Virtual Cards for AI Agents: How Agentic Payments Work

AI agents can already do quite a lot online. They can find information, compare services, manage subscriptions, and take care of routine tasks. But what if we want them to do more than that? For example, buy software, pay for services, or handle other business expenses without an employee stepping in every time.

The question is how to let AI agents make payments without giving them full access to company funds. Virtual cards offer one way to do this. A company can give an agent its own card, set spending limits, and control what it can pay for.

In this article, we'll look at how agentic payments work, how virtual cards fit into the process, and what it takes to let AI agents handle payments safely.

Agentic payments allow AI agents to pay for goods and services on behalf of people or businesses, within rules set by the person or company authorizing them.

Take a regular subscription payment. You set up a $100 monthly subscription, and the system charges your card automatically. It simply follows the payment schedule.

With an AI agent, you could ask it to find suitable software for a project, compare prices, choose a plan, and pay for it. Unlike regular automation, the agent can decide what to buy and which option to choose.

That doesn't mean giving the agent unlimited access to your bank account. The company still decides how much it can spend, what it can buy, and when it needs approval.

A typical agentic payment setup includes:

• AI agent — finds a product or service, decides what to buy, and requests payment.
• Authorization system — checks whether the purchase is allowed.
• Payment method — a virtual card, payment token, or another supported option.
• Payment infrastructure — processes the transaction and checks the applicable restrictions.
• Transaction monitoring — records the merchant, payment amount, and the agent responsible for the purchase.

If an AI agent needs to pay for something, why not give it a separate payment card with its own spending limits?

A virtual card works like a regular payment card, but exists only in digital form. It has payment credentials for online purchases and can be managed through an API, depending on the issuing platform.

Businesses already use virtual cards for advertising, software subscriptions, and employee expenses. AI agents can use them for similar purchases.

— Separate budgets. A company can give each agent its own virtual card instead of sharing one corporate card between different systems. Cards can also be issued for individual projects, purchases, or tasks.

— Spending limits. Cards can have monthly or per-transaction limits, as well as restrictions on merchant categories or specific vendors, where supported by the issuer.

— Payments at existing merchants. Virtual Visa and Mastercard cards use established payment networks. An agent can potentially pay at online stores and services that already accept these cards, although some purchases may still require additional authentication.

— Expense tracking. Each card can be linked to a particular agent or task in the company's system. This allows individual charges to be assigned to the right project.

— Control through an API. Cards can be issued, frozen, blocked, or closed programmatically. The company can also deactivate a card once the task is complete.

A virtual card alone doesn't make payments autonomous. The application still needs to check what the agent is allowed to buy and handle the checkout process.

Suppose a company uses an AI agent to run its Meta Ads campaigns. The agent creates ads, manages budgets, and monitors results. To pay for advertising, the company uses a dedicated virtual card.

The company gives the AI agent a monthly advertising budget of $500 and permission to manage its Meta Ads campaigns.

The agent can adjust campaign spending without asking for approval each time. Increasing the total $500 budget, however, requires approval.

The application enforces these limits separately from the agent's instructions.

The application requests a dedicated virtual card through a card issuing API instead of using the company's main corporate card.

The card is linked to the advertising account and the agent's task in the company's system. An authorized user can then add it as a payment method in Meta Ads.

The company sets a $500 advertising budget in its application and can apply additional limits to the virtual card, where supported by the issuer.

The advertising budget controls campaign spending, while card limits control which payments the issuer can authorize.

Meta doesn't charge the card for every ad. Advertising costs accumulate, and Meta bills the account later. This means the application needs to track campaign expenses separately from card transactions.

The agent creates ads, selects audiences, and monitors results through an authorized integration with Meta.

If one campaign performs better than another, the agent can shift part of the approved budget toward it.

With automatic billing, Meta generally charges the card when the advertising account reaches its payment threshold or on its monthly billing date.

The charge goes through the card network, and the issuer checks the available funds, card status, and applicable spending limits before deciding whether to approve it.

If the payment is declined, advertising may be interrupted until the billing issue is resolved.

After Meta charges the virtual card, the issuing platform records the transaction.

The company's application can retrieve payment information through an API or receive transaction notifications through webhooks, where supported.

It can then compare card transactions with advertising expenses reported by Meta.

If the company stops the campaigns, it can revoke the agent's permissions and deactivate the virtual card when it's no longer needed.

Beyond advertising, AI agents can handle software purchases, travel bookings, and routine procurement.

— SaaS Subscriptions and API Access. An AI agent working on a development project could purchase API credits, cloud resources, or software subscriptions as needed.
A dedicated virtual card would keep these expenses within the project's approved budget and help track recurring payments.

— Advertising and Marketing. For companies managing multiple advertising accounts, separate virtual cards help keep payments and budgets organized.
AI agents can manage campaigns on Meta Ads, Google Ads, and other platforms through supported integrations, while each advertising account has its own payment method and spending limits.

— Travel and Booking. An employee could ask an AI agent to arrange a three-day business trip to London. The agent would compare flights and hotels, book suitable options, and pay with a virtual card assigned to the approved travel budget.
The payment setup would also need to account for hotel deposits, delayed charges, cancellations, and refunds.
— Procurement and Supplier Payments. An AI agent could monitor office supply levels and reorder items from approved suppliers when stocks run low.
A dedicated virtual card would allow it to pay for these purchases within the company's spending limits, without requiring an employee to complete every order.
— AI Platforms and Multi-Agent Systems. An AI platform could integrate a card issuing API to provide virtual cards for its customers or individual agents.
Each customer or agent could have separate spending limits and transaction records, managed through one integration.

Besides virtual cards, AI agents can use payment tokens and, in some cases, stablecoins. These methods work differently.

Virtual cards use existing Visa and Mastercard payment networks. AI agents can use them to pay for software, subscriptions, advertising, and other services that accept card payments, subject to the card program's rules and merchant requirements.

Through a card issuing API, businesses can create cards, set spending limits, and track transactions.

Payment tokens let AI agents make purchases without accessing the original card details.

For example, Stripe offers Shared Payment Tokens that can be restricted to a specific merchant, amount, and period of validity.

Visa is developing Intelligent Commerce, while Mastercard has introduced Agent Pay. Both are working on ways to let authorized AI agents make purchases using controlled payment credentials.

Unlike a separate virtual card, a token can provide limited access to an existing payment method.

AI agents can also make payments from stablecoin wallets.

For example, Coinbase's x402 protocol allows compatible applications to pay for API access and digital services using supported stablecoins.

This can be useful for small, frequent payments between software services. However, the receiving service must support the payment method. An agent can't use stablecoins at a store that only accepts bank cards.

Several protocols address different parts of agent-driven shopping and payments:

• Agentic Commerce Protocol (ACP) — developed by OpenAI and Stripe to support shopping and checkout through AI agents.
• Universal Commerce Protocol (UCP) — Google's protocol for connecting AI shopping experiences with merchants.
• Machine Payments Protocol (MPP) and x402 — protocols for payments between applications and services.
• Model Context Protocol (MCP) — allows AI agents to connect to external tools and APIs. MCP doesn't process payments itself.

If a card issuing platform provides an MCP server, an agent could use it to request a virtual card. The payment itself would still go through the card network.

AI platforms can use a card issuing API instead of building their own card infrastructure.

The API handles card issuance and management, while the application controls the agent's purchases and permissions.

With the CardsPro API, businesses can issue and manage virtual cards, work with card balances and spending limits, and track transactions.

CardsPro supports USD and EUR card programs, with access to more than 20 BINs across jurisdictions including the US, UK, Hong Kong, Singapore, and Estonia. Available features and restrictions depend on the selected card program.

For example, a platform that provides AI agents to business customers could use CardsPro to issue separate cards for different customers or tasks.

When an agent needs to make a purchase, the application can request a card through CardsPro, apply the relevant spending controls, and link the resulting transaction to the agent's task.

The application must also manage secure checkout, user authorization, and any additional payment verification required by the merchant.

Before launch, developers should confirm that the chosen card program supports the intended payment scenario.