Mastercard Expands AI Agent Payments, Launches Crypto Partner Program

Agentic AI is shifting commerce from human-initiated checkout toward software that can search, decide and pay within a user’s mandate. That raises new demands around identity, authorization, fraud controls and disputes, making payment infrastructure a strategic battleground. Mastercard is extending its card network, tokenization and transaction data into the “prompt economy,” seeking to preserve its role as a trusted intermediary as banks, Visa and technology platforms build competing rails for autonomous commerce.

Mastercard launched Agent Pay for Machines on June 10, 2026, enabling continuous machine-to-machine payments across cards, bank accounts and stablecoins, including microtransactions worth fractions of one cent. More than 30 early participants include Adyen, Stripe, Coinbase and Cloudflare. On the company’s July 30 earnings call, Chief Executive Michael Miebach said Mastercard’s global network and data scale should keep it central to agentic commerce despite competition from banks and technology giants, as the company moves the product from pilots toward broader adoption.

AI agent payments allow systems not only to recommend products but also to complete transactions autonomously within spending limits and authorizations set by users. The significance of the collaboration between Banco Santander and Mastercard lies in bringing this form of agentic commerce into a regulated banking framework and testing whether existing payment networks can maintain security, privacy and consumer protection.

On March 2, 2026, Banco Santander used Mastercard Agent Pay in a controlled environment, with PayOS providing end-to-end orchestration, to complete Europe’s first live transaction initiated and executed by an AI agent through Santander’s existing payment infrastructure. The companies did not disclose the transaction value and stressed that the project remains a pilot and has not been commercially launched. They plan to expand testing and explore additional use cases.