Stripe's AI Chief: How AI Agents Will Buy, Sell, and Pay

**Emily Sands** (0:00)
Fraudsters have figured out that in AI, you actually don't really need to steal money or credentials, you can just steal tokens. And the scale of this actually shocked me when I looked at the data. So more than one in six signups at AI companies are this kind of abuse, whatever. The dine and dash, but it's for token. When I go and ask my friends and family whether they'd be comfortable letting an agent buy things on their behalf, they usually jump straight to like, well, is it going to overspend and is it going to buy the wrong thing? And can I stop it? And those are actually all legitimate concerns. And it's not Emily permissioning an agent to buy on her behalf. It's Emily has an agent who's tasked with running a business, and that includes buying some things and selling some things and making some profits. And that would be the world that I would like to be talking about 12 months from now.

**Matt Turck** (0:45)
Hi, I'm Matt Turck. Welcome back to The MAD Podcast. Today, I'm excited to be joined again by Emily Sands, Head of Data and AI at Stripe. The rise of agent e-commerce has only accelerated since Emily and I talked about it last year. And in this conversation, we go deep on the economic stack for AI agents, how agents buy and sell on your behalf, why per se pricing is breaking, token monetization, token theft, which Emily calls the most under discussed topic in all of AI, and finally, whether agents may eventually run entire businesses on their own. Please enjoy my conversation with the always excellent Emily Sands.
All right, so welcome back. You and I chatted about a year ago, and the theme of the discussion we had was all about the rise of agent e-commerce, keeping in mind that obviously this is a long-term trend that's going to take a while to play out. I'm curious about what you've observed over the last 12 months. What has become reality and what is yet to be built?

**Emily Sands** (1:49)
Yeah, I mean, a year ago, we were talking about agents as buyers in a pretty hypothetical way. I think that the canonical experiences, the consumer experiences, for example, weren't defined. We were largely reasoning kind of from first principles about what this might look like. Fast forward a year, as you note, like still early innings, still a lot to do, but we have actual infrastructure deployed. We have real companies building on it. We have real patterns to learn from.
And to be clear, the shape of how this unfolds has become more clear and it's going to continue to evolve. Specifically, what we've come to believe is there's a full spectrum of how Agent E-Commerce plays out, and that's actually really important for businesses in how they think about it. At one end, and this is where our machine payments protocol lives, but basically, you have agents that are out autonomously discovering a service and deciding to buy it and handling the transactions entirely on their own, like no human in the loop. That's maybe what people think of when they say Agent E-Commerce, but that's just one end of the spectrum. There's also the whole other end of the spectrum where people are looking for shoes for flat-footed runners inside an AI surface, and the AI surface gives you an answer, and increasingly, that was true also in traditional search, but now increasingly that answer comes with a buy button.
This is already how a huge number of people are discovering products. If you're a business, you need to show up there, and we've been building the infrastructure to make it, A, easy for businesses to show up, and B, easy for agents to execute those transactions. You asked about what's become more concrete. We recently partnered with Google, so merchants can sell right inside AI mode in the Gemini app.
Maybe you shop at JD Sports because I was on the topic of running shoes, or Fanatics, or Quince. Those were all early adopters. Microsoft and OpenAI were doing something similar with them, like helping businesses make their products discoverable inside Copilot and ChatGPT. Meta is another example, a little bit of a different flavor, but we're powering checkout right inside ads. So there's the discovery and then the one-click, and the agent actually goes and executes the transaction on your behalf. But really, I'd say what we've learned over the last year, the through line is whether we're talking about fully agent-led transactions with MPP or these very human-led purchases inside AI surfaces, there's just a new set of infrastructure that needs to work no matter where you are in the spectrum.