Visa is experimenting with agentic artificial intelligence that would add automated execution for consumers to queries on large-language models. Executives wouldn’t put a timetable on when these products will go live, but they are being tested in internal sandboxes. Jack Forestell, San Francisco-based chief product and strategy officer, explained how the first iterations of agentic AI will work. “We formed a point of view that AI and specifically agent-driven AI has the potential to radically transform the way we discover, the way we shop and the way we buy,” he said. Forestell’s teams have thought through all of these things. This doesn’t mean the service is flawless – it’s experimental – but it’s ready to go live. Stephen Karpin, Singapore-based president of Visa’s Asia-Pacific business, says this is the latest iteration of a move by the company from organizing itself around products, toward services. “This involves a combination of our infrastructure, capabilities, and APIs to create a ‘Visa as a Service’ stack,” he said, noting this is only possible because the company has spent decades building the foundations of its payments-processing network. “We are shifting to a services architecture that includes risk management, settlement, credential directors, and now tokenization,” he said. “This is now all scaling.” Visa reckons there will be massive demand for agentic AI. Forestell noted OpenAI and the like have quickly amassed more than 1 billion active users. Traffic volume from LLM sites to retail and marketplace websites is rising fast. What’s missing is the ability to pay directly off the back of a query. LLMs don’t have access to credit-card numbers or passwords. And there’s no trust factor: consumers fear agents would misrepresent them or steal their money; banks can’t tell if an agent is legitimate; merchants aren’t confident they’ll be paid. Forestell says Intelligent Commerce has been engineered for people to buy with AI and be confident the payment is as safe and secure as it is with a credit card.
. It’s really about tokenization. This involves three components: upgrading cards to handle agents; enabling agent transactions; and personalization to make LLM queries more relevant. This AI-prep work is focused on tokenization, which payments companies have applied to other digital payments for a decade or so. This involves replacing the 16-digit number on a plastic card with a unique, cryptographically protected code, like a one-time pass that is linked to an account but if hacked doesn’t provide access to funds or instructions. This abstraction layer is being refitted for agentic AI, meaning these tokens can interact with agents. This capability is augmented by services that sync payment instructions, and signals that ensure all authorized parties in a transaction have the same access to data for processing, detecting fraud, and handling disputes.