Mastercard Launches Agent Pay to Enable AI-Driven Transactions
Mastercard collaborates with AI firms and banks to integrate payment capabilities into AI search platforms, streamlining transactions.
April 29, 2025 — Mastercard has unveiled Agent Pay, a groundbreaking payments program designed to integrate AI platforms like OpenAI, Anthropic, and Perplexity into its payment network. This initiative aims to eliminate the need for users to switch windows when completing transactions after an AI-assisted search.
Closing the Loop on AI Search
Greg Ulrich, Mastercard’s Chief Data and AI Officer, emphasized that Agent Pay "closes the loop" on agentic search by enabling seamless transactions within AI chat platforms. "You want to close the loop within the experience to enable the customer experience in the most effective way possible," Ulrich told VentureBeat.
How Agent Pay Works
Agent Pay leverages Mastercard’s tokenization technology, which uses cryptography to mask personally identifiable information (PII) during transactions. "It’s a separate number that is useless if it’s not used within the context of the transaction you authorized," explained Pablo Fourez, Mastercard’s Chief Digital Officer.
Key partners in this initiative include Microsoft, IBM, Braintree, and Checkout.com, who will help scale the system and enhance merchant features. Mastercard is also in talks to integrate Agent Pay into Microsoft’s Copilot and Azure/OpenAI services.
The Rise of AI-Powered Search
AI search platforms have evolved from simply listing information to actively assisting users with tasks like finding suppliers or booking travel. OpenAI recently added shopping features to ChatGPT, signaling a shift toward transactional AI.
Fraud Detection and Security
While Agent Pay doesn’t rely on generative AI, Mastercard uses AI models for fraud detection. "We’re making sure that we safely and securely identify these players in the ecosystem," Ulrich said.
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Dr. Sarah Chen
AI Research Expert
A seasoned AI expert with 15 years of research experience, formerly worked at Stanford AI Lab for 8 years, specializing in machine learning and natural language processing. Currently serves as technical advisor for multiple AI companies and regularly contributes AI technology analysis articles to authoritative media like MIT Technology Review.