AI is changing how customers discover and evaluate brands. Enterprises need to think beyond rich results and develop the business context they publish for machines.
Schema Markup’s New Job: Help AI Understand Your Business
The new job I see for schema markup is to help AI understand your business, not just make individual pages eligible for rich results. That means explicitly describing your products, services, people, and locations, showing how they connect, and keeping those facts and relationships accurate as your business changes.
One of the biggest questions I hear from enterprise marketing leaders today is: How do we make sure AI is getting our brand right? It’s a fair question.
AI is increasingly influencing how customers discover, research, and choose businesses. Unlike traditional search, where customers could visit your website and form their own understanding, AI now brings information together from across the web to create answers on their behalf.
That information might come from your website, a third-party directory, customer reviews, or an article published years ago. And not all of it is necessarily accurate, complete, or up to date.
Here’s what I think is important for marketers to recognize: You can’t control everything AI says about your business. But you can take greater control of the information you give it, and that starts with your website.
Your website is one of the most valuable sources of information you own. It’s where you define who you are, what you offer, the expertise you bring to market, and what you want your business to be known for.
This is why I believe preparing the information you own for AI is one of the most important investments enterprise marketers can make today.
Assess Whether Your Schema Markup Is Ready For AI
And if your organization already has schema markup, you’ve already started building that foundation. The opportunity now is to think bigger about what it can do, and make sure your strategy is built for the job schema markup needs to do today and tomorrow, not just the one it did yesterday.
The good news is that if you’ve already invested in schema markup, you’re not starting from scratch. But not all schema markup is created equal. Before you focus on doing more, ask whether what you already have gives machines a clear, connected understanding of your business.
The opportunity is to assess the foundation you’ve built, identify where it could be stronger, and build from there.
Here are three questions I’d encourage enterprise marketing leaders to ask.
1. Check That Schema Markup Describes Your Key Business Entities
Having schema markup across your website is a great start. But is it capturing the information that actually matters to your business?
Think about your most important products, services, locations, and areas of expertise. Does your markup describe them accurately and in enough detail? Or is it simply meeting the minimum requirements for a search feature? The goal isn’t just more schema markup; it’s more meaningful markup.
Action Steps: Check Entity Coverage
[PLACEHOLDER — Schema App to supply practical steps for checking whether a priority page’s markup accurately describes its key business entity. Include what to inspect, an example of a missing or incomplete detail, and how the reader can verify the fix without a paid tool. Replace with sponsor-confirmed instructions before publication.]
2. Connect Your People, Products, Services, And Locations
It’s one thing for machines to recognize the individual parts of your business. It’s another for them to understand how everything fits together. Are your people, products, services, and locations consistently identified and connected? Can machines recognize when different pages are talking about the same thing?
Think about a healthcare system. It might have schema markup describing its physicians, hospitals, and medical services. That’s a great start. But does that information clearly communicate which physicians specialize in which treatments? Where they practice? Which services are available at each location? And how all of those things connect back to the healthcare system?
Move beyond describing individual pages to communicating a connected picture of your business.
Action Steps: Connect Related Entities
[PLACEHOLDER — Schema App to supply a worked relationship example, such as a physician, specialty, and practice location. Show the relevant page/markup, how to connect the entities consistently, and how the reader can verify the relationship without a paid tool. Replace with sponsor-confirmed instructions before publication.]
3. Keep Schema Markup Consistent With Your Website
Your business is constantly evolving. New services, new locations, new expertise. And as your website content changes, your schema markup needs to keep up. Because it’s not enough for your website to tell one story to customers while your structured data tells another to machines.
As your website evolves, does your schema markup keep pace, reflecting the same accurate information and maintaining the relationships that connect your business?
Our Wells Fargo case study illustrates why this matters. Wells Fargo encountered an AI Overview that incorrectly identified a branch as permanently closed. By strengthening the structured information on its website, the team helped address that inaccurate answer.
You can’t control every answer AI generates. But you can take greater control of the accuracy and consistency of the information you’re giving it to work with. And that requires governance to be part of your approach from the beginning.
Action Steps: Keep Markup Current
[PLACEHOLDER — Schema App to supply a concrete update-and-ownership procedure: who is responsible, what business or website changes trigger a check, what to compare between visible content and markup, and how to verify the correction. Replace with sponsor-confirmed instructions before publication.]
Understand Schema Markup Beyond Rich Results
For years, when marketers talked about schema markup, the conversation was largely about rich results. Does our website have schema markup? Is it valid? Are we eligible for those enhanced search features?
Those are still important questions. Rich results have delivered real value for businesses, and they remain an important part of a strong search strategy.
But somewhere along the way, I think we started confusing one benefit of schema markup with its full potential. Because schema markup was never just about helping search engines display information differently. Its bigger purpose has always been about helping machines understand information.
In fact, this idea goes back much further than Schema.org. In 2001, Tim Berners-Lee and his colleagues introduced the vision of the Semantic Web: a web where information wasn’t just published for people to read, but connected and described in ways machines could understand and use. That vision helped shape the foundation for the structured data technologies we use today, including schema markup. And what’s exciting is that we’re now seeing why that original vision matters so much.
There’s a big difference between describing the individual pieces of your business and helping machines understand how they all fit together. In traditional search, marketers largely focused on getting their websites discovered and bringing customers to their content. Now, AI is increasingly helping customers interpret that information, compare options, and make decisions.
That means we need to think differently about what we’re asking our schema markup to accomplish. We should question whether we’re giving machines the information and context they need to understand our business as a whole, and recognize our relevance to the topics that matter most.
Use Schema Markup To Build A Marketing Context Layer
But here’s the challenge: Across large enterprise websites, that information is often spread across thousands of pages, managed by different teams, and constantly changing. Even when the information is accurate on individual pages, it doesn’t always tell a clear, connected story about the business.
And sometimes, we’re contributing to the confusion ourselves. As Schema App’s CTO Mark van Berkel discusses in Forbes, AI doesn’t always need to hallucinate incorrect information. Sometimes, it works with conflicting information businesses have already published.
If we want AI to understand our business, we need to give it more than individual pieces of information. We need to help it understand how those pieces fit together. And for large enterprises, that’s not a small challenge.
Think about everything your organization publishes across its website. Your products and services, locations, your people and their expertise, the topics you want to be known for. All of that information helps tell the story of your business. But across thousands of pages, different teams, and constantly changing content, those connections aren’t always clear.
What if we started thinking about our website not just as a collection of pages, but as a connected source of truth about our business? That’s the opportunity I see with a Marketing Context Layer.
A Marketing Context Layer is a governed foundation of information about your business that helps machines understand who you are, what you offer, what you’re known for, and how it all connects. It starts with the information you own and publish on your website.
Through advanced schema markup, you can make important business facts and relationships explicit, connecting them into a Content Knowledge Graph that can be maintained as your business evolves.
And this isn’t just a marketing conversation. Forrester has been exploring the importance of context layers in enterprise AI, recognizing the role of connected business knowledge in helping AI systems interpret and use information. I believe there’s an important opportunity to apply that same thinking to marketing. If enterprises are investing in governed business context to power AI internally, shouldn’t we also be thinking about the context we’re publishing for AI to understand us externally?
This is where schema markup becomes much more than an SEO tactic. It’s the starting point for building a connected, governed foundation of information about your business. One you can keep improving, maintaining, and putting to work as search and AI experiences evolve.
As our CTO, Mark van Berkel, explores in Forbes, the organizations that want to make meaningful use of AI need to invest in the information foundations that support it.
For marketing leaders, that means recognizing the opportunity in the information you already own. You may not be able to control every answer AI generates about your brand. But you can take ownership of building the clearest, most connected, and most reliable representation of your business possible to support how accurately AI represents you.
Your Schema Markup Is the Starting Point
I believe we’re at an exciting turning point for enterprise marketers. We’ve spent years investing in our websites, creating content, and building our presence in search. Now we have an opportunity to make those investments work harder by helping machines understand the business behind the content.
And as AI continues to evolve, from search and answers to emerging agentic experiences, having clear, connected, and reliable business information will only become more important.
Because the goal isn’t just to be found. It’s to be understood. And that starts with taking ownership of the information we control.
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The opinions expressed in this article are the sponsor's own.