A new kind of shopper is buying online, and they may already be shopping at your store.
AI assistants are reshaping how shoppers discover, compare, and purchase products. After all, half of all consumers now use AI when searching the internet, including when they’re researching what to buy and making comparisons.
That’s where brands can benefit from this spike in AI-driven product discovery. AI-referred traffic from assistants like ChatGPT and Gemini to retail sites grew 393% year-over-year in Q1 2026 — and it’s not just growing; it’s converting. This traffic already outperforms non-AI traffic (a bucket that includes paid search and email) by 42%. That’s a full reversal from just a year earlier, when it converted 38% worse than everything else.
That’s a strong signal of a major opportunity for brands. But few storefronts are built for AI to find, let alone recommend.
Why AI agents aren’t discovering your products
The short answer: your store and your products aren’t simple for AI assistants to find. And by 2027, half of enterprises will lean on AI agents to redefine how humans and machines collaborate. And those agents only build trust based on what they can verify.
No one has published hard data linking visibility scores directly to lost recommendations or revenue. But when an agent can’t analyze content, it doesn’t get matched to a shopper’s question, and a product that isn’t matched doesn’t make the shortlist of AI recommendations.
To avoid losing out on increased AI-referred sales, review these trust signals to understand where your store stands with AI shoppers.
When an agent can’t analyze your catalog, it skips your store
An AI agent won’t care if your product is the best fit for what a shopper needs. If it can’t easily evaluate your products, you don’t show up in the shortlist. Our study with IDC on agentic commerce puts a fine point on it: if AI can’t read your content or catalog, you’re not considered, you don’t make the sale, and, worst of all, you basically don’t exist.
This is a pervasive problem: a third of the content on an average US retailer’s product page isn’t machine-readable. Product pages were actually the least readable pages the study measured, only lagging behind homepages.
AI assistants need to find your store and read your catalog to evaluate whether 1 of your products fits the needs of a shopper asking for recommendations. IDC calls this the “agent buyer”: it discovers products through structured catalogs and machine-readable metadata, evaluates data quality over design, and won’t recommend brands it can’t verify.
Let’s say a shopper uses AI to find a digital picture frame. Two stores sell the same product at the same price. One has all the product specs and structured attributes readily available for the AI agent to find and read. The other only has marketing copy. Only 1 will show up when a shopper asks an agent to shortlist options — and it has nothing to do with ad spend.
The good news: WooCommerce automatically maps many core product fields—think product title, description, image, SKU, price, currency, and stock status—to Schema.org JSON-LD on product pages. This gives search engines and compatible agents the structured product data they need to discover products more easily. Stores may need extensions or custom markup for richer fields and variation-level data.
Stale stock and inconsistent pricing are trust failures agents don’t forget
Agent trust doesn’t work like customer complaints. While you can offer excellent service to smooth over a poor experience with a customer, agents aren’t as forgiving.
IDC found that 80% of agentic AI use cases will require real-time, contextual data access by 2027. Live, accurate inventory is 1 of 3 pillars agents need before they’ll trust a store enough to recommend it or even make a purchase.
Bad recommendations — like an item that’s actually out of stock or a price that changes at checkout — and the agent will deprioritize that store going forward. It goes beyond losing that single sale; it can cost the store its standing, the way a low seller rating impacts a marketplace listing.
The good news: Agents focus on your product pages, and WooCommerce keeps stock levels updated as orders come in. So brands have an accurate, centralized view of their site inventory. Extensions also let you extend that single source of truth across multiple channels or sales locations.
Brands often complicate decisions by catering to 2 different buyers
Most teams mistakenly treat human conversion optimization and agent readability as 2 separate projects, with separate owners and budgets. IDC’s guidance says otherwise: build for humans and agents in parallel, because structured catalogs, clean data, and live inventory are now table stakes for being recommended by AI agents at all.
Brands often convert human buyers with a story, while agent buyers act only on what they can verify.
Human buyers discover through story, imagery, and community, and reward transparency and lifestyle context. Agent buyers discover through structured catalogs and machine-readable metadata, and reward clean inventory, accurate pricing, and reliable fulfillment. That means your store has 2 audiences and jobs to do.
Source: IDC study
The good news: Because WooCommerce sits on an open stack, merchants don’t have to hand “AI infrastructure” to a separate vendor. The platform uses the same product data, relies on the same team, and follows the same roadmap.
Agents act on pricing and attribute mismatches across channel
An agent that finds different product prices or specs across your site, a marketplace listing, and a social storefront doesn’t flag the inconsistency. It moves on to a competitor.
IDC calls this “the collapsing stack” — the push toward 1 source of commercial truth, with agents losing trust in a brand’s data when they find mismatched information. The same study calls for “consistent identity“: the same product story, attributes, and policies across every channel and surface.
The good news: You can easily audit pricing and product attributes. WooCommerce serves as your CMS and data source, powering your site, your feed, and soon, agent-facing surfaces. Fix a price or an attribute once, and every sales channel can pull from the same corrected source.
Help AI find your store
↑ Back to topThis channel is already growing faster than the others you’re optimizing. But the numbers are still small, so it’s the perfect time to get ahead of the trend/competition.
Start here: Export your catalog and look for missing attributes. No need to redesign your product pages, no new budget line — just a decision-maker handing a short scoping task to whoever runs point on the catalog.
When you’re ready to act on what the export returns, the mechanism behind everything [covered here] walks through how agents read a store and what to do with it.
Want the complete data picture behind this argument? Download the full IDC x WooCommerce study.
Feeling stuck with your ecommerce solution? Let’s talk.
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