Author: Tiger Research

The news headlines are always reporting on AI agents trading autonomously and handling payments on their own. In fact, the cryptocurrency wallet industry has already been quietly paving the way. Currently, there are more than ten companies specifically creating wallets for agents. What do they really want? What are the potential returns?

Key Points

• When AI agents browse the web, purchase goods or information, they will initiate hundreds or thousands of micro-payments worth only a few cents or even less. The existing bank card payment system cannot support such volume, thus requiring wallets that can automatically split and send funds according to preset conditions.
• Despite almost no revenue in the short term, companies like Coinbase and Binance are still ramping up AI wallet infrastructure. The reason is simple: to secure a future user base before agents engage in large-scale trading. This phase is about positioning for the expected demand before it explodes.
• According to calculations based on Coinbase's data, after the increase in AI agent usage, its revenue could reach up to about 7 times what it is now.
• The accumulated payment records in the wallet can intuitively show whether a particular AI agent is generating income, which opens the door for issuing loans based on future earnings—similar to extending credit based on a small business’s card transaction history.
• However, all this is still in the realm of possibilities, not verified facts. AI agents can still make mistakes, execute erroneous payments; rules vary across countries and companies; the legal status of agents is also not yet clear. Thus, the current competitive focus is not on making money today, but on securing a position in a market expected to take shape in the coming years.

AI Agents are Becoming Fully Active

Earlier this year, there was a well-publicized experiment on the prediction market Polymarket: give an AI agent $50 in starting capital and let it trade autonomously, with the condition that if it doesn’t earn enough to cover API and server costs, it will "disappear." As a result, this agent successfully traded. Subsequently, a number of similar agents began trading in the same manner.

AI agents have not yet entered daily life, but it is clear they will be used on a large scale in the near future.

Every Agent Transaction Starts from a Wallet

Currently, AI agents have not entered daily payment scenarios. Their most active applications remain trading bots within the cryptocurrency ecosystem—independent of traditional payment tracks, focusing on cryptocurrency trading.

In the future, payments will extend into areas that are hard to imagine today. As we pointed out in previous reports, AI is changing the nature of payments. Once actions are taken directly by agents on the internet rather than by people, single payment amounts will dramatically decrease. A single API call or data query might cost as little as $0.001 or, in extreme cases, even $0.00001.

To surpass the current way of using wallets and realize such small, automatically split, and intervention-free payments, it is essential to rely on programmable payment systems. This is the context in which the x402 payment track emerges, and wallets serve as the foundation for its operation.

However, the existing payment tracks are designed around the concept of "humans" as the main transaction subjects.

Bank cards are issued to specific holders and use a chargeback mechanism—people dispute and reverse transactions when issues arise, with each transaction charging a fixed fee of several cents. When a person occasionally spends $20, these are not problems. But once agents start making thousands of payments per second, at $0.001 per API call and $0.00001 per data record, this payment model becomes economically unviable.

The core issue is: can money itself be programmable?

Bank cards can automate the entry of payment information but cannot be programmed to split, stream payments, or settle cash flows on conditions. The track that wallets operate on inherently possesses these capabilities. Storing payment information on a card can only enable the execution of a single "human-scale" transaction. Once the economy shifts to direct transactions between machines, wallets become the sole possible starting point.

Agents Could Be a $50 Billion Business

From relevant tables, it can be seen that wallet providers have a wide coverage, ranging from exchanges to stablecoin issuers. Why are so many different types of players entering the agent wallet infrastructure, which almost shows no profit in the short term?

The answer is: they are laying out future revenue and business rather than today's. Adding agent functionality to wallets is not to make immediate profits but to establish the capacity to absorb massive transaction volumes when agents become active on a large scale.

The key point is that AI agents will ultimately operate around the clock in a browserless environment, completely devoid of human intervention. Imagine a user instructing an agent to complete a research report. As the agent collects information, each time it retrieves paid data from different platforms, it will execute a small payment. A single command from the user could instantly trigger 20 to 30 payments or even more.

What appears to be a simple request to a human turns into a multitude of payment transactions when processed through an AI agent.

How will this change in the payment environment affect company revenues? This can be estimated using the data disclosed by Coinbase. The calculation is based on Coinbase's 9.2 million monthly active trading users (MTU), rather than its total of around 120 million registered users.

By combining adoption rates, the number of agents per user, and daily call frequency, the following scenarios are obtained:

• Conservative Scenario (adoption rate 10%, 1 agent per user, 50 calls per day): annual revenue increase of about $84 million, growth rate of 1.2%.
• Neutral Scenario (adoption rate 50%, 2 agents per user, 200 calls per day): additional revenue significantly rises to about $3.36 billion, growth rate of 46.8%.
• Aggressive Scenario (adoption rate 100%, 3 agents per user, 1000 calls per day): annual revenue of about $50.37 billion, approximately 7 times Coinbase's current total revenue.

The most striking point in this comparison is that the gap between the three scenarios expands geometrically, rather than simply adding up. The adoption rate increasing from 10% to 100% (10 times) results in a revenue difference expanding by about 600 times—from $84 million to $50.37 billion.

Because the three variables of adoption rate, the number of agents per user, and daily call volume are multiplicative, any slight increase will result in exponential growth in total volume. Therefore, once agents achieve large-scale adoption and the user base surges, the revenue stream generated could reach about 7 times the current total revenue.

This is also why Coinbase, despite having almost no related revenue today, is vigorously promoting AI wallet infrastructure—it aims to lock in a share of the expected revenue that the agent era will bring.

Moving Towards a New Bank for Agents

The transaction data accumulated through wallet infrastructure goes far beyond mere records. It provides a foundation for new business models: the payment history stored in the wallet can become a credit standard for assessing the financial condition and performance of AI agents.

Once this data-driven credit assessment system is established, wallet providers can naturally extend to the next generation of financial services, such as income-based financing (RBF) specifically targeting agents.

Stripe Capital is a typical example. It successfully built a new financial business atop existing payment data. When Stripe launched its lending service Stripe Capital in September 2019, it did not rely on external credit agencies or cumbersome loan materials, but directly used real-time sales data from each merchant in its payment network to assess loan eligibility and amounts.

Stripe’s case illustrates that a company can build high-value financial businesses based on existing operational data pipelines without the need for additional sales networks or marketing investment.

Wallet providers for agents are likely to follow a similar expansion path. By continuously accumulating agents' income data through wallets, they have a foundation to provide operational funds through RBF and to generate revenue as a financial platform focused on agents.

However, to truly establish this new business line, one prerequisite must be met: AI agents must evolve from mere payment executors into asset-holding entities capable of generating their revenue, earning enough real income to repay loans.

This Growth Has Yet to Be Verified

The earlier description of Coinbase’s maximum revenue growing 7 times and expanding towards RBF is based on an optimistic scenario of widespread adoption of agent payments. There are still significant barriers to making these realities materialize in the actual economy.

First, the actual purchasing conversion rate and payment reliability of AI agents remain in considerable doubt. Agents can still "hallucinate" and make mistakes when placing orders autonomously, leading to erroneous payments; sometimes they may even be directly intercepted by the card issuer's fraud detection system (FDS). Therefore, the actual payment completion rate remains relatively low.

Additionally, payment protocols such as x402, AP2, and MPP are still in a fragmented state and have not converged into a unified standard; AI agents are not legal entities and lack clear KYC (Know Your Customer) and financial regulation, further hindering market expansion.

Thus, the current goal for wallet providers is not short-term transaction fee revenue. The Apple App Store took 15 years to establish a $10 billion fee market, and WeChat Pay took 7 years to create its massive mini-program ecosystem. Agent wallets are similarly on a long timeline—they are building an ecosystem rather than competing for immediate returns.

Current competition is not about marginal revenue today; it is about which company can gain control of the data flow in the agent economy, which is expected to mature over the next five to ten years.

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