A webpage has two readers: the human who reads the text, and the machine that has to understand what that text is. For the human, the difference between an article, a product page and a frequently asked question is clear at a glance. For the machine, it's all just text, unless you tell it otherwise. That telling is what schema markup does.

01 / the principleWhat structured data is

Schema markup, also known as structured data, is a piece of invisible code in your page that tells machines what's there: this is an article, this is the author, this is the publication date, this block is a question with an answer. The agreements on this are set out at schema.org and are read by all major platforms.

The common types can be summed up briefly. Article for articles and blog posts, with author and date. FAQPage for blocks with questions and answers. HowTo for step-by-step guides. Product for products with price and reviews. Organization for who you are as a business. For the visitor, nothing about the page changes; the code is only for machines.

02 / the effectWhat AI systems do with it

Not demonstrable for AI citations: Ahrefs measured in May 2026 that pages adding JSON-LD saw no measurable gain in AI citations. The often-cited figure of 30 to 40 percent comes from the GEO research by Princeton and concerns content (sources, citations and statistics), not schema. What schema does do is make data machine-readable: who the author is, when the piece was written and which block contains the answer to which question is then stated explicitly. That an AI system cites a page more often as a result has not been demonstrated.

Schema only reinforces what is already there. A page with no content doesn't become a source through markup; a good page becomes more readable through it. The order is therefore fixed: first content that genuinely answers a question, then the markup on top. How to do the first part is covered in how to write content that AI can cite.

Schema markup makes data machine-readable. That AI cites a page more often as a result has not been demonstrated.

03 / the nuanceWhat Google does and doesn't require

Google is clear about it: no special markup is required for AI Overviews. Google's AI features rest on the usual search and quality systems, and content written for people wins there. Anyone who adds schema purely to reach AI Overviews is doing it for the wrong reason.

At the same time, Google does recommend structured data for your visibility in a broader sense, including for rich results with stars, questions and breadcrumbs. Whether platforms outside Google use the markup when selecting sources has not been demonstrated. The conclusion is therefore fairly sober: schema is nowhere required, makes your data machine-readable, and does no harm anywhere. It belongs in the same category as llms.txt: machine-readability as a layer on top of good content, not a replacement for it.

04 / in practiceWhere to start

Start small and where it pays off. For most service providers that order is as follows:

The direct recommendation for a service provider with a knowledge blog: do steps 1 and 2 now, add FAQPage as soon as you have pages with question-and-answer blocks, and skip step 4 until your site genuinely calls for it.

Many systems handle part of this automatically: WordPress with an SEO plugin, as well as modern site builders, write Article markup automatically. So check what's already there before having anything built. That checking is free with Google's Rich Results Test or the validator at schema.org: enter the link, and you see which types the page carries and whether there are any errors.

One warning: only mark up what is actually on the page. FAQPage markup on a page without visible questions, or review stars without reviews, fails on inspection and can harm your visibility rather than help it.

05 / the limitWhen schema isn't a priority

If your site has five pages and barely any knowledge articles, the gain from markup is small: there's little to mark up, and machines don't get lost across five pages. Focus first on whether your pages answer your clients' questions.

Anyone without any measurement in place is also better off leaving schema for now. Without a baseline measurement you won't know afterwards whether the markup did anything. Measure where you stand first, then make the change, and measure again; that way the effect is an observation instead of a feeling.

This text was produced with AI assistance and checked and approved by a human before publication.