Published August 10, 2026.
AI search engines and AI agents use two main signals to understand a website: structured data and entities.
Structured data states facts directly. Entities are the real-world subjects those facts describe, such as brands, products, people, places, and concepts.
Clear structured data and clear entity identity make content easier to cite, easier to act on, and less likely to be skipped.
Structured data is usually written in JSON-LD and uses the schema.org vocabulary.
It can state facts such as:
In June 2026, Google and Schema.org published the first usage dataset of its kind. It showed nearly 5,500 types and properties in total.
Among the most widely deployed types, with ten million domains or more, were:
| Type | Use |
|---|---|
| Organization | Identity markup |
| Person | Identity markup |
| BreadcrumbList | Site structure |
| WebPage | Page structure |
An entity is the stable thing a system can recognize across contexts.
Text alone can suggest an entity. It cannot confirm one.
That is why entity clarity matters: without it, a system may hedge, skip, or misidentify the subject.
A 2026 audit of 5,000 production sites found that 71 percent had deployed at least one schema type, but only 22 percent passed a clean validation check across everything they emitted.
The article recommends testing with Google's Rich Results Test or the Schema Markup Validator.
For AI search, better structured data and clearer entities can improve citation accuracy.
For AI agents, they can improve reliability by reducing abandoned tasks, fallback questions, and wrong assumptions.
The article says these improvements should be measured over time, not assumed.
Verseodin tracks brand citations across ChatGPT, Gemini, Claude, and Perplexity on a recurring schedule.
It compares citation results before and after structured data and entity cleanup.
Structured data is machine-readable code, usually JSON-LD in schema.org. An entity is the subject described by that code.
They look for consistent naming in text, confirmation in schema such as Organization or Person, and external references like sameAs links to Wikidata or Wikipedia.
Yes. A system can infer an entity from text and context. That inference is less confident than structured confirmation.
Validate the structured data, then track whether AI engines cite the brand correctly for real prompts.
Satvik Mishra is the Co Founder of Verseodin. He writes about generative engine optimization strategy and AI visibility.