Hundreds of millions of buyers now ask AI systems for product recommendations before they ever open a search engine. Most stores have no idea whether they can be seen, understood, trusted, or recommended by any of them.
Human analytics and search rankings were built to answer human-era questions. Neither one tells you whether an AI shopping system would recommend your store to a buyer today.
One is the store a human sees. The other is the store AI can actually extract. They are rarely the same store.
This is the chain every AI shopping system runs a store through, whether it is ChatGPT, Perplexity, or an autonomous buying agent. A break at any link stops the process. A store can be perfectly crawled and read, and still never get recommended if it fails later in the chain.
It is a ladder. Most stores assume they are either invisible or visible to AI. In reality there are seven distinct stages between the two, and most stores are stuck somewhere in the middle without knowing it.
Visibility becomes useful once it becomes measurable. That's what the AI Commerce Score does: it walks a store through the same chain outlined above and scores where it holds up and where it breaks down.
Every layer depends on the one below it. A store can't be trusted if it isn't understood. It can't be recommended if it isn't trusted. And revenue only shows up once a store makes it all the way to the top.
Don't guess whether your store is visible. Measure it.
Illustrative example · single-site signal for atomfoundry.dev.
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