Structured data for AI trainers: beyond FAQ & HowTo

Structured data is often used to make content suitable for rich snippets in Google. Think FAQPage, HowTo, Product or Article. Content is increasingly used as training material for AI systems or as input for retrieval augmented generation (RAG). Structured data plays a new role as a result. I’ll show you how to use structured data strategically for AI processability.

Why structured data is becoming more important for AI

AI uses crawlers, embeddings and semantic parsing to understand text. If the content is well-structured, it is used in AI-generated responses.

Structured data helps search engines better understand what your content is about, adding additional information related to terms and topics that connect to knowledge databases such as Wikidata. Structured data used to mainly provide enrichment in search results, but now it works as a training method for AI models that generate answers independently. (1)

What works better than the standard formats?

The standard structured data formats FAQPage and HowTo are valuable, but are limited to specific content types. For AI use, you want broader formats that provide insight into thematic and semantic relationships. Effective structured data types for AI trainers include:

1. DefinedTerm
Ideal for highlighting concepts and technical terms. This gives meaning to concepts that AI models can recognize and link to knowledge structures.

2. EducationalOccupationalProgram or Course
For content that explains training or learning lines, use this schema to give structure to educational content. AI models use this to better organize content by difficulty and topic.

3. TechArticle
For in-depth technical content, you can use this type to distinguish between general and specialized explanations. Helps prioritize information for technical retrieval systems.

By using structured data smartly, I give Google and AI systems more context.

Issues to consider in implementation

Different priorities apply to structured data focused on AI processability than visual SERP enrichment. For example, you should have a focus on meaningful content, not visually appealing content. Provide a clear structure with content clusters. Use recognizable references whenever possible, such as linking to a page on Wikidata using the sameAs attribute.

This approach strengthens your position in knowledge networks and increases the likelihood that AI will use your answers. (2)

Structured data at a B2B platform

For an international B2B platform, I revised structured data with a focus on entities and relationships between content topics. Instead of just adding FAQPage schemas, I worked with TechArticle and DefinedTerm to better connect subject terms and product categories. I deliberately chose TechArticle and DefinedTerm because these schemas help AI better understand how subject terms and product categories relate to one another.

Within a few months, I noticed that not only did Google show more rich results, but the content also appeared more often in AI listings. This confirmed that structured data not only supports SEO, but also increases findability within AI systems.

Structured data as infrastructure for GEO

For Generative Engine Optimization (GEO), structured data is important for recognizing things. This helps AI systems identify relationships between pages and topics. In addition, structured data helps generate good snippets from your content. These are then used in AI-generated answers.

This makes structured data not just a tool for Google, but a strategic channel toward the broader AI ecosystem.

Summary

Structured data was a means to supplement results in the SERP, but now structured data is important for content processing in AI systems. Those who look beyond structured data such as FAQ and HowTo discover formats that connect to pre-existing human and machine knowledge, and to the meaning of pre-existing content.

By deploying structured data in the right way, you increase the likelihood that your content will be found and it will be actively processed. Thus, your content is displayed and reused in generated responses.

Frequently asked questions about structured data and AI

Of course you’d like to know how structured data works, especially in combination with AI and generative search engines. That’s why I answer the three questions I get most often about it.

What is the difference between structured data for SEO and structured data for AI?

In SEO, you use structured data primarily to help search engines understand what’s on a page. AI looks beyond that: what do you really want to say with the text? Structured data therefore links concepts together and makes connections so that generative models can better understand how topics are related. SEO structured data thus ensures visibility in search results. AI-structured data today also helps with inclusion in generated answers.

Does it still make sense to use FAQ and HowTo diagrams?

FAQ and HowTo diagrams are certainly still useful, but their function has changed. FAQPage and HowTo are practical tools for search engines. AI models learn primarily from semantic consistency.

So I combine FAQ and HowTo schema schemas like DefinedTerm and TechArticle, which better explain what a topic means and how it relates to other terms. This keeps your content relevant in both search results and AI responses.

How does structured data help with Generative Engine Optimization (GEO)?

Structured data establishes links between different pages and topics. As a result, generative systems understand not only individual words but also the meaning between them. The result: AI uses your content as a trusted source. As a result, your information appears more often in AI-generated answers.