Schema Markup for AI: The Tags That Help You Get Pulled

Using schema markup from Schema.org has long been a staple of SEO campaigns, but did you know that it also matters for AI search?

Using schema markup for AI adds context, builds trust, and increases your chances of appearing in AI-generated responses. 

But why is that? What is schema markup?

You can think of schemas as labels for certain types of content. 

Imagine reading a book that’s one massive wall of text. You can technically still read it, but you have to guess where each chapter begins and ends. 

Using schemas is the equivalent of adding sticky notes to the book that clearly label things like:

• The author 
• The name of each chapter 
• The forward and prologue 
• The index at the back 

In the same vein, schemas add helpful context to your online content by distinguishing:

• Recipes
• Reviews
• FAQ sections 
• Hours of operation 
• Author biographies 

This makes it much easier for search algorithms and AI platforms (ChatGPT, Perplexity, Claude, etc.) to pull information from your website. 

As a result, you’ll increase your chances of appearing in AI-generated responses, summaries, and overviews. 

This guide will teach you how to properly use schema markup for AI search campaigns, so don’t go anywhere! 

How Schema Influences AI Search 

In order to properly identify and understand things like brands, people, places, and things, AI tools go through a process called entity recognition. 

It’s how AIs are able to distinguish things like Amazon the company from the Amazon rainforest. 

To recognize entities, AIs use a combination of tokenization, pattern recognition, and context analysis. 

Do you know what helps AIs with context analysis?

You guessed it, schemas! 

As we’ve already explained, schemas clearly label things like reviews, products, authors, and FAQ sections. This makes it easier for AIs to identify your brand as a distinct and consistent entity. 

Consistency is the name of the game here. 

If you want to get cited by AI search tools more often, adding schema markup is a must. 

Schemas make your content machine-readable, which, as we’ve mentioned before, is like labeling specific aspects of your content (like reviews and FA Q sections). 

This makes it effortless for AI tools to pull information from your website. 

For example, if a user asks a chatbot about your hours of operation, it can snap to the openingHours schema to quickly find them. 

This removes the need for ‘guesswork,’ where a chatbot has to do things like:

1. Scrape the visible text on your website (like your Contact Us page) 
2. Check third-party listings
3. Look for cached versions of your website containing the information 

If the chatbot still isn’t able to find the information, it may tell users that it just doesn’t know. 

Instead of making AI tools jump through all those hoops, it’s best to include schema markup so that all your business’s information is readily available.   

Also, schemas occur behind the scenes in your site’s code, so you won’t have to worry about them interfering with your user experience. 

What are the Must-Have Schemas for AI?

By now, it should be clear that schema markup is extremely important for improving your visibility on AI search tools. 

It makes pulling information from your site easier, reduces inaccuracies, and establishes your brand as a consistent entity. 

Yet, we still haven’t explored which schemas work best for improving AI visibility. 

After all, there are over 800 different schemas, and it can be daunting to know where to start. 

Here’s a breakdown of the schema types that matter most to AI search tools. 

Organization and Person 

Remember when we mentioned how entity recognition helps AI tools distinguish things like Amazon, the eCommerce company, from the Amazon rainforest in Brazil?

Well, the Organization schema plays a big role in that process. 

This schema lets AI tools know that your brand name represents a real company, and not something else. 

It removes all the ambiguity from company names (like Apple or Amazon) and establishes you as a verifiable entity (instead of just a word). 

The Organization schema also enables AI tools to link your brand to other sources of trusted information, like your company’s Wikipedia page. 

Using this schema lets AI tools know, “Oh, you’re the company from these other sources, too.”

The sameAs field comes in handy for this very reason. 

In it, you can list your brand’s page on other trusted platforms, like Wikipedia or LinkedIn. 

Here’s an example of this schema in action:

{

“@context”: “https://schema.org”,

“@type”: “Organization”,

“name”: “The HOTH”,

“Url”: “www.thehoth.com”,

“sameAs”:  [

https://www.linkedin.com › company › thehothseo

  ]

}

Here, we’re letting AI tools know that we’re a real business entity named The HOTH (and not a planet from Star Wars). 

What if you aren’t an organization, but an individual practitioner like an author, lawyer, or doctor?

In that case, you would use the Person schema. 

This lets machines know that your name represents a verifiable person with expertise and authority. 

Within this schema, there are property fields such as:

• Name – The professional’s full name

• JobTitle – Their job title 

• Affiliation – Their company, university, publication, etc.

1. 1. Alumniof – Their educational background

• SameAs – The professionals’ other online profiles 

• Image – A photo of the person in question 

• URL – Their official website (if applicable) 

Check the schema’s page linked above to see the full list of properties.

This schema is important for reducing ambiguity, clarifying expertise (which is essential for Google’s E-E-A-T), and heightening your chances of appearing in AI summaries. 

FAQ and HowTo 

The FAQ schema is HUGELY important for both SEO and GSO (generative search optimization, which is optimizing for AI search). 

Why is that?

It’s because answering common user questions is a major way to generate traffic. 

That applies to both traditional search (Google and Bing) and AI-powered search (ChatGPT and Perplexity). 

As we’ve clearly established so far, text is just text to machines if there’s no schema markup. 

Thus, you need a way to communicate that “this page contains a series of commonly asked questions, and here they are, all clearly labeled.”

The FAQ schema does just that, which is why it’s so useful. 

HowTo is another massively important schema that applies to your instructional content. 

If you’re producing a tutorial or ultimate guide, you’ll want to use this schema because it identifies your content as instructional. 

It also makes it easier for AI tools to extract each of the steps included in your content, and it helps them understand the topic you’re discussing. 

All these factors increase your chances of appearing in rich snippets and AI citations. 

Article and BlogPosting

Next, you need to clearly identify the articles and blogs on your website, which is where these two schemas enter the picture. 

The Article schema is primarily used for news articles, interviews, and in-depth analyses. 

BlogPosting is for all your blog-style content.

Both contribute to consistent entity recognition and will improve your visibility on AI search tools (and traditional search engines). 

Review and AggregateRating 

Lastly, you can’t forget about your reviews, as they’re one of the most important trust signals for AI search tools. 

Use the Review schema for individual reviews, and the AggregateRating schema for your average score across multiple reviews. 

Remember, AI tools will only recommend the businesses they think are of the highest quality, so you’ll need a stellar review profile. 

Implementing Schema Markup the Right Way (Especially Review Schema) 

Schema markup is most commonly encoded in JSON-LD, but it can also use Microdata, RDFa, and others. 

You need to place your schema markup in the or section of your HTML. 

There are also WordPress plugins like RankMath and Yoast SEO (with Schema Pro included) that will add the markup to your website for you. 

Schema.org is obviously a great resource for learning how to write schema markup, but you shouldn’t rely on it alone. 

There are plenty of tools that simplify and expedite the process, such as:

These will help you create all the schemas mentioned in this article (FAQ, HowTo, AggregateRating, etc.). 

From there, you need to test your markup to see if it works properly. 

To do that, you can use Google’s Rich Results Test and the Schema.org Validator. 

These tools will spot errors and let you know if search engines (and AI tools) are able to view your data. 

Common Mistakes to Avoid 

Here are some beginner pitfalls you don’t want to wander into:

1. Don’t overtag web pages with conflicting schemas or unnecessary properties. For instance, a simple blog post should only receive the BlogPosting schema, and not others like Product (even if a product is mentioned). 
2. Use testing tools like the ones mentioned above to avoid using invalid code. 
3. Don’t ignore third-party review sources when configuring your Review schemas, but ensure you have permission to do so. 

Final Thoughts: Using Schema Markup to Improve AI Search Visibility 

In the age of AI-powered search, schema markup is no longer optional, especially for reviews. 

If you want your brand to consistently appear in AI-generated summaries and overviews, you NEED proper schema markup so that AI tools can easily pull information from your site. 

Do you need better schema markup for your site?

Get in touch with our team for a structured data audit and review integration strategy!