AP2 is designed to “securely initiate and transact agent-led payments across platforms,” according to a Tuesday (Sept. 16) company blog post.
Google is collaborating on agentic payments with more than 60 companies, some of which include Adyen, American Express, Mastercard, PayPal, Coinbase and Revolut, per the post.
“AI agents are capable of transacting on behalf of users, which creates a need to establish a common foundation to securely authenticate, validate and convey an agent’s authority to transact,” the post said. “While today’s payment systems generally assume a human is directly clicking ‘buy’ on a trusted surface, the rise of autonomous agents and their ability to initiate a payment breaks this fundamental assumption and raises critical questions that AP2 helps to address.”
The questions are authorization, or proving that a user gave an agent authority to make a specific purchase; authenticity, or allowing merchants to be sure an agent’s request reflects the user’s intent; and accountability in cases of fraud or incorrect transactions, per the post.
The protocol can be used as an extension of the Agent2Agent (A2A) protocol and Model Context Protocol (MCP). In conjunction with industry rules and standards, it offers a payment-agnostic framework for users, merchants and payments providers to transact across all types of payment methods, the post said.
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PYMNTS Intelligence’s August edition of The Prompt Economy Tracker® Series explored the rise of MCP, an open standard that was introduced by Anthropic in late 2024 and has since been adopted by OpenAI, Microsoft and Visa.
“MCP is the digital equivalent of USB-C for agents,” the report said. “It defines how agents plug into data, invoke APIs, talk to other agents, and complete tasks securely and efficiently. This is the infrastructure that transforms agents from smart tools into autonomous actors inside the commerce ecosystem.”
Meanwhile, a July PYMNTS Intelligence report, “Payments Execs Say AI Agents Give Payments an Autonomous Overhaul,” revealed that agentic AI could demand new infrastructure, trust frameworks and corporate oversight.
AI agents require real-time, scalable, secure infrastructure, the report said. Legacy systems can’t deal with thousands of concurrent autonomous agents acting on APIs, analyzing data and triggering actions across systems.
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