--- source_url: "https://contentmarketinginstitute.com/seo-for-content/structured-data-ai-engines" title: Structured Data Helps Brand Visibility in AI Engines mirrored_at: 2026-08-24T01:08:44.003Z host: contentmarketinginstitute.com cited_in_42a: true mirror_canonical: "https://index.42a.ai/contentmarketinginstitute.com/seo-for-content/structured-data-ai-engines" --- > **Original source:** https://contentmarketinginstitute.com/seo-for-content/structured-data-ai-engines Search isn’t dead; it’s just growing up. Artificial intelligence overviews (AIO) and large language models (LLM) have reshaped how people seek information. Instead of scanning search engine results pages, audiences increasingly ask complex questions of these AI-driven tools and expect them to source information, summarize it, and contextualize answers instantly. “Traditional search engines are now becoming answer engines,” says [Caerley McShane](https://www.linkedin.com/in/caerleyhill/), global SEO lead at SAP. Caerley joined [Martha van Berkel](https://www.linkedin.com/in/martha-van-berkel/), CEO and cofounder of Schema App, at [Content Marketing World](https://contentmarketingworld.com/) to explain what this shift means, why content structure could be your competitive advantage, and how you should start implementing it. Watch the presentation or read on for the highlights and takeaways. ## Search traffic declines, but influence grows For B2B brands, this information-seeking evolution creates a paradox. “For B2B, this may mean that consumers will never go to your site, but they’re still going to use your content,” Caerley says. Related:[How To Build Content That Both Humans and AI Agents Trust](https://contentmarketinginstitute.com/seo-for-content/build-content-trust) That doesn’t make search irrelevant. It changes what success looks like. “Citations are swiftly becoming the first page of search,” Caerley says. Being referenced as a trusted source influences brand awareness, perception, and trust even when [users never click through](https://contentmarketinginstitute.com/strategy-planning/new-digital-topography) to your site. SAP measured that impact. Between 2024 and 2025, SAP saw traffic from LLMs grow 168%. LLM-referred visitors remain a small slice of SAP’s total traffic, but their behavior is more valuable. They’re more engaged and twice as likely to convert. The takeaway? Visibility is no longer just about ranking pages. It’s about whether [AI engines understand, trust, and reuse your content](https://contentmarketinginstitute.com/seo-for-content/build-content-trust). ## Why structure determines AI understanding Getting AI engines to believe in your content requires more than clear writing; it demands [well-organized information](https://contentmarketinginstitute.com/content-optimization/how-to-optimize-content-organization-for-2025-think-context-not-hierarchy). Martha explains that unstructured content pages make it difficult for AI systems to understand nuances and relationships. The machines infer meaning by analyzing how ideas connect, not just by scanning keywords and phrases. That’s why [Google](https://developers.google.com/search/blog/2025/05/succeeding-in-ai-search) and [Microsoft](https://blogs.bing.com/webmaster/May-2025/IndexNow-Enables-Faster-and-More-Reliable-Updates-for-Shopping-and-Ads) both say structured data improves visibility in AI-driven search experiences. Early research already shows how structure affects AI understanding. An experiment by Aiso [tested the identical content on structured pages vs. unstructured pages](https://www.getaiso.com/blog/schema_markup_experiment_blog_post). Researchers provided ChatGPT with links to the company background, product pricing, CEO background, awards and recognition, and contact information, then asked the same questions of each version. Related:[Déjà Vu All Over Again? Answer Engine Optimization Is a Familiar Trap](https://contentmarketinginstitute.com/seo-for-content/answer-engine-optimization) The results revealed the value of structure: ChatGPT responses using the structured pages scored 30% higher for accuracy, completeness, and presentation quality than their unstructured counterparts. ## Moving from keywords to entities Schema markup provides scaffolding for structured content, telling machines what the content is about. “It’s the language of search engines and now the language of AI,” Martha says. Schema markup has long been associated with rich results in search — stars, pricing, videos, and other enhanced listings. Those results still matter. However, as AI-driven answers replace clicks, rich results are no longer the end goal. They’re a signal that structured data is working — not the primary reason to use it. When content is marked up using schema language, machines no longer see only strings of text. They see named things — a person, a product, an organization, a topic. Each is defined with properties and relationships. Those defined things are called entities. Here’s how an unstructured site may appear to machines — software application, organization, and offer are viewed as separate pages with no explicit relationship between them. ![How an unstructured site may appear to machines.](https://eu-images.contentstack.com/v3/assets/blt663d10211b43b0ca/blt2664f270b7229c42/695be491dc865eb1adf2ead0/unstructured-site-example.png?width=1400&auto=webp&quality=80&disable=upscale "How an unstructured site may appear to machines.") That same site with structured content using schema markup would look like this: Related:[19+ Expert Ideas To Update Your Traditional SEO Strategy In the AI Era](https://contentmarketinginstitute.com/seo-for-content/update-seo-strategy-ai) ![That same site with structured content using schema markup.](https://eu-images.contentstack.com/v3/assets/blt663d10211b43b0ca/blt8f5927c35e6b0e9e/695be4da6c339cb2ffd5b112/structured-site-example.png?width=1400&auto=webp&quality=80&disable=upscale "That same site with structured content using schema markup.") With structured content, each page — software application, organization, and offer — is connected. The schema language connects the software application page to the organization page as its “provider” and to the offer page as the “itemOffered.” The offer page connects back to the organization as “offeredBy.” The organization page then links to external sites that reference the brand using “sameAs” language. Unlike one-dimensional keywords or phrases, entities describe what things are and how they relate to other things. Martha shares an example of a shoe. It’s a single word, but it has many attributes. With schema markup, that shoe becomes an entity described as leather, white, comfortable for walking, and styled with a buckle. That more robust description provides the context for machines to understand what the shoe is. Schema markup uses a shared vocabulary from [Schema.org](https://schema.org/) to define those entities and attributes in a consistent, machine-readable way, allowing search engines and AI tools to interpret meaning reliably across content. Once content is expressed as entities, those entities can be linked across pages and topics, allowing machines to understand how ideas connect across a site. ## Connecting entities into knowledge graphs When entities are consistently defined and connected across pages, they form a knowledge graph — a system of relationships that explains what a brand knows and how ideas connect. “A content knowledge graph is a collection of relationships of entities or things on your website,” Martha says. Knowledge graphs aren’t diagrams marketers draw or manage directly. They are how machines connect structured entities across content. That structure reduces AI hallucinations and improves grounding because LLMs can query a trusted network of information. It also allows marketers to ask better questions about content coverage, consistency, gaps, and performance. You move beyond page-level optimization toward managing a connected system of expertise. ## Structuring your content Building entities that will lead to content knowledge graphs may sound technical, but the steps are largely strategic. It doesn’t require reinventing your content strategy, but it requires a shift from traditional SEO page optimization to website optimization through structure and connections. Among Caerley and Martha’s advice: ### Focus each page on a single, clearly defined topic Pages that try to cover too many ideas make it harder for AI systems to identify the primary entity and understand how that content fits into a broader system of knowledge. ### Use schema markup to define what the page is about Schema language signals whether a page represents a concept, product, organization, or topic, so machines can interpret meaning consistently. Here’s an example of HTML code marked with schema language: ![An example of HTML code marked with schema language.](https://eu-images.contentstack.com/v3/assets/blt663d10211b43b0ca/blt71992f145bc2c6c8/695be51cffc87a4af2e2e91f/schema-markup.png?width=1400&auto=webp&quality=80&disable=upscale "An example of HTML code marked with schema language.") ### Link related entities across content When brands have authoritative content on a topic[, internal entity linking](https://contentmarketinginstitute.com/seo-for-content/internal-linking-for-seo-how-to-get-it-right) helps AI systems understand how ideas connect across pages, reinforcing the brand’s ownership of that subject matter. ## Measuring visibility in a zero-click world While brand visibility is the goal, traditional attribution metrics become harder. “The top of the funnel is just going to keep getting foggier and darker,” Martha notes. Until AI platforms provide better analytics, marketers must rely on directional signals, such as: - AI-referral traffic quality - Engagement and conversion rates - Citation presence in AI-generated answers. At SAP, Caerley uses a mix of analytics platforms, SEO tools, and direct testing within the AI systems to evaluate performance. ## Structuring content visibility and impact AI has changed a lot, but it hasn’t killed search or the value of [strong content](https://contentmarketinginstitute.com/ai-in-marketing/prioritize-website-content). Success will increasingly depend less on individual pages and more on the clear and consistent way brands present knowledge across their sites. Structured content, entities, and knowledge graphs make that possible. They provide the context that machines need to understand, trust, and use the information when delivering answers. Visit the [Content Marketing World](https://www.contentmarketingworld.com/) website for the latest on all things CMWorld.