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Visa partners with OpenAI to power agent-led payments

Visa and OpenAI announced a partnership to integrate Visa's payment capabilities directly into OpenAI's platform, enabling AI agents to make secure, verified purchases. The collaboration addresses a critical infrastructure gap for agentic commerce, which McKinsey estimates could reach $1 trillion to $5 trillion globally by 2030, giving merchants and payment networks a standardized framework to handle agent transactions safely.

Visa Inc. and OpenAI announced a partnership at Visa's Payments Forum in San Francisco to support agent-led payments by integrating Visa's payment capabilities into OpenAI experiences (Digital Commerce 360 - AI). Under the collaboration, developers and merchants gain a new framework to verify and process purchases that AI agents make. Payments will use tokenized Visa credentials, real-time authorization, and fraud monitoring, while users can set guardrails on how much agents can spend, which merchants they can transact with, and when human approval is required.

The partnership positions Visa and OpenAI to capture a major shift in commerce infrastructure. McKinsey & Company estimates agentic commerce could account for up to $1 trillion in U.S. B2C retail sales by 2030, with global volume potentially reaching $3 trillion to $5 trillion (Digital Commerce 360 - AI). For commerce practitioners, this standardized payment infrastructure removes friction from agent-enabled transactions and establishes security guardrails essential for scaling autonomous shopping experiences.

The move builds on Visa's earlier agentic commerce initiatives, including Visa Intelligent Commerce launched in April 2025 and its Trusted Agent Protocol rolled out in October 2025 (Digital Commerce 360 - AI). Visa also announced new tools including Agent Score, an Agentic Directory, and a Large Transaction Model for fraud detection. Mastercard responded this week with its own Agent Pay for Machines service, designed for agent-to-agent transactions and business-to-AI commerce use cases.

Sources:1 report