Short answer: Structured data for AI search helps indirectly. It gives search engines explicit, machine-readable facts about who you are, what a page is and who wrote it, and those engines are the indexes AI answers are built from. But Google says structured data is not required for its generative AI features and there is no special "AI schema". The markup worth your time in 2026 is Organization, Article or BlogPosting with real authors, BreadcrumbList, LocalBusiness, Product and VideoObject, all matching the visible page. FAQPage no longer produces rich results in Google (ended 7 May 2026).
What role does structured data play in AI search?
Google's structured data introduction says markup gives Google explicit clues about what a page means and can make the page eligible for rich results. For AI search, Google is unusually direct. Its generative AI optimisation guide lists "overfocusing on structured data" among things you can ignore: "Structured data isn't required for generative AI search" and "there's no special schema.org markup you need to add". The same guide says it is still "a good idea to continue using it as part of your overall SEO strategy".
So the honest answer to "what structured data helps AI search engines cite my pages?" is: none directly causes a citation, but the right markup removes ambiguity at the indexing stage. That matters because:
- Google AI Overviews and AI Mode cite pages from the normal Google index, and Google's AI features page lists "making sure your structured data matches the visible text on the page" as a best practice.
- Organization and author markup help Google "disambiguate your organization in search results", in the words of its Organization documentation. An agency called "Spark Digital" in Noida and one in Pune are different entities; markup with your address, logo and profiles says which one you are.
- Product, LocalBusiness and Merchant Center data feed shopping and local results, which AI answers draw on for "near me" and "price" questions.
The same logic applies to structured data for answer engines outside Google, such as ChatGPT search and Perplexity. Neither publishes guidance saying schema earns citations, so treat markup as a way to make facts unambiguous, never as a substitute for a clear answer in the visible text.
Which schema markup types should you use for AI search?
Start from the page type, not from a list of every schema.org class. This table uses Google's search gallery as checked in October 2026, which lists 25 supported features.
| Page | Schema type | Google feature status (Oct 2026) | Why it helps AI search | Priority |
|---|---|---|---|---|
| Home or About page | Organization (or a specific subtype) | Supported; logo and knowledge panel details | Identity: legal name, logo, address, profiles via sameAs | High |
| Blog post, guide | BlogPosting or Article | Supported | Author, publish and modified dates made explicit | High |
| Every inner page | BreadcrumbList | Supported (desktop display) | Shows where a page sits in your site hierarchy | Medium |
| Clinic, showroom, branch page | LocalBusiness subtype (Dentist, RealEstateAgent, etc.) | Supported | Hours, address, phone for local answers | High for local firms |
| Product page (D2C) | Product with Offer | Supported (merchant listings, snippets) | Price, availability, returns stated precisely | High for ecommerce |
| Video page | VideoObject | Supported | Makes video content findable as text facts | Medium |
| Author bio page | ProfilePage with Person | Supported | Gives the author entity a stable home URL | Medium |
| Forum or community Q&A | DiscussionForumPosting or QAPage | Supported | Only for genuine user-generated discussions | Situational |
| FAQ section | FAQPage | No rich result since 7 May 2026 | Harmless if accurate; no Google display benefit | Low |
Google's case studies show why the supported types are worth doing even outside AI: Rotten Tomatoes measured a 25% higher click-through rate on pages with structured data, and Nestlé saw an 82% higher click-through rate on pages that showed as rich results. Those are classic search results, not AI citations, and they come from Google's own documentation, so read them as best cases.
Which structured data features has Google retired?
Several "AI schema" checklists still recommend markup Google no longer uses for display. From the Search Central changelog:
| Date | Change | What to do |
|---|---|---|
| 12 Jun 2025 | Retirement notices added for several features, including ClaimReview | Stop adding fact-check markup for Google display |
| 9 Sep 2025 | Docs removed for course info, estimated salary, learning video, special announcement and vehicle listing markup | Leave existing markup or remove it; no new work |
| 5 Nov 2025 | Practice problem and dataset markup phased out of Search; Dataset markup used only by Dataset Search | Use Dataset only if you publish real datasets |
| 8 May 2026 | FAQ rich result deprecated: "no longer appear in Google Search starting May 7, 2026" | Do not promise FAQ snippets; keep FAQs for readers |
| 15 Jun 2026 | FAQ rich result documentation removed | Update internal SEO checklists |
HowTo is also absent from the current gallery. If a vendor's "AI schema package" is mostly FAQPage and HowTo, it is selling markup with no current Google display feature. Our FAQ schema generator page explains where FAQ markup still has a use.
What entity markup actually matters?
For most Indian service businesses, two blocks of markup do the heavy lifting.
Organization on the home or About page
Google says there are no required properties for Organization and recommends adding as many relevant ones as apply, on the home page or a single page that describes the organisation. It does not need to be on every page. The properties worth filling for an Indian business:
| Property | Example value (illustrative) | Rule |
|---|---|---|
name, legalName | Brand name; name as registered with MCA | Same spelling as Business Profile and invoices |
url, logo | Home page; square logo URL | Logo crawlable, not blocked by robots.txt |
address, telephone, email | Registered office, Sector 63, Noida, IN | Must match the footer and Business Profile |
sameAs | LinkedIn, Google Business Profile, Justdial, IndiaMART, YouTube | Only profiles you control and keep current |
taxID | Your GSTIN | Google asks that taxID match the country in address |
foundingDate, numberOfEmployees | Year; headcount range | Only if true and stated on the About page |
Article or BlogPosting with a real author
Google's Article documentation also has no required properties, but recommends author, author.url, headline, image, datePublished and dateModified. Use Person for people, list every visible author separately, and point author.url to a profile page that shows real experience. An "Admin" author with no profile tells a machine nothing; a named practitioner with a ProfilePage and LinkedIn in sameAs is a verifiable entity.
How should you implement schema markup for AI search?
- Use JSON-LD. Google supports JSON-LD, Microdata and RDFa, and recommends JSON-LD where the site setup allows it.
- Pick the most specific type. Google's general guidelines ask for "the most specific applicable type". A dental clinic is
Dentist, not justLocalBusiness. - Mark up only what users can see. The guidelines say: "Don't mark up content that is not visible to readers of the page." Hidden prices, invisible FAQs and ratings that appear nowhere on the page are violations.
- Keep it a true representation. Markup must be "a true representation of the page content". A blog post marked as a Product or a city page claiming an office that does not exist risks a manual action, which removes rich result eligibility.
- Render it server-side or verify rendering. If a tag manager injects JSON-LD, check that the rendered HTML in URL Inspection contains it.
- Tie
dateModifiedto real edits. Builds that stamp every page with today's date make the signal meaningless. - Give the markup an owner. Someone must update hours, prices and addresses in the markup when they change on the page.
Common structured data mistakes, and how to fix them
| Mistake | Risk | Fix |
|---|---|---|
| LocalBusiness markup on 40 "city pages" with no office in those cities | Misleading markup; scaled thin pages | Mark up real locations only; use areaServed on the service page |
| AggregateRating copied from Google or Practo reviews | Misleading markup; review snippet ineligibility | Only mark up reviews collected and shown on your own page |
| FAQPage schema with answers hidden in collapsed code | Hidden content | Make every marked answer visible, or remove the markup |
| Different business names across schema, footer and Business Profile | Entity confusion | One canonical name and address everywhere |
| Plugin and theme both outputting Organization | Conflicting duplicates | Disable one; keep a single @id |
| Product price in markup differs from on-page price after a sale | Merchant listing errors, mistrust | Generate markup from the same field the page displays |
How do you test and maintain structured data?
- Validate JSON syntax at build time.
- Run the Rich Results Test on one URL per template, not just the home page.
- Use URL Inspection to confirm the rendered HTML contains the markup and the canonical is correct.
- Compare every marked value with the visible page.
- Watch the rich result status reports in Search Console after deployment.
- Re-test whenever a template, CMS field or plugin changes.
Our free SEO and schema tools help with the basics. Structured data is one layer of the wider stack covered in Google AI Overviews SEO and the AI search technical audit; and if someone tells you an llms.txt file replaces schema, read what llms.txt actually does. For implementation across a large site, see our SEO services.
Sources
- Google: Optimizing your website for generative AI features: structured data not required; no special schema; keep using it for SEO.
- Google: AI features and your website: structured data matching visible text listed as a best practice.
- Google: Introduction to structured data: purpose, JSON-LD recommendation, Rotten Tomatoes and Nestlé case studies.
- Google: General structured data guidelines: visibility, true representation, specificity, manual actions.
- Google: Search gallery: the 25 currently supported features.
- Google: Organization structured data and Article structured data: recommended properties, taxID rule, author best practices.
- Google Search Central: Latest documentation updates: retirements from 2025 to 2026, including FAQ rich results ending 7 May 2026.