The Rise of Agentic Commerce — Emily Glassberg Sands (Stripe)
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What is Stripe’s overall scale and impact on the global economy?
Stripe's network handles on average about fifty thousand new transactions every minute. To put that in perspective, because it's a lot of zeros, that's about one point three percent of global GDP.
Welcome back to the Matt Podcast. Today I'm sitting down with Emily Glassberg Sands, head of information at Stripe. Once a payments API startup, Stripe has become one of the most legendary companies of this generation and a full financial infrastructure platform that moves 1.3% of the world's GDP online. We talked about why Stripe decided to build its own AI financial model and what it learned in the process.
Stripe is a little bit different. We have really differentiated data. OpenAI doesn't have that data. Anthropic doesn't have that data. Our first instinct was actually full on wrong.
We also discuss the brave new world of gent e commerce, where agents will buy and sell on our behalf, and what it means for payments and new infrastructure like MCB servers.
Who's doing the buying is different and where they're doing the buying is different. It's pretty clear that MCP is becoming the default way that any single service, Stripe or GitHub, or Notion talks to an LLM.
We close the conversation covering fun Stripe data about the incredible rise of this generation of AI startups.
They are monetizing faster than any previous generation of startups that we've seen. Those that already hit 30 million in annualized revenue got there in about a year and a half. For comparison, the fastest growing SaaS startups on Stripe took five and a half years to hit that same mark.
We're living in an era where AI is increasingly rewriting commerce, money movement, and risk. And this episode is a great way to make sense of where the world is going. Please enjoy this terrific conversation with Emily Glassberg Sans. Emily, welcome. Thanks for spending time with us.
Delighted to be here. Thanks for having me.
All right. So everyone in tech obviously knows Stripe, which is a monster of a company. But maybe for context, what is the latest and greatest way of describing the full breadth of what the company does and maybe the latest stats?
Well, Stripe builds programmable financial infrastructure. So put kind of less buzzwordy, we are giving any business, whether it's a 20-year-old selling a Figma template or now more than half of the Fortune 100s, the rails and the intelligence to move money online and to grow faster. You asked about the numbers last year. Companies processed about $1.4 trillion on Stripe. To put that in perspective, because it's a lot of zeros, that's about 1.3% of global GDP. And that number grew 38% year over year in what many experienced as kind of a rocky macroclimate. Stripe's network handles on average about 50,000 new transactions every minute. So those are the transactions that are adding up to 1.4 trillion in payments volumes processed annually.
And every one of those transactions is training data for some. Of the AI systems that we will talk about today. I would just say because of the flywheel, like Stripe is no longer the payments API. If we were talking 10 years ago, we'd be talking about a payments company. But in practice, we're optimizing now the entire payments lifecycle: the checkout, user experience, fraud prevention, bank routing, automatic card update retries, even how you handle disputes. As a business. And that's all in service of merchants' profits, right? Growing their revenue and reducing their costs. And so I think of sort of the tools we're creating as generating a structural tailwind for the internet economy, for growth in any environment.
And we're already seeing it. Businesses on Stripe grew seven times faster. Last year than the S P 500. So it's it's that infrastructure creating a structural tailwind for growth that's our primary focus.
Amazing. All right. So we're going to unpack uh some of this. Uh before we do that, you are head of information at Stripe. What does that mean? What does your remit cover?
Yeah, our information org is really focused on three things. One is how do we use data effectively?
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Chapters
8 chapters
1
What is Stripe’s overall scale and impact on the global economy?
0:00–7:57
2
How does the Head of Information role shape data, ML, and experimental projects at Stripe?
7:57–17:54
3
Why did Stripe decide to build its own payments foundation model and what were the early challenges?
17:54–26:57
4
How did the team choose a BERT encoder over GPT‑style decoders for the foundation model?
26:57–35:21
5
What improvements did the foundation model bring to real‑time fraud detection and card‑testing detection?
35:21–43:51
6
How is agentic commerce reshaping the checkout experience and payment flows?
43:51–52:06
7
What is the Model Context Protocol (MCP) and how does it enable AI agents to transact on Stripe’s behalf?
52:06–1:00:19
8
How are AI‑driven pricing models (usage‑based and outcome‑based) changing billing for AI startups?
1:00:19–1:15:13
Speakers
1 identifiedMore from The MAD Podcast with Matt Turck
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Stripe's AI Chief: How AI Agents Will Buy, Sell, and Pay