Tiger Research: How Crypto Giants Are Betting on AI Agent Payment Infrastructure

This report is authored by Tiger Research. To achieve true autonomous automation, native payment capabilities are essential. The market has already begun to actively prepare for this shift.

Key Points

• The payment entity is shifting from humans to AI Agents, making payment infrastructure a core requirement for achieving true autonomy.
• Big tech companies (including Google AP2 and OpenAI Delegated Payment) are designing approval-based automated payment systems on top of existing platform infrastructures.
• Cryptocurrencies have achieved a disintermediated payment model through ERC-8004 and x402 standards, utilizing NFT-based identity verification and smart contracts.
• Big tech companies prioritize convenience and consumer protection, while cryptocurrencies emphasize user sovereignty and broader Agent-level execution capabilities.
• The key question for the future is: Is payment controlled by platforms or executed by open protocols?

1. Payment is No Longer Exclusive to Humans

Source: macstories (Feder1C0 Viticci)

Recently, "OpenClaw" has garnered significant attention. Unlike major AI systems like ChatGPT or Gemini that are primarily responsible for retrieving and organizing information, OpenClaw allows AI Agents to execute tasks directly on the user's local PC or server.

Through instant messaging platforms like WhatsApp, Telegram, and Slack, users can issue commands, and the Agent subsequently executes tasks autonomously, including email management, calendar coordination, and web browsing.

Operating as open-source software and not tied to a specific platform, OpenClaw functions more like a personal AI assistant. This architecture is favored for its flexibility and user-level control.

However, a key limitation remains. For AI Agents to achieve full autonomy, they must be able to execute payments. Currently, Agents can search for products, compare options, and add items to the cart, but final payment authorization still requires human approval.

Historically, payment systems have been designed around human entities. In an AI Agent-driven environment, this assumption no longer holds. If automation is to become fully autonomous, Agents must be able to independently assess, authorize, and complete transactions within defined constraints.

Foreseeing this shift, large tech companies and crypto-native projects have launched technological frameworks aimed at achieving Agent-level payments over the past year.

2. Big Tech Companies: Building Agent Payments on Existing Infrastructure

In January 2025, Google launched AP2 (Agent Payment Protocol 2.0), expanding its AI Agent payment infrastructure. While OpenAI and Amazon have also outlined related initiatives, Google is currently the only large enterprise with a structured implementation framework.

AP2 divides the transaction process into three authorization layers (Mandate Layers). This structure allows for independent monitoring and auditing at each stage.

• Intent Mandate: Records the action the user wishes to perform.

• Cart Mandate: Defines how the purchase should be executed under preset rules.

• Payment Mandate: Executes the actual transfer of funds.

Example: Suppose Ekko instructs the AI Agent on Google Shopping to "find and purchase a winter jacket under $200."

• Intent Mandate: Ekko instructs the AI Agent to purchase "a winter jacket with a maximum budget of $200." This information is recorded on-chain as a digital contract, which is the intent mandate.

• Cart Mandate: The AI Agent follows the intent, searches for matches among partner merchants, and adds qualifying items to the cart. Price verification ($199, within budget ✓) and confirmation of the shipping address occur.

• Payment Mandate: Ekko reviews the selected items and clicks approve. $199 is processed through Google Pay. Alternatively, the AI Agent can automatically complete the payment within preset parameters.

Throughout the process, the user does not need to input additional information. Google AP2 relies on existing user credentials (pre-registered cards and addresses), reducing the entry barrier and simplifying the adoption process.

Source: Google

However, Google currently only supports Agent payments for companies within its partner network. Therefore, its usage is limited to a controlled ecosystem, restricting broader interoperability and open access.

3. Cryptocurrencies: Self-Custody and Open Exchange

The crypto space is also developing payment infrastructure for AI Agents, but its approach is fundamentally different from that of big tech companies. While large platforms build trust within a controlled ecosystem, the crypto space starts from another question: Can AI Agents gain trust without relying on centralized platforms?

Two core standards aim to address this goal: Ethereum's ERC-8004 and Coinbase's x402.

First is the identity layer. AI Agents operating on the blockchain must be identifiable. ERC-8004 serves this function. It is issued in the form of NFTs, but instead of art collectibles, it consists of credential NFTs containing structured identity data. Each token comprises three parts:

1. Identity

2. Reputation

3. Validation

These elements together form a verifiable on-chain identity certificate.

In terms of payment mechanisms, x402 serves as the payment pathway. Developed by Coinbase, x402 is the crypto-native payment standard for AI Agents. It enables Agents to conduct autonomous transactions using stablecoins. Its core feature is automated smart contract execution, with conditional logic embedded directly in the code, allowing settlement to occur without human intervention once conditions are met.

When ERC-8004 (identity) is combined with x402 (payment), AI Agents can verify counter-parties and execute transactions without relying on centralized platforms.

Example: Ekko instructs his Agent A to purchase a second-hand laptop with a maximum budget of $800. The seller's Agent B communicates directly with it.

• Mutual Verification: Identity and reputation scores are checked via the ERC-8004 NFT (e.g., reputation 72, balance confirmed).

• Smart Contract Escrow: $800 is transferred from the wallet into a smart contract escrow, with funds locked until receipt confirmation.

• Settlement and Reputation Update: After the transaction is completed, x402 automatically settles, and both parties' reputation records are updated and written into their respective ERC-8004 NFTs.

Throughout the process, no intermediaries are involved. Two AI Agents transact directly through blockchain-based verification and settlement, reflecting the Agent-to-Agent (A2A) business model in a crypto-native manner.

4. Big Tech vs. Cryptocurrencies: Differences in AI Agent Operational Domains

Google AP2 represents a controlled model designed for verified partners. Google restricts market participants to protect consumers. Given that AI Agent execution has probabilistic outcomes rather than complete certainty, if a transaction error occurs, liability may ultimately fall on the payment infrastructure provider. To reduce the probability of failure, Google is motivated to narrow its ecosystem.

A restricted ecosystem enhances stability but also limits the Agents' ability to operate autonomously and optimize choices in a broader market.

In contrast, ERC-8004 and x402 reflect a more open architecture. The crypto model aims for permissionless and interoperable solutions.

While end-to-end execution is not yet perfect, the long-term vision is for Agents to independently manage daily consumption. Large platforms may attempt to integrate major retail channels, while open crypto standards have structural advantages in handling small, high-frequency programmatic payments (micropayments). For example, an Agent purchasing 1,000 stock images at $0.01 each would have higher operational efficiency through a crypto-native path.

Of course, the lack of a centralized entity also brings trade-offs: identity assessment standards must be established in a decentralized manner, and no single entity bears ultimate responsibility for failures.

Conclusion

Both big tech companies and the crypto space are pursuing the same goal: achieving autonomous AI Agent commerce. The difference lies in the architecture: big tech companies favor closed, controlled systems, while the crypto space promotes open, protocol-based models.

The future trend is more likely to be interoperability between the two approaches rather than a zero-sum game.