requirements for payment systems will change—and Crypto provides a solution that better aligns with machine needs.

Payment is just the first step; the harder issue is identity. In the future, the internet may be flooded with AI agents—some representing individuals, others representing enterprises, still others representing protocols, and some merely parts of automated systems. Who this AI is, who it represents, whether it has authorization, what it has done in the past, and whether it is trustworthy will all become very real concerns.

If these questions cannot be answered, the more powerful the AI becomes, the greater the risk. Many platforms today rely on account systems to manage identity, but these systems are typically closed. Identities within one platform are difficult to directly transfer to another, and user behavior, credit records, and authorization relationships are often controlled by the platform.

Crypto offers an alternative approach. Wallet addresses, digital signatures, on-chain records, and verifiable credentials enable an AI agent to possess a relatively open digital identity. It doesn’t need to expose underlying real-world personal information, but can prove control over a specific address, ownership of certain permissions, execution of specific transactions, and interactions with particular protocols.

For AI agents, verifiable identity is crucial, as AI may not be limited to running on a single platform in the future but could instead collaborate across applications, protocols, and networks. A verifiable identity is better suited to an open internet environment than an account usable only within a single platform.

On-chain identity does not equate to absolute trust. Addresses can be stolen, permissions may be abused, and AI can be manipulated by malicious instructions—so Crypto cannot automatically solve all trust issues.

But it at least provides a new infrastructure that allows identity, authorization, and behavioral records to be verified, rather than relying entirely on a platform’s database. This may become increasingly important for large-scale collaboration among future AI agents.

The development of AI relies on three types of resources: data, computing power, and models. These resources are not always concentrated in the hands of a few companies—much of the data comes from users and real-world scenarios, much of the computing power can be distributed across different regions, and many model capabilities may be jointly developed by different teams.

The challenge lies in how to enable these resources to collaborate. The traditional internet’s solution is platforms—entities that set rules, allocate traffic, and control settlements, with participants contributing resources according to the platform’s guidelines. While this approach is highly efficient, it often leads to centralization: resource providers typically lack pricing power, and users find it difficult to truly participate in value distribution.

The answer in crypto is the network. Through tokens, smart contracts, and on-chain settlement, crypto enables more transparent relationships between resource contribution, network usage, and reward distribution. This is precisely the issue many AI + crypto projects aim to solve: if someone provides data, can they receive compensation? If someone contributes computing power, can it be automatically settled? If someone trains a model, can they participate in long-term earnings? If someone verifies results, can they be incentivized?

Stay calm here. Not all "AI + Token" projects have value; some merely package the AI concept as a market narrative without real products or genuine demand. Such projects may gain short-term attention but struggle to create long-term value.

True value in AI + Crypto shouldn't just mean adding another coin—it should solve real problems in payments, settlement, identity, incentives, permissions, and collaboration. If a project cannot demonstrate that it creates tangible value in these areas, it is more likely just a short-lived trend driven by market hype.

Markets often shorten long-term trends into short-term fads. When AI becomes popular, a flood of AI-themed assets emerges; when MEMEs gain traction, countless MEME projects appear; when RWA catches fire, stories about tokenizing assets proliferate. But focusing solely on short-term price movements can cause you to overlook truly significant developments.

The relationship between AI and crypto should not be limited to "which AI coin rose the most." More importantly, we should ask whether AI needs a new payment system, open identity, automated settlement, cross-platform collaboration, or a more transparent incentive mechanism.

If the answer to these questions is yes, then Crypto is not merely an ancillary concept to AI, but a critical infrastructure for AI’s next phase. AI addresses productivity, while Crypto enables value to flow freely, be verified, and be settled—one solving the problem of productivity, the other solving the problem of value networks.

This is the true point of convergence between the two. AI does not exist for Crypto, and Crypto does not exist to chase AI trends—their intersection stems from a more fundamental need: when intelligence begins to act, value must be able to flow alongside it.

Whenever a new trend emerges, the market first becomes excited, then filters it—and AI + Crypto is no exception. It offers significant potential, but also clear risks. First, the concept has become overheated, with many projects lacking genuine AI capabilities and merely using the AI narrative to attract attention. For average users, evaluating project value has become more challenging.

Second, security issues become more complex. If AI agents are able to automatically execute trades or payments in the future, poorly designed permissions could pose greater risks than those of standard accounts. Incorrect commands, malicious manipulation, private key management, and authorization scope will all become new security challenges.

Moreover, regulatory uncertainty still exists. AI involves data and algorithms, while crypto involves assets and payments; when combined, the regulatory complexity increases significantly, particularly regarding stablecoins, cross-border payments, and automated financial behaviors—all of which are likely to become key areas of future regulation. Therefore, it is not an absolute statement that AI cannot exist without crypto; rather, as AI evolves from a tool into an active participant and begins engaging in open economic activities, crypto will become one of its unavoidable foundational options.

For traders, the integration of AI and crypto may initially appear as a new market trend, but in the long term, it reflects the broader evolution of the digital assets industry. Crypto is gradually transitioning from a mere trading market into a digital financial infrastructure, where users enter not just to chase short-term price fluctuations, but to participate in the growth of global digital assets through a safer, more stable, and more efficient platform.

This is precisely the direction AEGET continues to build toward. As a global cryptocurrency trading platform, AEGET consistently emphasizes security, stability, and innovation, delivering a more comprehensive digital asset trading experience to users across spot, futures, and copy trading scenarios. Meanwhile, AEGET remains focused on the long-term value behind emerging trends such as AI, stablecoins, and RWA, rather than short-lived hype.

In the AI era, the role of trading platforms is evolving. They are no longer just gateways for buying and selling assets, but also vital bridges connecting users to new assets, new narratives, and new financial scenarios. For users, opportunities always exist—but what truly matters is having stable tools, clear judgment, and a reliable trading environment when those opportunities arise.

The integration of AI and crypto should not be simply understood as a short-term trend. What truly matters is the convergence of intelligence and value networks. When AI is merely a tool, it can function without crypto; but as AI begins to execute tasks, access resources, make payments, establish identities, and participate in collaboration, it will increasingly require an open, programmable, and verifiable value system.

This is what Crypto is all about. In the short term, the market will continue to fluctuate around AI-related concepts; in the long term, only the infrastructure that solves real-world problems will endure.

AI makes machines smarter; crypto makes value more free. When machines begin participating in economic activities, their convergence may have only just begun.