Schema markup in 2026: what AI search engines actually look for

Schema markup has been a standard SEO recommendation for years, but its role in AI search is different — and more important. While traditional search engines use schema to generate rich results, AI models use it to understand entity relationships and verify factual claims. Getting schema right is now a prerequisite for AI citation.

Organisation schema is the starting point. It establishes who you are — your name, description, URL, logo, contact information and social profiles — in a format AI systems can parse unambiguously. Many sites have no Organisation schema at all, or have it partially implemented. A complete, accurate Organisation schema is the single highest-impact schema addition for most brands.

Service schema communicates what you do. For each core service, a Service schema object linked to your Organisation tells AI models the name, description, area served and provider. This is what enables AI systems to confidently say 'Company X offers service Y' — without it, they have to infer this from body copy, which introduces error and uncertainty.

FAQ schema remains valuable, particularly for conversational queries. When a user asks a question that maps to one of your FAQs, a well-structured FAQ schema significantly increases your likelihood of citation. The key is ensuring your FAQ content is substantive — shallow one-line answers are less likely to be cited than thorough, accurate responses.

Beyond these core types, consider Review schema (if you have genuine reviews), Event schema (for any events), and BreadcrumbList schema for navigational clarity. The goal is to reduce ambiguity — the more clearly AI systems understand your content structure, the more confidently they can cite you.