When an AI model encounters your website during training or at retrieval time, it faces an interpretation challenge: what exactly is this organisation, what do they do, and can this content be trusted? Structured data answers these questions directly, in machine-readable language that leaves no room for ambiguity. This article explains which schema types matter most for AI visibility — and how to implement them correctly.

Why structured data matters more for LLMs than for traditional SEO

In traditional SEO, structured data's primary value is earning rich results in Google's SERP — star ratings, FAQ dropdowns, recipe cards. For LLMs, the value is different and arguably more fundamental: structured data provides unambiguous entity signals that help AI systems build accurate representations of who you are.

LLMs process vast quantities of unstructured text during training. For most concepts and entities, the model derives understanding from statistical co-occurrence patterns — how words appear together across millions of documents. This inference process is powerful but imperfect. Structured data cuts through this ambiguity by presenting facts about your organisation in a format designed explicitly for machine parsing.

Think of JSON-LD as a direct briefing to the AI: "Here is exactly who this organisation is, what it does, and what you should know about it." That directness is its power.

"Think of JSON-LD structured data as a direct line of communication with AI systems — you're telling them exactly who you are, what you do, and why you're credible."

Organization schema: the most important markup for brand visibility

The Organization schema type is the single most important structured data implementation for GEO. It should appear on your homepage and About page, and it should be as complete as possible. A well-implemented Organization schema includes:

  • @type: Organization (or the more specific subtype: SoftwareApplication, LocalBusiness, etc.)
  • name: Your exact legal or trading brand name
  • url: Your canonical homepage URL
  • description: A clear, factual 1-2 sentence description of what you do
  • foundingDate: Year of founding
  • numberOfEmployees: Approximate employee count range
  • sameAs: An array of URLs to your brand's presence on authoritative external sites (Wikipedia, LinkedIn, Crunchbase, Wikidata, social profiles)
  • logo: URL to your official logo image
  • contactPoint: Primary contact information

The sameAs property is particularly important for AI visibility. By linking your Organization entity to its representations on Wikipedia, Wikidata, and other knowledge bases, you're explicitly connecting your site to the entity graph that AI systems use to understand brand relationships.

Article and BlogPosting schema: signalling expertise at scale

Every article or blog post on your site should carry Article or BlogPosting schema. This serves two GEO purposes: it signals that your content is authored (rather than AI-generated or scraped), and it provides authorship and publication metadata that AI retrieval systems use to assess content credibility.

Key properties to include: headline, description, datePublished, dateModified (keep this current — recency matters for retrieval systems), author (with Person schema including the author's name and profile URL), publisher (with Organization schema), and image. The dateModified field is often overlooked but is important for retrieval systems that weight content freshness.

FAQPage schema: matching how people ask AI questions

FAQPage schema is one of the highest-leverage structured data types for GEO because it directly mirrors the question-and-answer format that AI assistants use. When your content is marked up as FAQPage with clear question and answer pairs, it becomes trivially easy for AI systems to extract and reproduce your content as part of a conversational response.

Design your FAQ content around the specific questions your audience asks AI assistants. These tend to be more conversational and specific than traditional search queries: "What's the difference between X and Y?" rather than "X vs Y." Structure each FAQ answer as a complete, standalone response that provides value even if read without the surrounding page context — because that's exactly how an AI retrieval system may use it.

HowTo schema: capturing procedural queries

Procedural queries — "how do I X?" — represent a significant share of AI assistant usage. HowTo schema marks up step-by-step instructional content in a structured format that AI retrieval systems can parse and reproduce reliably. For categories where procedural knowledge matters (software, services, professional expertise), HowTo markup on your best how-to content can meaningfully improve citation rates for how-to queries.

Person schema: building author authority

Person schema on author profile pages and in article markup establishes that your content is authored by real, verifiable humans with relevant expertise. This matters increasingly as AI models are trained to distinguish human-authored from AI-generated content, and as retrieval systems weight content from verified authors more highly.

For each named author on your site, create an author profile page with Person schema that includes: name, job title, employer (linked to your Organization), relevant credentials, and links to their verified profiles on LinkedIn, Google Scholar (if relevant), or other authoritative directories. Connect this Person schema to the Article schema on every piece they've written via the author property.

Validating and testing your structured data

After implementing structured data, validate it using Google's Rich Results Test and the Schema.org validator. Validation errors — missing required properties, incorrect value types — can cause AI systems to ignore your markup entirely. Common errors include: missing @context declaration, using relative rather than absolute URLs, and providing array values where single values are expected.

Once validated, monitor whether your structured data is having the expected effect on AI visibility by running regular visibility audits. For a complete audit framework, see our GEO audit guide. For implementation advice connected to your About page specifically, see optimising your About page for LLM citation and the broader 7 factors of AI visibility.