For decades, e-commerce rewarded the biggest brands that could buy their way to the top of search results. AI is changing that. Shopify COO Jess Hertz shares what Shopify’s data reveals about the agentic shopping revolution in real time, and how the company is building the infrastructure layer that makes products discoverable and purchasable by AI. Plus, why Shopify’s engineers can spend freely on AI tokens while the rest of the business world agonizes over ROI, and what it looks like when a company powering over 14% of online shopping decides to win the future or die trying. This is an abridged transcript of an interview from Rapid Response*, hosted by former *Fast Company editor-in-chief Robert Safian. From the team behind the Masters of Scale podcast, Rapid Response features candid conversations with today’s top business leaders navigating real-time challenges. Subscribe to Rapid Response wherever you get your podcasts to ensure you never miss an episode.
Shopify just posted its, I think, fifth consecutive quarter of growth above 30%. How much of that growth is sort of stealing share to make that happen, like from Amazon or someone else, and how much is about AI? There is a lot of discussion around AI and agentic shopping, but how much business is it really?
The way I think about it is really in two pieces. One is our core business, which is incredibly durable, and the second is that AI is expanding our upside. On the core business piece, the best statistic I can give you to think about this is that almost 90% of our quarterly revenue is from merchants who’ve been on the platform for over a year. That growth compounds, and it really shows how strong the business actually is. But on the agentic side, while that agentic GMV [gross merchandise value] is small, it’s definitely growing.
We do have early signs that Sidekick is helping merchants sell more, and merchants who are a part of Catalog are really starting to make more money. For listeners who may not be as Shopify-versed, Sidekick is our AI-powered commerce agent that lives within Shopify. What we’re really seeing is that merchants are bringing Sidekick more and more into their business. On the Catalog piece, that’s our product layer for agentic commerce. That’s what makes products understandable, discoverable, and purchasable by AI.
What we’re seeing there is that it is increasing conversion. When someone comes from an agentic channel, the conversion rate when an agent is using our catalog data is [double] compared to if it’s just using scraped data. So it’s really the combination of these persistent tailwinds in our base case and, as we enter the agentic era, even more upside.
You’re building this sort of infrastructure layer for AI commerce. You have these agentic storefront integrations with ChatGPT and Gemini and Copilot, whatever. How much do you worry that the big AI platforms are going to build their own layer?
What I would say is I think we’re past that SaaSpocalypse moment. Shopify has certainly come out the other end of that. The way I really think about that is, complexity is both the challenge and the moat for Shopify. As you mentioned, we’re building all of these products, but when you think about it, a complex world helps Shopify. We’ve always been a unified operating system for commerce. We’ve always acted as this aggregator of different ways to sell, whether that’s an online store, in-person retail, or agentic commerce. And with buyers across different channels, it helps Shopify actually do better because that complexity is hard. It’s hard for merchants to be able to manage that on their own. So I think what’s even more scarce in this AI world is that infrastructure that you’re talking about, right? And building that complete stack for the merchant.
And for those merchants who are looking at agentic shopping and this future of having an AI agent between them and a customer, they’ll be relying on Shopify to help them manage that—which is good for you, but might also make them feel a little more beholden, a little more trapped?
I don’t think they’ll feel trapped. I think the nice part about Shopify—even if you look at things like the Universal Commerce Protocol, which is the open commerce standard that we developed with Google, which is really the transaction layer of commerce—is that the merchant continues to be the merchant of record. So the idea is not that we’re trying to do anything in terms of disintermediating the merchant. It’s really facilitating for merchants the ability to have that one business and have it work everywhere commerce happens.
And so that is really at the core of what our products and partnerships are trying to accomplish for the merchant.
I was talking to Uber’s COO, Andrew Macdonald, a few months back. I don’t know if you know Mac, but he ignited this meme about the hidden costs of AI.
Yeah.
You know, that, “Oh, I’m spending money on these tokens that maybe I’m not getting a return on.” And I’ve heard that your team can still access tokens mostly without restriction.
Yes. I think we see a very healthy ROI. Now look, the idea of adoption is never going to be the same thing as impact, so that is definitely true, and we are thinking through ways to measure impact. Head count for Shopify has been flat for more than eight quarters, while revenue is growing 34%. So I think from an ROI, pure financial company perspective, we are doing quite well. I think the other piece to it is that we work carefully in terms of moderating that type of cost. We have a pretty open and flexible view, and we want engineers to be able to use the best models for the best circumstance. Obviously, we have thoughtful speed bumps built in along the way. We’re constantly monitoring it. We’re constantly making sure we’re providing the best tools that we can. But it is not something we take lightly. We are a fairly pragmatic company at bottom.
To generate that higher productivity, which is basically what you’re talking about AI doing, doing more revenue with the same number of people, I heard you say that the ideal employee has evolved from being a T-shaped person to an X-shaped person. Can you unpack that for us?
It’s another one of my pet theories, so I’ve given you some of my pet theories today. When I joined Shopify, we had this idea of the T-shaped person, right? So you have lots of breadth, but you still have this one vertical that you go deep in, which is your craft, right? For me, that would be a legal craft or a regulatory craft. But what I think we’re starting to see is AI is really pushing toward what I’m calling X-shaped people, right? So you have multiple spikes of expertise, are able to absorb complexity much faster, learn new spaces and be a 7-out-of-10 designer if you want to be, right? Or I try to do my own data work now. So you’re able to move across domains faster. I’ve created this analogy in my head where now you see different slices, right? You have different vectors of expertise, and you’re really moving away from the expectation that you have to have depth in just one area.
The other part is really how those different-shaped people actually intersect with each other. I think the idea of team composition and the different constellation of people will only become more and more important as we enter this AI world. It’s actually that team combination that becomes the accelerant to incredible amounts of work that you couldn’t even imagine. And some of that magic is trying to say, “Okay, where are people’s edges? How do they fit together? And how is this sort of shape of employee changing over time?”
When you first started describing the X shape, I was thinking, “Oh, this is what we used to call a generalist, maybe a higher-level generalist.” But then when you talk about the teams, they’re generalist specialists because you’re fitting them together in different ways.
Exactly. I think a little bit about Tetris, maybe. It’s not that you’re a pure generalist and a pure athlete. It’s that you have the ability to go deep in different areas. You still might have specialized areas of expertise, right? So I still might have a legal background, some craft expertise in certain areas. It’s just that I can learn different areas much faster because I have different tools available to me. So now I not only have a legal or a talent sort of pie or quadrant to me, I’m now deep in commercial, so I’m able to generate these areas of expertise in a much different way than I was five years ago.