New in AI

COMMERCE · Retail Adoption

AI sent Shopify eight times more traffic. It sent thirteen times more orders.

When orders grow faster than visits, the visitors are different. Shopify's numbers say AI-referred shoppers arrive closer to buying than anyone else.

Chandni Melwani

Chandni Melwani

Founder & Editor

Jul 23, 2026 · 2 MIN READ

The News

For its first quarter of 2026, Shopify said referral sessions from AI chatbots to its merchants' stores grew more than 8x year over year while AI-referred orders grew nearly 13x. Shopify says new buyers place orders through AI channels at nearly twice the rate of other channels, that AI-referred sessions beginning on a product detail page convert at nearly 50% higher rates than organic search, and that orders attributed to AI-powered search carry 14% higher average order values than orders from organic search. In its May earnings release the company reported GMV of $100.7 billion for the quarter, up 35% year over year, and revenue of $3.17 billion, up 34%.

Know More

  • — The gap that matters: traffic grew 8x, orders grew ~13x. Orders outpacing visits means conversion improved, not just reach.
  • — Conversion: for sessions that begin on a product detail page, AI-referred visitors convert at nearly 50% higher rates than organic search. It is a scoped figure, not an all-traffic one.
  • — Basket size: AI-referred orders carry 14% higher average order values than orders from organic search.
  • — New customers: Shopify said new-buyer orders through AI channels occur at nearly twice the rate of other channels.
  • — How the traffic arrives: Shopify says Agentic Storefronts are 'active by default for eligible stores', making them discoverable in ChatGPT, Google AI Mode and Gemini, Microsoft Copilot, and Meta. Shopify's documentation states this without a date; the announcement post went up on March 24, 2026 and says only 'starting this week.'
  • — It was opt-out, not opt-in. Eligible stores were active by default rather than choosing to join, which is part of why the volume moved so fast.
  • — Not evenly available: Shopify lists Google AI Mode and Gemini as early access, and says it 'isn't yet available for all stores.'
  • — Where the purchase completes depends on the channel. ChatGPT sends the customer to the merchant's own checkout; for Google, Copilot and Meta, a store with direct checkout switched on lets the customer buy inside the AI channel. Shopify says there are no fees beyond standard payment processing for Copilot's direct checkout.
  • — Underneath it sits MCP, the Model Context Protocol — an open standard originally released by Anthropic that lets an AI assistant query an external system directly, which is how an agent reads a catalog in real time rather than crawling a page.
  • — Timing caveat: these are Q1 2026 figures, not a fresh release. The multiples, conversion and order-value numbers come from Shopify's own AI search insights post rather than the May earnings call, and Shopify has not published an updated set since.
  • — Not disclosed: the absolute size of AI-referred traffic. Every figure here is a growth multiple or a relative rate, so a 13x increase on a small base is still a small base.

Two numbers from Shopify’s first quarter are worth putting side by side. Referral sessions from AI chatbots to its merchants’ stores grew more than eightfold year over year. Orders referred by those tools grew nearly thirteenfold.

Orders outrunning visits by that margin is the whole story. Had both grown at the same rate, AI would just be a bigger pipe carrying the same kind of shopper. Growing apart means the shoppers themselves are different, and Shopify’s other disclosures say the same thing three more ways: among sessions that begin on a product detail page, AI-referred visitors convert nearly 50% better than organic search, those orders run 14% larger, and new-buyer orders arrive through AI channels at nearly twice the rate of other channels.

None of this happened because merchants opted in. Shopify switched on Agentic Storefronts for eligible stores during March, putting catalogs inside ChatGPT, Google’s AI Mode and Gemini, Microsoft Copilot and Meta by default — though the Google surfaces remain early access and are not yet open to every store. Underneath sits MCP, the open protocol that lets an assistant query a store’s catalog directly instead of scraping a page, which is what makes availability and specifications answerable in real time. Where the sale closes varies by channel: ChatGPT hands the shopper back to the merchant’s own checkout, while the others can complete the purchase in place when a store has direct checkout enabled.

The explanation for the conversion gap is not mysterious either. An assistant does the comparison before the shopper ever reaches a store. Questions about fit, alternatives and price get answered in the conversation, so the person who lands on a product page has finished researching rather than started. It is the same pattern Adobe found when it measured AI-referred shoppers converting 54% better, arrived at independently on different data.

What none of it says is how big the channel actually is. Shopify published multiples and rates, never absolute volume, and thirteen times a small number remains a small number. The honest read is that this is a quality signal rather than a size one. The work it points to is unglamorous and worth starting anyway: an assistant can only recommend a product it can parse, so structured product data is what decides whether a store appears in the answer at all, and that sits well upstream of anything on the storefront.

#Shopify#Agentic Commerce#AI Search#Conversion#Retail Adoption#E-commerce

Frequently Asked Questions

Why does it matter that orders grew faster than traffic?

It means the extra visitors were better qualified, not just more numerous. If traffic and orders grew at the same multiple, AI would simply be a bigger version of the same channel. Orders growing faster means a higher share of those visits ended in a purchase, which is what the separate conversion and basket-size figures also show.

Why would AI-referred shoppers convert better?

Because an AI assistant does the comparison work before the shopper arrives. By the time someone lands on a product page from ChatGPT or an AI search result, the questions about fit, alternatives and price have often already been answered, so they arrive closer to a decision than a browser who clicked a search result to start researching.

Do we know how big AI traffic actually is?

No. Shopify disclosed growth multiples and relative rates, not the absolute volume of AI-referred sessions or orders. A 13x increase tells you the direction and the speed but not the size, and a large multiple on a small base is still a small base. Treat these as a signal about quality of traffic rather than a measure of how much of the channel exists.

Is my store already in this?

Quite possibly, without having done anything. Shopify says Agentic Storefronts are active by default for eligible stores, and that millions of merchants can sell in AI chats — so this is opt-out rather than opt-in. Two caveats worth checking rather than assuming. Google AI Mode and Gemini are still early access and not available to every store, and where the purchase completes depends on the channel: ChatGPT sends the customer to your own checkout, while Google, Copilot and Meta can complete the sale inside the AI channel if you have direct checkout switched on. You manage which channels you sell on under Sales channels in the Shopify Admin.

What should a merchant do about this?

The practical work is making product data machine-readable, because an assistant can only recommend what it can parse. Structured product information, clear specifications and accurate availability are what determine whether a store appears in an AI answer at all. That work sits upstream of any storefront design change.

Sources

Chandni Melwani

Chandni Melwani

Chandni Melwani is the founder and editor of New in AI, covering AI agents, M&A, and enterprise adoption. She holds a Master's in Management of Artificial Intelligence from Queen's University and brings a practitioner's perspective from her work in Data and AI leadership.

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