Key takeaways
- Use Article, FAQPage, Course, and BreadcrumbList schema where relevant.
- JSON-LD in the <head> is the easiest, safest format.
- Schema must match the visible content, never mark up things that aren't on the page.
- Validate with Google's Rich Results Test before publishing.
Structured data for AI SEO means adding schema.org markup, usually JSON-LD, that describes your page to machines. The most useful types are Article, FAQPage, Course, and BreadcrumbList. Accurate schema helps AI search systems understand and correctly attribute your content.
Which schema types matter
- Article, for blog posts and guides.
- FAQPage, for question-and-answer sections. Google removed the FAQ rich result in 2026, so read does FAQ schema still help AI search before you rely on it.
- Course, for course and lesson pages.
- BreadcrumbList, to describe your site hierarchy.
- Organization / WebSite, site-wide identity and logo.
Example: FAQ schema
Here's a minimal FAQPage block you can adapt. Keep the answers identical to what's visible on the page.
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [{
"@type": "Question",
"name": "What is an AI SEO course?",
"acceptedAnswer": {
"@type": "Answer",
"text": "An AI SEO course teaches you to make content
visible in AI Overviews and AI Mode..."
}
}]
}Rules to follow
- Only mark up content that's actually visible on the page.
- Keep schema answers in sync with the on-page text.
- Validate at Google's Rich Results Test and Schema.org validator.
- Don't stuff unrelated types, relevance beats quantity.
Do it in order: structure your content first (see citation-worthy content), then layer schema on top. The course's Module 5 covers this in depth. And don't confuse schema with the llms.txt file, which is optional and not a ranking lever. Wondering which types are actually worth adding? See what structured data helps AI search cite your pages.