AI Agent Payment Infrastructure: The Development Direction of Cryptocurrency and Big Tech Companies

Source: Tiger Research

Translation: Baihua Blockchain

Core Highlights

• The payment subject is shifting from humans to AI Agents, making payment infrastructure a key requirement for true autonomy.
• Big tech companies (including Google AP2 and OpenAI Delegated Payment) are designing automated approval-based payment systems built on existing platform infrastructure.
• Cryptocurrencies, through standards like ERC-8004 and x402, leverage NFT-based identity verification and smart contracts to enable decentralized payment models.
• Major tech firms prioritize convenience and consumer protection, while cryptocurrencies emphasize user sovereignty and broader agent-level execution capabilities.
• The key question for the future is: Will payments be controlled by platforms or executed via open protocols?

1. Payments Are No Longer Exclusive to Humans

Source: macstories (Federico Viticci) Recently, “OpenClaw” has garnered widespread attention. Unlike AI systems like ChatGPT or Gemini, which primarily focus on retrieving and organizing information, OpenClaw allows AI Agents to execute tasks directly on the user’s local PC or server.

Through messaging platforms like WhatsApp, Telegram, and Slack, users can issue commands, and the agent will independently carry out tasks, including email management, calendar coordination, and web browsing.

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

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

Historically, payment systems have been designed around human actors. In environments driven by AI Agents, this assumption no longer holds. For automation to be truly autonomous, agents must be able to independently evaluate, authorize, and complete transactions within defined constraints.

Anticipating this shift, major tech firms and crypto-native projects have launched frameworks over the past year aimed at enabling agent-level payments.

2. Big Tech: 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 company with a structured implementation framework.

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

• Intent Mandate: Records the user’s desired action.
• Cart Mandate: Defines how to execute the purchase under preset rules.
• Payment Mandate: Executes the actual transfer of funds.

Example: Suppose Ekko instructs Google’s AI Agent to “find and buy a winter jacket under $200 on Google Shopping.”

• Intent Authorization: Ekko’s command is recorded as a digital contract on-chain, indicating the intent to purchase “a winter jacket with a maximum budget of $200.”
• Cart Authorization: The AI agent follows the intent, searches partner merchants for matching items, and adds suitable products to the cart. It verifies the price (e.g., $199, within budget ✓), and confirms the delivery address.
• Payment Authorization: Ekko reviews the selected item and approves. The $199 is processed via Google Pay. Alternatively, the AI agent can automatically complete the payment within preset parameters.

Throughout this process, no additional input from the user is required. Google AP2 relies on existing user credentials (pre-registered cards and addresses), reducing barriers to entry and simplifying adoption.

Source: Google

However, Google currently only supports agent payments within its partner network, limiting usage to a controlled ecosystem and restricting broader interoperability and open access.

3. Cryptocurrencies: Self-Hosting and Open Exchange

The crypto space is also developing payment infrastructure for AI Agents, but with a fundamentally different approach. While big platforms build trust within controlled ecosystems, crypto starts from a different question: Can AI Agents gain trust without relying on centralized platforms?

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

First is the identity layer. For AI Agents operating on blockchain, being recognizable is essential. ERC-8004 serves this purpose. It issues NFTs that are not art collectibles but credential NFTs containing structured identity data. Each token includes three components:

1. Identity
2. Reputation
3. Validation

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

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

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

Example: Ekko instructs his Agent A to purchase a used laptop with a maximum budget of $800. Seller’s agent B communicates directly.

• Mutual verification: Using ERC-8004 NFTs, verify identity and reputation scores (e.g., reputation 72, balance confirmed).
• Escrow smart contract: $800 is transferred from the wallet into an escrow smart contract, locking funds until delivery is confirmed.
• Settlement and reputation update: After transaction completion, x402 automatically settles, and both parties’ reputation records are updated and written into their respective ERC-8004 NFTs.

No intermediaries are involved. The two AI agents conduct the transaction directly via blockchain-based verification and settlement, exemplifying a crypto-native A2A (Agent-to-Agent) business model.

4. Big Tech vs. Cryptocurrency: Divergent Domains for AI Agent Operations

Google AP2 exemplifies a controlled model designed for verified partners. Google restricts market participation to protect consumers. Because AI agent execution results are probabilistic rather than deterministic, if a transaction error occurs, liability may ultimately fall on the payment infrastructure provider. To minimize failure risk, Google has an incentive to narrow its ecosystem.

This restricted ecosystem enhances stability but also limits the ability of agents to operate autonomously and optimize across broader markets.

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

While end-to-end execution is not yet perfect, the long-term vision is for agents to manage daily consumption independently. Major platforms might try to integrate key retail channels, but open crypto standards have structural advantages in handling small-value, high-frequency programmable payments (microtransactions). For example, an agent purchasing 1000 images at $0.01 each via crypto-native pathways can operate more efficiently.

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

Summary

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

The future is more likely to see interoperability between these approaches rather than a zero-sum competition.

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