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AI agents pay through a chain of separate functions: a person or organization sets limits, the agent presents evidence of its identity or authority, a wallet or payment provider makes a credential available, and a merchant or service requests payment. A payment rail then authorizes and executes the transaction; settlement, refunds, and disputes follow that rail’s rules. No single wallet or protocol necessarily handles every step.
What happens when an AI agent makes a payment?
A useful way to understand an agent payment is to follow the transaction from instruction to outcome. The agent’s natural-language interpretation of a request is not, by itself, payment authorization. A payment system needs evidence connecting the user’s or organization’s intent to the particular purchase being requested.
- Set intent and limits. The user or organization defines the task and relevant bounds, such as a budget, permitted payment instrument, or purchase constraints. Google’s Agent Payments Protocol (AP2) describes an open mandate as a way to express constraints before a specific checkout is finalized.
- Resolve the purchase. The agent finds a merchant or digital service and identifies the actual goods, service, or terms. AP2 describes a closed checkout mandate that records finalized purchase details.
- Present evidence of agent context and authority. Depending on the system, the agent may provide signed intent or identity information, mandate credentials, or another authorization artifact. Visa’s Trusted Agent Protocol (TAP) describes signed agent intent and consumer-recognition signals; AP2 uses a chain of verifiable digital credentials.
- Make a bounded payment capability available. A wallet, credential provider, issuer, or payment service supplies the means to pay. It may apply controls such as per-transaction or per-session limits, protected key custody, or screening, depending on the provider and implementation.
- Request, authorize, and execute payment. A merchant or service requests payment. The relevant payment system checks the request under its rules and, if approved, executes it on a supported rail. For example, an x402-enabled web service can respond to a request with an HTTP 402 Payment Required response containing structured payment details; the client then returns payment authorization for verification.
- Settle and record the outcome. Funds are settled and accounted for according to the selected rail. The transaction record should remain connected to the authority granted and the service delivered so the parties can handle errors, refunds, or disputes under the applicable rules.
Wallet access is not the same as authorization
A wallet or payment credential makes it possible to attempt a payment; it does not necessarily specify what the agent is allowed to buy, from whom, or how much it may spend. Those permissions must be expressed and enforced through controls appropriate to the provider and transaction.
Coinbase’s product materials describe controls such as per-session and per-transaction caps for its service. Such examples are provider-specific, not guarantees made by every wallet or agent-payment protocol. In AP2, mandates are one proposed way to preserve the relationship between user constraints and a particular transaction: an open mandate captures constraints before checkout, while a closed mandate binds finalized purchase details to payment authorization.
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This distinction matters when a task changes along the way. A broad instruction such as “buy supplies for the project” may not establish authority for any particular merchant, item, or amount. A robust implementation needs a way to check the resolved purchase against the limits that were actually granted, rather than treating the model’s interpretation as permission.
Authorization, identity, execution, and settlement are different jobs
These terms describe related but distinct parts of a payment:
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- Authorization is approval or rejection of a requested payment under the relevant system’s rules. A mandate or agent identity assertion alone does not move funds.
- Agent identity and intent help a merchant understand which agent is interacting and what it is attempting to do. Visa TAP focuses on merchant-facing agent trust information, including signed intent and consumer-recognition signals; it can optionally carry payment information.
- Payment execution is the act of submitting and processing an approved transaction through a payment mechanism.
- Settlement is the movement and final accounting of funds on the applicable rail. Its timing, reversibility, and remedies depend on the rail and implementation.
AP2 documentation frames the authorization problem with the question, “How can we verify that a user gave an agent specific authority for a particular purchase?” Its answer is centered on verifiable mandates and an audit trail. That is a different job from identifying the agent to a merchant or carrying a payment request between software services.
How the main agent-payment approaches differ
The protocols and services below overlap in some deployments, but they are not interchangeable. Their primary roles differ, and the payment rails available depend on the implementation.
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| Approach | Primary job described by its sources | Payment or settlement framing | Useful distinction |
|---|---|---|---|
| AP2 | Signed, verifiable checkout and payment mandates for authorization evidence and auditability. | Payment-agnostic framework, with examples for cards and an x402 extension. | Records user intent and finalized purchase authorization. |
| Visa Trusted Agent Protocol (TAP) | Helps merchants recognize an agent and inspect signed intent and consumer-recognition information. | Initial specifications apply in a Visa network context; payment information can optionally be carried. | Centers agent identity and trust signals, rather than providing a universal wallet. |
| x402 | HTTP-native payment request and response for APIs and digital services. | Its whitepaper describes multiple settlement methods; current options depend on implementation. | Supports pay-per-request flows with structured payment details. |
| MPP | Machine-to-machine payment workflow; Visa has published a card specification and SDK. | Stripe and Tempo announced the protocol; Visa describes card support and connections with emerging rails. | Accepted funding methods depend on the implementation and may include cards, on-chain funds, or both. |
| Mastercard Agent Pay for Machines | Credentialing, permissioning, transacting, and settling at machine scale. | Mastercard describes cards, accounts, and stablecoins. | Describes network-level controls and multiple settlement rails. |
In practical terms, AP2 is most focused on evidence of delegated authority; TAP on agent trust at merchant interactions; x402 on exchanging payment requests over HTTP; and MPP and Mastercard’s machine-payment service on transaction and settlement infrastructure. A system can combine layers—for example, mandate evidence for authority with a separate protocol for the payment request and a rail for settlement.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which payment rails can an agent use?
There is no universal settlement behavior implied by the phrase “AI-agent payment.” Official materials describe implementations involving existing card networks, accounts, stablecoins, and other on-chain mechanisms. The chosen rail determines how the transaction is executed and accounted for, along with the available refund or dispute path.
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A card transaction may use existing network authorization and tokenized credentials. An API payment using x402 may use a settlement method supported by that service. Mastercard’s Agent Pay for Machines materials describe cards, accounts, and stablecoins. These are examples of different implementation choices, not a promise that every agent, merchant, or protocol supports every option.
Keep authorization separate from settlement when evaluating a system: a signed mandate can establish what was permitted, and an identity protocol can help a merchant recognize an agent, but neither alone settles the funds. Likewise, the fact that a payment request was accepted does not tell you what remedies are available if the service fails or the agent makes an error.
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Why micropayments make costs and exception handling important
Agent systems may make many small payments, including pay-per-request charges for digital services. Visa and Artemis reported roughly $15.0 million in adjusted volume across 109.6 million transactions since x402 launched in May 2025. Their 2026 report also described about $25,000 across roughly 115,000 MPP transactions in the first few weeks after MPP’s mid-March 2026 launch. These are time-bounded reported observations, not current lifetime totals or forecasts.
Visa and Artemis note that conventional card fees and dispute processes can be poorly matched to high-frequency, very small agent transactions. Visa also says chargeback windows and evidence rules were designed around human-speed commerce and do not straightforwardly fit chains of agents paying agents. That makes transaction records, evidence of granted authority, and clear responsibility for service delivery important operational questions—not details a wallet alone can settle.
What to check before allowing an agent to spend
For an individual or organization, useful questions concern the whole payment path rather than just the wallet label:
- What purchases, merchants, services, instruments, and maximum amounts are allowed?
- Are limits enforced per transaction, per session, or in another way, and by which provider?
- What evidence connects the user’s or organization’s instruction to the finalized purchase?
- Can a merchant verify the agent’s identity or intent where that matters?
- Which rail will execute and settle the payment, and what refund or dispute procedure applies to that rail?
- Are transaction records sufficient to connect the authorization, payment, and service delivered?
Google’s 2025 AP2 announcement described more than 60 collaborating organizations. That figure refers to the announcement’s partner set, not a count of current production deployments. Product capabilities and network support should be checked with the relevant provider rather than inferred from protocol names.
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