Schema.org
Schema.org is a shared vocabulary for structured data with which you mark up content on your website unambiguously for machines. Instead of a search engine or AI having to guess whether a number is a price, a date or a rating, you tell it directly. The vocabulary was founded in 2011 by Google, Bing, Yahoo and Yandex and is the industry standard today.
Why Schema.org matters for AI visibility
AI assistants like ChatGPT, Perplexity or Google AI Overviews have to pull reliable facts from your page in a flash. Free-flowing text leaves a lot of room for interpretation: what is the company's name, what are the opening hours, what is the price? Schema.org provides these details in a clearly labeled form, so that the machine adopts them without guesswork. This increases the chance that your content is understood correctly, cited and recommended in an answer. Structured data is thus a foundation for citability: the more cleanly a statement is stored in machine-readable form, the lower the risk that a model spreads false or outdated information about you. Schema.org doesn't replace good content, but it makes it unambiguously graspable.
How Schema.org works technically
Schema.org is at first only the vocabulary, that is, the list of permitted types and properties. A type is, for example, LocalBusiness, Product or FAQPage; a corresponding property is something like name, address or priceCurrency. For a machine to read these details, you need a format. The writing style recommended today is JSON-LD, a small data block in the source code of your page that stores the facts cleanly separated from the visible text. Older formats are microdata and RDFa, which sit directly in the HTML. Important: the marked-up details must exactly match what visitors see on the page. If you invent ratings or prices in the data block that don't exist visibly, this counts as spam and can be penalized.
Common mistakes
The most expensive mistake is the discrepancy between markup and visible content: five-star ratings in the data block but none on the page. Just as widespread are outdated details, such as old opening hours or a long-since-changed company name, that were updated only in the running text but not in the schema. Many also use the wrong type, such as Product for a service. Required fields are also easily forgotten, causing search engines to ignore the markup. So check your markup regularly with Google's Rich Results Test or the Schema Markup Validator. Less but correctly maintained markup is always better than lots of faulty markup. Keep in mind: Schema.org describes your content, it's not meant to embellish it.
Example
Imagine a small dental practice. In the visible text are the name, address, telephone number and opening hours. For humans this is clear. But a machine sees only words and numbers. If the practice now adds a JSON-LD block with the type LocalBusiness, in which name, address, telephone and openingHours are cleanly labeled, an AI can adopt these facts directly. If someone asks their assistant "Which dentist nearby is open this afternoon?", the chances are considerably better that this very practice is named correctly and with the right hours.
Common questions
Do I need Schema.org if I'm already doing good SEO?
Yes. Good content ensures that you're found; Schema.org ensures that machines understand your facts unambiguously. Especially for AI answers and rich snippets, machine-readable markup is an additional, clearly measurable advantage.
In which format should I implement Schema.org?
Use JSON-LD. It is the format recommended by Google, sits as a separate block in the source code and is easy to maintain, without you having to rebuild your visible HTML. Microdata and RDFa work too but are considered more cumbersome.