AI agents will not use one universal way to pay. For a person asking an agent to book travel or manage a subscription, the likely model is delegated use of familiar merchant and card systems. For software buying API calls or compute automatically, payments may need to happen more often, at much smaller values, and directly between machines. Payment companies are developing ways to identify agents, limit what they can spend, and protect payment credentials—but the standards, reach, and rules for responsibility are still taking shape.
What does it mean for an AI agent to make a payment?
An agentic payment is a transaction initiated by software acting on instructions from a person or business. That covers at least two different jobs, and the distinction matters: a system designed for booking a hotel is not necessarily suited to paying fractions of a cent for thousands of software requests.
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Agent-assisted purchases for people and businesses
A person might ask an agent to find and book a trip, buy a product, or manage a subscription. The agent works within a conventional commercial transaction: a merchant, a purchase, and a payment method such as a card. Visa describes this as a consumer-scale use of agentic commerce, where the key challenge is making it clear to sellers that an automated buyer is authorized to act for a customer. Visa’s overview of agentic payments separates these purchases from machine-to-machine payments.
Machine-to-machine payments
An agent may instead pay for an API call, a small amount of compute, or another digital resource as it uses it. These transactions can be low-value and frequent, so the payment needs to fit into the same automated exchange as the resource request. That is a different design problem from asking an agent to complete an occasional retail checkout.
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How might an agent be authorized to pay?
Payment authorization is not simply giving an AI the card number. Payment providers are describing systems that can recognize an agent, convey what the customer intended, and let an agent initiate a payment without exposing the underlying credentials. The specific mechanisms differ, and the announcements describe vendors’ designs—not a shared system already accepted by every merchant or payment provider.
Recognizing an agent and its intent
Visa says its Trusted Agent Protocol (TAP), developed with Cloudflare, is designed to help merchants distinguish trusted agents from malicious automation. Visa describes agent-specific cryptographic signatures and information about the agent’s intent and consumer recognition, with optional payment information. The announcement says payment and commerce companies provided feedback during development; that participation does not establish universal deployment. Visa’s TAP announcement also reports over 4,700% growth in AI-driven traffic to US retail websites over the prior year and says 85% of shoppers who had used AI to shop said it improved their shopping experience. Those are Visa-reported figures, not independent estimates of all shoppers or retail traffic.
Registering agents and protecting credentials
Mastercard’s Agent Pay program, announced in April 2025, describes registering and verifying trusted agents and using tokenized payment credentials. Its examples include consumer purchases and business purchasing workflows; the announcement describes intended capabilities, not proof that every use case is broadly available. Mastercard’s Agent Pay announcement names collaboration with Microsoft and other ecosystem firms.
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Stripe describes Shared Payment Tokens (SPTs) as a way for an agent to initiate a payment with customer permission without seeing the underlying payment credentials. In March 2026, Stripe said it was expanding SPT support to Mastercard Agent Pay and Visa Intelligent Commerce network tokens, as well as Affirm and Klarna buy-now-pay-later tokens. Stripe described those capabilities as rolling out, so availability can vary. Stripe’s announcement is the place to check its stated support and rollout details.
Which payment approaches are being developed?
The current initiatives address different parts of the problem. Some focus on proving an agent is trusted in a consumer checkout; others are designed for frequent machine payments or for shielding credentials. These are announced approaches, not a like-for-like performance ranking.
| Initiative | Focus and announced design | What the announcement does not establish |
|---|---|---|
| Visa and Cloudflare: Trusted Agent Protocol | Merchant recognition of agents, using signatures and information about agent intent and consumer recognition. Visa | Feedback from participating companies does not demonstrate universal merchant deployment or acceptance. |
| Mastercard: Agent Pay | Registering and verifying agents and using tokenized credentials for proposed consumer and business purchasing workflows. Mastercard | The announcement does not establish that every described workflow is widely available. |
| Stripe: Shared Payment Tokens | Customer-permitted agent payments without disclosing the underlying payment credentials to the agent; Stripe described expanding support for several network and buy-now-pay-later tokens. Stripe | Stripe said supported capabilities were rolling out; availability may vary. |
| Machine Payments Protocol (MPP) | An open machine-to-machine payment standard announced by Stripe and Tempo. Visa announced a card specification and SDK for card credentials to participate in MPP-compatible workflows. Visa’s MPP card announcement | The announcement does not establish broad provider reach or routine use across services. |
| Mastercard: Agent Pay for Machines | Announced infrastructure for high-frequency, low-latency, low-value agent and machine transactions, including credentialing, programmable permissions and spending limits, transactions across providers, and settlement across cards, accounts, and stablecoins. Mastercard’s June 2026 announcement | Capabilities and initial participants are described by Mastercard; the announcement does not establish universal availability or acceptance. |
How MPP describes a machine payment
Visa’s March 18, 2026 description presents the interaction as a sequence inside a resource request:
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- An agent requests a resource from a service.
- The service returns the payment requirement.
- The agent authorizes payment in that same interaction.
- The service delivers the resource.
Visa announced a card specification and SDK so card credentials can participate in MPP-compatible flows. The sequence illustrates the protocol design Visa describes; it is not evidence that every service currently supports it.
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Will agents pay with cards or stablecoins?
The emerging designs do not make cards and stablecoins an either-or choice. Visa’s framing is that cards fit proxy and consumer-scale purchases, while stablecoins can suit machine-native micropayments. Mastercard says Agent Pay for Machines supports settlement across cards, accounts, and stablecoins. These are providers’ descriptions of where their approaches may fit, not proof that one rail is universally faster, cheaper, safer, or accepted.
For a consumer purchase, a card-based flow can build on familiar merchant and payment systems while adding agent recognition, customer authorization, and tokenization. For machine-to-machine use, the design question includes whether a service can request and receive a very small payment as part of an automated exchange. MPP’s card specification is one sign that card credentials may be adapted for machine workflows; the existence of stablecoin-focused or onchain activity does not mean cards are excluded.
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What do reported transaction figures show?
Visa’s July 14, 2026 summary of a joint Visa-Artemis report says x402 recorded about $15.0 million in adjusted volume across 109.6 million transactions since its launch in May 2025. The underlying onchain figures are stated as of April 21, 2026. Visa says x402 was incubated by Coinbase and Cloudflare and is stewarded by the Linux Foundation. The same Visa summary says MPP settled about $25,000 across roughly 115,000 transactions in its first few weeks after launching in mid-March 2026. Visa reports that the average payment on both protocols was a fraction of a cent. Visa’s summary and cited Artemis figures describe early, dated activity—not settled mass adoption.
The x402 and MPP totals should not be combined into a market-size estimate: they cover different observation windows and stages of development, and their measurement methods may differ. The figures show that machine-payment protocols are being used and measured, but do not establish how representative that activity is of commerce as a whole.
What is still unresolved about trust and responsibility?
Recognizing an agent or setting a spending limit can help control a transaction, but neither feature by itself answers who is responsible if the agent buys the wrong thing or acts outside the user’s intent. Visa identifies possible responsibility questions involving the person who delegated the task, the platform operating the agent, the model developer, and the merchant. Those are open questions raised by Visa, not settled legal conclusions.
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Disputes may also become harder when an agent makes transactions rapidly or passes work through chains of agents. Existing chargeback processes are built around human-scale interactions, while machine activity can be faster and more numerous. Payment systems will need reliable evidence of what the customer authorized, what the agent did, and which parties controlled the action if a transaction is challenged. Visa discusses these issues in its account of agentic payment activity and open questions.
The International Monetary Fund’s April 2026 note describes emerging AI-agent uses in payment initiation, orchestration, routing, compliance checks, liquidity management, and settlement monitoring. It characterizes these as emerging design patterns rather than settled or standardized architectures. The IMF note, “How Agentic AI Will Reshape Payments”, offers a broader view of how agents could affect payment operations beyond checkout.
What should customers and businesses look for?
When evaluating an agent-enabled payment service, the useful questions are practical rather than tied to a particular protocol name:
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errors- Permission: What exactly did the customer authorize the agent to buy or do, and can the authorization be limited to a purpose, merchant, amount, or time period?
- Credential exposure: Does the agent receive reusable payment credentials, or does it act through a token or other mechanism that keeps the underlying credentials from the agent?
- Spending controls: Can limits and permissions be enforced during execution, rather than merely described as user preferences?
- Acceptance: Which merchants, services, agents, payment providers, and payment methods actually participate? Announced partnerships and protocol designs do not by themselves mean universal acceptance.
- Disputes: What record shows the customer’s instruction and the agent’s actions, and where should a mistaken or unauthorized transaction be challenged?
- Availability: Is the specific feature available for the customer’s region, account, merchant, and payment method now, or is it still described as a rollout or planned capability?
These questions matter because agentic payments are not one product category with one trust model. The landscape includes consumer purchases through familiar payment systems, machine-native transactions, and technologies intended to connect or secure those flows. The race is over the infrastructure and rules that will let sellers trust an agent’s authority—and let customers understand what happens when that trust fails.
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