Your Catalog Is About to Have Customers You Never Meet

Think about the last thing you bought after asking an AI. Maybe you typed “what’s the best X under $100” into ChatGPT and just trusted the answer. A lot of people now do this instead of opening ten tabs and reading reviews. The AI names a product, and that’s the shortlist.

Now flip it around. Someone did that about your product category this morning. The AI named some products and skipped others. And if you run a store, you almost certainly have no idea what it said.

This is the strange new gap in e-commerce. You know your Google rankings cold. You know your conversion rate, your ad performance, which campaigns are pulling. But when a shopper asks an AI what to buy, you can’t see which of your SKUs it recommends, which it ignores, what price it quotes, or where it sends the buyer once it’s decided. The single most decisive moment in the funnel, the recommendation itself, happens completely off your radar.

And it’s getting more decisive, not less. Conversational product discovery is now just a feature inside the tools people already use. The infrastructure underneath it is being poured right now, with standards for how AI agents discover products, compare them, and eventually transact on a shopper’s behalf. The plumbing for agentic commerce is being laid in front of us. Soon the “customer” evaluating your catalog won’t even be a person scrolling. It’ll be an agent reading your product data and making a call.

That’s the part worth sitting with. An agent doesn’t squint at your beautiful photography or get charmed by your brand voice. It reads attributes. It compares specs. It checks whether the price it has for you is current. If your product description is missing the exact dimension the AI uses to compare your category, you don’t lose on quality, you lose because you were unreadable. The gap between what the AI measures and what your page says is where sales quietly leak.

The brands that win here will be the ones who treated this as a visible, measurable surface while everyone else assumed it didn’t apply to them. You can’t optimize a moment you can’t see. And right now, for most catalogs, the whole AI-recommendation layer is dark.

The window to shape your position, rather than react to it after agents are already transacting, is open now. beket.ai brings that dark layer into the light. We show you how AI represents your products, where it’s quoting stale prices or missing key attributes, and what to fix first, so when a shopper, or an agent, asks what to buy, your catalog is the easy answer.