Schema Markup for AI Search

The schema markup that helps AI search is the markup that describes your entity and connects it together. A connected @graph linking Organisation, WebSite, WebPage, and Article by @id gives AI platforms a verifiable picture of who you are and what a page is about. Article schema with a named author, sameAs links to authoritative profiles (LinkedIn, Wikidata), and BreadcrumbList for structure are the dependable building blocks. FAQPage is no longer a useful target: Google deprecated FAQ rich results in 2023 and we do not recommend it.

The vocabulary used throughout this guide is defined by Schema.org, the shared standard maintained by Google, Microsoft, Yahoo, and Yandex. Google recommends implementing structured data in JSON-LD format and documents every supported type in its structured data gallery. Structured data does not guarantee a citation, but it gives AI systems a reliable, machine-readable account of your entity and content that is far less ambiguous than prose alone.

What schema does (and does not) do for AI search

Schema markup does not buy citations and there is no published, reproducible figure that says "type X gives Y percent more citations". What schema does is reduce ambiguity. The Generative Engine Optimization paper (arXiv 2311.09735) found that content which is clearly attributed, cites sources, and states facts plainly is more likely to be surfaced by generative engines. Schema is the structured layer of that same principle: it tells the engine, unambiguously, what your organisation is, who wrote a page, when it was updated, and how your pages relate to each other. Treat schema as entity hygiene, not a growth hack.

Schema types ranked by how much they help AI understanding

Schema type	What it does for AI	Priority
Connected @graph (Organization + WebSite + WebPage)	Links your entity, site, and page by @id so the engine sees one verified network rather than disconnected blocks	Critical
Organization + sameAs	Establishes the entity and connects it to authoritative profiles (LinkedIn, Wikidata) for cross-referencing	Critical
Article + Person author	Attributes content to a named author and a publisher, with datePublished/dateModified for freshness	High
Speakable	Flags the most quotable passages; low adoption, low cost, narrow but real support	Optional edge
BreadcrumbList	Describes where a page sits in your site, helping topical structure	Medium
Product + Offer	Gives commerce details (price, availability, brand) in machine-readable form for product queries	High (ecommerce)
FAQPage	Deprecated. Google removed FAQ rich results in 2023; do not add it	Avoid

1. The @graph pattern - connect your entities

The @graph pattern connects multiple schema entities into a single, interlinked structure. Instead of separate disconnected blocks, @graph tells AI platforms your Organisation, WebSite, WebPage, and Article are part of the same verified network, linked by @id. This connected signal is more useful than the same blocks scattered and unlinked, because the engine can resolve every reference to a single entity rather than guessing.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "Organization",
      "@id": "https://example.com/#organization",
      "name": "Your Company",
      "url": "https://example.com",
      "sameAs": [
        "https://www.linkedin.com/company/yourco",
        "https://www.wikidata.org/wiki/Q123456"
      ]
    },
    {
      "@type": "WebSite",
      "@id": "https://example.com/#website",
      "url": "https://example.com",
      "name": "Your Company",
      "publisher": { "@id": "https://example.com/#organization" }
    },
    {
      "@type": "WebPage",
      "@id": "https://example.com/guide/#webpage",
      "url": "https://example.com/guide/",
      "isPartOf": { "@id": "https://example.com/#website" }
    },
    {
      "@type": "Person",
      "@id": "https://example.com/#author",
      "name": "Author Name",
      "jobTitle": "Expert Title",
      "worksFor": { "@id": "https://example.com/#organization" }
    },
    {
      "@type": "Article",
      "headline": "Article Title",
      "isPartOf": { "@id": "https://example.com/guide/#webpage" },
      "author": { "@id": "https://example.com/#author" },
      "publisher": { "@id": "https://example.com/#organization" },
      "speakable": {
        "@type": "SpeakableSpecification",
        "cssSelector": [".answer-capsule"]
      }
    }
  ]
}
</script>

Reference: schema.org/WebSite, schema.org/WebPage.

How @graph strengthens AI understanding

Connects author to organisation, establishing where the content comes from
Links article to a verified publisher and the page it lives on
Uses @id references, so the engine resolves each entity once instead of seeing duplicates
Gemini draws on Google's Knowledge Graph, so a clean, internally consistent entity graph helps it reconcile your structured data with what it already knows

2. Organisation schema and sameAs - entity authority

Organisation schema with @id and sameAs links is the foundation of your entity. AI platforms use it to confirm your brand exists and to connect it to other places it appears. sameAs links to LinkedIn, Wikidata, and your verified profiles let an engine cross-reference your claims against independent sources, which is far stronger than an unlinked, self-asserted name.

Reference: schema.org/Organization, schema.org/sameAs.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://example.com/#organization",
  "name": "Your Company Name",
  "url": "https://example.com",
  "logo": "https://example.com/logo.png",
  "description": "Your consistent brand description used everywhere.",
  "foundingDate": "2020",
  "areaServed": {
    "@type": "Country",
    "name": "United Kingdom"
  },
  "sameAs": [
    "https://www.linkedin.com/company/your-company",
    "https://www.wikidata.org/wiki/Q123456",
    "https://www.youtube.com/@yourcompany",
    "https://g.co/kgs/yourGBPid"
  ],
  "contactPoint": {
    "@type": "ContactPoint",
    "contactType": "customer service",
    "email": "[email protected]"
  }
}
</script>

Organisation schema best practices

Use @id to create a persistent identifier other schema can reference
Include sameAs links to authoritative profiles. A Wikidata item is especially valuable because it is itself a node in the open entity graph that engines draw on
Use areaServed, which matters for local and regional businesses
Match the description to what appears on your GBP, LinkedIn, and other profiles, so cross-references reinforce rather than contradict each other
Include foundingDate to add an entity permanence signal

3. Article and a named author

Article schema attributes a page to a named author and a publisher, with datePublished and dateModified. A clearly attributed, dated, well-sourced page is the kind of content the GEO research found generative engines prefer to surface. Connecting the Article to a real Person and Organisation, rather than leaving authorship implicit, makes that attribution explicit and verifiable.

Reference: schema.org/Article, schema.org/Person, Google Article documentation.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Your Article Title",
  "description": "A clear description of the article content.",
  "datePublished": "2026-04-01",
  "dateModified": "2026-04-06",
  "author": {
    "@type": "Person",
    "@id": "https://example.com/#author-jane",
    "name": "Jane Smith",
    "jobTitle": "AI Search Analyst",
    "url": "https://example.com/about/jane-smith/",
    "sameAs": [
      "https://www.linkedin.com/in/janesmith"
    ]
  },
  "publisher": {
    "@id": "https://example.com/#organization"
  },
  "mainEntityOfPage": "https://example.com/article-url/"
}
</script>

Author and Person best practices

Create an author bio page on your site and link to it via url
Connect the Person to LinkedIn and other professional profiles via sameAs
Include jobTitle to establish expertise relevance
Use @id so other pages can reference the same author entity
Include dateModified and keep it honest. Google's Article guidance asks that the date reflect a genuine update, not a cosmetic change

4. Speakable schema - a narrow, low-cost edge

Speakable schema marks content suitable for text-to-speech and voice assistants using CSS selectors or XPaths to flag the passages a platform should read aloud. Google documents Speakable as a limited feature aimed at news content, so support is partial rather than universal. It is low cost to add and few sites bother with it, which makes it a small, optional edge rather than a core requirement.

Reference: schema.org/speakable, Google Speakable documentation.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Your Article Title",
  "speakable": {
    "@type": "SpeakableSpecification",
    "cssSelector": [".answer-capsule", "h1"]
  },
  "publisher": {
    "@id": "https://example.com/#organization"
  }
}
</script>

Speakable implementation tips

Use cssSelector to target your answer capsule paragraphs
Include the page title (h1) as speakable
Keep speakable content concise, around two or three sentences per section
Validate with Google's Rich Results Test

5. BreadcrumbList - site structure signal

Reference: schema.org/BreadcrumbList, Google breadcrumb documentation.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    { "@type": "ListItem", "position": 1, "name": "Home", "item": "https://example.com/" },
    { "@type": "ListItem", "position": 2, "name": "Guides", "item": "https://example.com/guides/" },
    { "@type": "ListItem", "position": 3, "name": "Schema Markup", "item": "https://example.com/schema-markup-ai-search/" }
  ]
}
</script>

BreadcrumbList helps crawlers understand your site hierarchy and the topical relationships between pages. It tells a platform where a page sits within your structure, which supports topical authority assessment.

BreadcrumbList best practices

Include BreadcrumbList on every page, not just deep pages
Use descriptive names that include relevant keywords, not just "Page 1"
Match the breadcrumb trail to your actual URL structure
Keep trails logical: Home > Category > Subcategory > Page

6. Product and Offer - commerce details for AI

Product schema with an Offer gives AI platforms the concrete commerce details (price, currency, availability, brand) that product and shopping queries depend on. It is the structured form of the facts a buyer needs, and it lets an engine state them accurately rather than scraping them from prose. Only include AggregateRating when you have genuine, verifiable review data behind it.

Reference: schema.org/Product, schema.org/Offer, Google Product documentation.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Product Name",
  "description": "Clear product description with key features.",
  "brand": {
    "@type": "Brand",
    "name": "Your Brand"
  },
  "offers": {
    "@type": "Offer",
    "price": "99.00",
    "priceCurrency": "GBP",
    "availability": "https://schema.org/InStock"
  }
}
</script>

Product schema with accurate Offer data feeds product and comparison answers. If you publish AggregateRating, it must reflect real reviews that are visible on the page; fabricated or unverifiable ratings breach Google's structured data policies and undermine trust.

7. FAQPage - deprecated, do not use

FAQPage schema is no longer a useful target. Google deprecated FAQ rich results in August 2023 and now shows them only for a small set of authoritative government and health sites. For everyone else FAQPage no longer produces a rich result, and we do not recommend adding it. You can still write helpful questions and answers as normal page content; you simply do not mark them up as FAQPage.

If you previously added FAQPage markup expecting rich results, you can safely remove it. The useful version of "answer the question" is plain, well-structured prose with a clear question as a heading and a concise answer beneath it, which any engine can read without the deprecated markup.

Common schema mistakes that hurt AI understanding

The most common schema mistakes are having no Organisation schema at all, using schema without @id references so blocks float disconnected, having sameAs links that point to dead profiles, and implementing schema that contradicts the visible page content. AI platforms can detect inconsistencies between structured data and on-page content, and an inconsistency is worse than no markup.

Mistake 1: No Organisation schema at all

Without Organisation schema, AI platforms have to infer your business name, type, and location from unstructured text. Adding Organisation schema is a short task that immediately gives engines a clear, machine-readable entity to anchor to. This is the most common gap we find in audits.

Mistake 2: Schema without @id references

If your Organisation schema has no @id, other blocks cannot reference it, so your Article and Person schema float as disconnected entities. Use @id on every block and reference it with { "@id": "..." } instead of duplicating data.

Mistake 3: Dead sameAs links

If your sameAs array includes links to deleted profiles or old domains, engines find broken references and have less reason to trust the entity. Audit your sameAs links periodically and remove any that no longer resolve.

Mistake 4: Schema that contradicts page content

If your Organisation schema says "London" but your page says "Manchester", a platform detects the conflict and trusts neither. Schema must match visible content. Your business description in schema should match the description on your homepage, GBP, and LinkedIn.

Mistake 5: Missing dateModified on articles

Platforms use dateModified to judge freshness. If your Article schema has no dateModified, there is nothing to read. Include both datePublished and dateModified, and update dateModified only when you genuinely revise the content, in line with Google's Article guidance.

Mistake 6: Adding deprecated FAQPage markup

FAQPage no longer produces rich results for most sites since Google's August 2023 change. Adding it now spends effort for no return and can clutter your output. Write the questions and answers as normal content instead.

Testing and validating your schema

Use Google's Rich Results Test and the Schema.org validator to check your schema. Test every page type, not just your homepage. Confirm @id references resolve, sameAs links work, and the schema matches visible content. Re-test after meaningful site updates.

Testing tools

Google Rich Results Test validates JSON-LD and shows which rich results your schema supports
Schema.org Validator checks syntax and structure against the Schema.org specification
Google Search Console reports schema errors and warnings across your site

What to check

Every @id reference resolves to a real schema block
Every sameAs URL returns a live page
Organisation name matches your GBP, LinkedIn, and other profiles
dateModified is accurate and recent
Author Person schema links to a real bio page on your site
No duplicate schema blocks on the same page
No leftover FAQPage markup

Implementation checklist

Step	Schema type	Page type
1. Add Organisation schema	Organization	Every page (via site-wide template)
2. Add WebSite and WebPage	WebSite, WebPage	Site-wide and per page
3. Add Person schema for authors	Person	Author bio pages and articles
4. Add Article schema	Article	Blog posts, guides, insights
5. Connect everything with @graph	@graph	All pages
6. Add BreadcrumbList	BreadcrumbList	Every page
7. Add Speakable (optional)	SpeakableSpecification	Content pages
8. Add Product and Offer	Product, Offer	Product pages
9. Do not add FAQPage	(deprecated)	n/a
10. Validate	-	Google Rich Results Test

How each AI platform uses schema

Platforms weight signals differently. The notes below are directional, based on each platform's documented data sources, not measured citation rates.

Platform	Signals it leans on	Why
ChatGPT	Organisation, entity consistency	Web results come largely via Bing, so a clear, consistent entity helps it build a reliable profile
Gemini	Organisation, Person, sameAs	Draws on Google's Knowledge Graph, so it benefits from structured data it can reconcile with what it already holds
Perplexity	Article, dateModified	Emphasises live sources and freshness, so accurate dates and clear attribution matter
AI Overviews	Article, BreadcrumbList, Speakable	Sits inside Google Search and reads supported structured data directly
Claude	Organisation, Article	Clear entity and authorship help it understand and attribute a source when it retrieves the page

Frequently asked questions

Does schema directly improve AI citations?

Not on its own, and there is no reliable published figure that puts a percentage on it. What schema does is remove ambiguity: it states your entity, authorship, dates, and page relationships in a form an engine can read without guessing. That supports the broader pattern the GEO research describes, where clearly attributed, well-sourced content is more likely to be surfaced.

Which schema type should I add first?

Organisation schema, connected to your WebSite and pages via a @graph. It is the foundation that every other type references. Add it site-wide through your template, then layer Article and Person schema onto your content pages.

Should I still add FAQPage schema?

No. Google deprecated FAQ rich results in August 2023, and they now appear only for a narrow set of authoritative government and health sites. For everyone else FAQPage produces no rich result, so adding it is wasted effort. Write your questions and answers as ordinary page content instead.

Can I use a WordPress plugin for schema?

Yes, but check the output. Plugins such as Yoast, RankMath, and Schema Pro generate valid schema but often omit fields that matter for entity understanding, such as sameAs, areaServed, and @id references. Supplement plugin output with the fields that connect your entities.

Does schema work the same for ecommerce and service businesses?

The core entity types (Organisation, WebSite, Article, Person) apply to both. Ecommerce sites should add Product and Offer schema. Service businesses should add LocalBusiness or ProfessionalService and Person schema. Read our guide on AI search for ecommerce for sector-specific advice.