What Google actually shipped
Two things happened at once, which is why rankings have been jumping around like a heart monitor. First, a broad spam update went live, retuning how Google weighs low-value pages. Second, and this is the new part, Google added a dedicated model whose whole purpose is detecting content that was churned out by a machine at volume.
It isn't punishing AI because it's AI. It's punishing the pattern that comes with lazy AI: hundreds of near-identical pages, generic phrasing, copy that says a lot of words and answers nothing. The tell isn't the tool you used. It's that nobody with real knowledge would have written it that way.
Why this hits merchants harder than most
If your catalogue comes out of an ERP, MACE, Spruce, K8, you were already fighting thin pages full of stock codes. The tempting fix was to point an AI at every product and let it write a paragraph each. Do that across two thousand SKUs and you've just built exactly the fingerprint this update is trained to catch: bulk, templated, no lived knowledge behind it.
The cruel part is that it looks busy. Every page has copy now. But copy that a machine could have guessed from the product name adds nothing a buyer or a search engine can't get elsewhere, and at volume it now reads as a spam signal rather than a helpful one.
The test that decides which pages survive
There's a simple question that separates content that ranks from content that gets flagged: could only you have written this? If the paragraph could sit on any competitor's site with the logo swapped, it's commodity, and commodity is what the model is trained to discount.
The pages that hold up are the ones carrying something a machine can't invent: what this cable actually gets used for on site, which board warps if you leave it outside, what you'd fit instead when the usual part is on backorder, the fact that it's in stock in your yard today. Real stock, real use, real answers. That's not AI-proof by luck. It's the exact opposite of the pattern being penalised.
The other shift you should read alongside it
The same week, Google confirmed AI Overviews are surfacing more external links with clearer attribution, and its own studies show those answers are resolving more searches on the results page. So two things are true at once: bulk AI content is being pushed down, and AI answers are becoming the place buyers land.
That isn't a contradiction. It's the same message from both ends. The web is drowning in machine-written filler, so both classic search and AI answers are getting pickier about what they trust and cite. The pages that win aren't the ones with the most copy. They're the ones that plainly, specifically answer the thing that was asked.
What to do this week
Don't panic-delete every AI-touched page. Start by finding the bulk. Pull your product and category pages and look for the ones that could have been written about anyone's stock: generic, interchangeable, no real detail. Those are your risk.
Then fix the pages that earn it first, your best-selling lines and top categories. Rewrite the lead copy to say something only your business knows: the real use, the real spec, the real availability. Keep the stock code for your team, put the buyer's language up front. Leave the low-traffic long tail for later, or prune it. One page that genuinely answers beats fifty that a machine guessed.
If you'd rather see which of your pages are exposed before you spend a week rewriting, that's exactly what a revenue X-ray is for.
More on AI and GEO search: Generative engine optimization: the merchant's guide · How to get cited by ChatGPT · ChatGPT shopping research: how to be the store it names · Why ChatGPT recommends your competitor instead of you · How to get Shopify product pages into Google AI Overviews · Why your Shopify store doesn't show up in AI search.