Key Takeaways
- Mastercard introduced Agent Pay for Machines on June 10, a service that lets AI agents and connected systems pay one another automatically across its global network, with some payments as small as fractions of a cent.
- More than 30 partners signed on, including Stripe, Adyen, Coinbase, Cloudflare, OKX, Ripple, Polygon, and Solana, with settlement supported across cards, bank accounts, and stablecoins.
- Mastercard frames the product as long-term infrastructure for agentic commerce rather than a near-term revenue driver, joining rivals Visa, Stripe, and Google in the race to build payment rails for machines.
Mastercard rolled out a payments service on June 10 designed to let artificial intelligence agents transact directly with one another, deepening its push into a market where software, not people, initiates purchases.
Agent Pay for Machines, known as AP4M, allows transactions to be permissioned, orchestrated, and settled at machine speed across Mastercard’s global network, the company said. Some payments run as small as fractions of a cent and execute continuously in the background of digital commerce.
Agent Pay for Machines builds on Agent Pay, the consumer agentic program Mastercard introduced in 2025.
Where that effort defined how trusted AI agents make purchases for people, the new system targets automated, high-frequency payments between machines and services.
“Agent Pay for Machines will create the conditions for a superbloom of AI business models,” said Jorn Lambert, Mastercard’s chief product officer. He said machine payments can move at very high volumes, very small values, and extremely low latency.
How Agent Pay for Machines Works
Mastercard built the service around four functions:
- Credentialing each agent,
- Permissioning spending rules,
- Enabling agents to transact across systems, and
- Settling payments across multiple rails.
Organizations can set authorization limits that are enforced programmatically, keeping transactions within defined parameters.
Settlement spans cards, bank accounts, and stablecoins. Mastercard initially logs agent permissions onto public blockchains, including Polygon, Solana, and Base, according to the company. Identity verification ties each agent to its human or corporate owner through a feature called Verifiable Intent.
Mastercard offered one example of an entrepreneur instructing an agent to launch a flower shop’s website. The agent buys a domain, hosting, images, and checkout pages within a set budget, turning a single request into a chain of automated purchases across providers.
Crypto and Fintech Partners Back the Rollout
Initial participants include Aave Labs, Anchorage Digital, Ant International, BVNK, Checkout.com, Cloudflare, Coinbase, Getnet by Santander, Global Payments, OKX, Ripple, Solana Foundation, Stripe, and Tempo, among others.
Several are building stablecoin settlement and agent wallet infrastructure on top of the network.
Why Mastercard Is Betting on Machine Commerce
Agentic payment volumes remain a small fraction of overall commercial flows.
Lambert predicted AI assistants will eventually handle a meaningful share of online purchases, saying “it’s just easier for consumers to do.” He was less certain about machine-to-machine payments but said too much activity is underway for some version of the market not to take shape.
Mastercard enters a crowded field. Visa, Stripe, and Google have each released agent payment tools or standards over the past year.
Coinbase backs the x402 protocol, while Stripe and Tempo developed the Machine Payments Protocol. Mastercard has not set a public launch date beyond its initial partner phase.
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Dr. Guneet Kaur is a senior editor at CCN.com and a Science Fellow at Exponential Science. She is a fintech and blockchain expert with extensive experience in digital finance education, blockchain ecosystems, and cryptocurrency markets. She has worked with global media such as Cointelegraph, as well as education and blockchain platforms, to design and lead strategic content and learning initiatives. As an educator and assessor for top-tier executive programs, she bridges real-world fintech trends with academic insight.
Dr. Kaur is also a published researcher and peer reviewer across fintech and data science journals, including Financial Innovation Journal and International Journal of Big Data Intelligence and Applications. Her work spans data-driven analysis, Web3 innovation, and technical content development. With a strong foundation in both industry and academia, she translates complex financial technologies into practical applications, empowering learners, professionals, and institutions across the rapidly evolving digital finance landscape.
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