TL;DR: I ran a small experiment to try and get some insight into whether large language models actually parse schema markup or are just nodding politely in its direction. I put a fake company address (inside beautifully invalid JSON-LD, on a page about ducks) into the head of an HTML document, mentioned no address anywhere in the visible text, and then asked various LLMs where the company was based. They happily told me, several of them citing the “structured data” they had so studiously consulted.

The experiment was then picked up by Search Engine Roundtable, at which point British sarcasm met the LinkedIn carousel, the two annihilated each other in a small puff of smoke, and a chunk of the GEO community came away convinced I had just proved that LLMs are lovingly parsing schema exactly as Schema.org intended.

An AI search engine response demonstrating that Large Language Models read structured schema data. The top section shows a user prompt asking for a company's address from a specific URL. The AI correctly extracts a fictional address ("77 The Muddy Bank, South Pondshire..."). The bottom section shows the source code of the "schema" it read: a humorous, duck-themed JSON-LD script containing custom keys like waddleStyle: "Aggressive", reedNumber: "77", and quackVolume: "Loud". A cartoon duck points down at the code with a shocked expression.
The guilty LinkedIn post that was patient zero of schema confusion. Image Credit: Mark Williams-Cook

I had arguably proved the opposite. The schema was deliberately broken. The LLMs returned the data anyway, because as far as they were concerned, the JSON-LD was simply more text on the page, lightly garnished with curly braces. That distinction is the whole point, because a growing cohort of “GEO experts” is pointing at “the LLM returned information that was only in the schema” as cast-iron proof that LLMs are using schema as designed. They are doing nothing of the sort. They are reading the HTML and shrugging at the structure.

I am not professing schema is worthless. I think you should still use it. But the way it is currently being sold to clients (as a magical injection of LLM citations) is propped up on a remarkably thin pile of evidence, and I want to walk through why.

A Quick Refresher On What Schema Is Actually For

Schema, or Schema.org structured data, is a collaborative vocabulary built by Google, Microsoft, Yahoo, and Yandex to let webmasters embed machine-readable information on their pages. The clue is in the name. It is a schema. A shared, agreed structure that lets a machine know that “Mark Williams-Cook” is a Person, that he works at an Organization called “Candour,” and that the string “01603 957068” sitting in his profile is a telephoneNumber and not, for instance, my weight in grams.

Google’s official documentation puts it about as plainly as Google ever puts anything:

“Structured data is a standardized format for providing information about a page and classifying the page content.” Google also says it uses structured data “to understand the content of the page, as well as to gather information about the web and the world in general, such as information about the people, books, or companies that are included in the markup.”

The whole point of schema is to remove ambiguity. Natural language is messy. “Apple” is a fruit, a company, a record label, and probably the surname of someone’s gerbil. If you tell a search engine in plain English that you sell Apple, it has to guess. If…


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Last Update: June 16, 2026