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  • AI SEOSearch Engine Optimization
  • May 11, 2026
1 min read

How Businesses Can Get Recommended by AI Assistants

Key Takeaways

  • Customers are increasingly asking AI assistants for business recommendations and answers.
  • Businesses need to become the clearest and most helpful answer to the questions customers ask.
  • A modern, well-structured website helps AI crawlers understand the business.
  • Content should directly answer real customer questions, especially pricing and decision-making questions.
  • Entity clarity helps AI systems connect the business name, services, location, and brand identity.
  • Authoritative third-party citations strengthen credibility.
  • Schema markup helps AI systems classify and understand website content.
  • Reviews and reputation management are important trust signals.
  • Original, consistent, human-created content is stronger than generic mass-produced content.
  • AI recommendation takes time, consistency, work, and financial investment.

As more customers use ChatGPT, Gemini, Perplexity, Grok, Claude, and Copilot to search for answers, business owners are asking a new question: how do we become the company AI tools recommend? In an episode of The Unlearning Lab with JAR Consulting Group, Kevin Wosmansky and Mike discussed what it takes for a business to become visible, understandable, and trustworthy to AI assistants. Their discussion makes one thing clear: AI search optimization for businesses is not a shortcut. It is a disciplined process of building authority across your website, content, reviews, citations, and digital presence.

 

Why AI Recommendations Matter for Businesses

 

Customers are no longer relying only on traditional search engines. They are asking AI assistants for recommendations, cost comparisons, service providers, and expert guidance. That shift changes how businesses need to think about online visibility.

 

Kevin Wosmansky framed the question many business owners are already asking: how can a business get recommended by ChatGPT and other AI assistants?

 

“Somebody asked me a question. They were asking how they could get their business recommended by ChatGPT and AI assistants.”

 

That question is becoming more common because AI tools are now part of how people discover information. If a company wants to be recommended by AI, it needs to become the answer customers are looking for.

 

The Core Idea: AI Visibility Is a Trust-Building Process

 

AI recommendation is a trust-building process. Before a business can be recommended, AI systems need to be able to find the business, understand what it does, and trust it as a credible source.

That is the foundation of Generative Engine Optimization, or GEO. A business is not recommended simply because it exists online. It needs to send clear, consistent, and credible signals across the digital ecosystem.

 

This process often takes six months to a year, though it can happen faster or take longer depending on the business, the market, and the consistency of the work.

 

JAR Consulting Group’s Seven Areas of Focus

 

JAR Consulting Group uses a seven-area approach for helping businesses become more likely to be recognized and recommended by AI assistants. These are not one-time tasks. They are ongoing areas of focus that work together to build authority.

 

1. Build a Website AI Crawlers Can Understand
 

The first area is a comprehensive, well-structured website. A website still needs to serve human visitors, but it also needs to be easy for AI crawlers and search systems to parse.

 

That means the site should clearly communicate:

  • Who the business is
  • Where it operates
  • What services it provides
  • What expertise it has
  • How customers can contact it

The visible side of a website matters, including branding, readability, and user experience. But the backend matters just as much. Proper architecture, clean coding, and structured information help AI systems understand the business more accurately.

 

For GEO, the goal is clarity. AI systems should not have to guess what the company does.

 

2. Create Content That Answers Customer Questions
 

The second area is creating content around the questions customers are already asking. Customers frequently ask cost-related questions, such as:

 

  • How much does a website build cost?
  • How much does AI search optimization cost?
  • How much should a business expect to invest?

Many businesses avoid answering pricing questions because they do not want competitors to see the information. But if customers are asking these questions, the business should answer them clearly.

This is a key GEO practice: write content in the same language customers use when asking AI tools for help. AI assistants are built to answer questions, so businesses should create helpful, direct, question-based content.

 

3. Establish Entity Clarity Across the Internet
 

Entity clarity means making sure the internet understands exactly who the business is. The company name, location, services, contact information, expertise, and brand identity should be consistent wherever the business appears.

 

That includes:

  • The company website
  • Google Business Profile
  • Facebook page
  • Better Business Bureau listings
  • Industry directories
  • Review platforms
  • Other relevant third-party listings

Kevin added an important point about consistency:

 

“I’d add one more thing: your brand identity.”

 

That detail matters because a business should present the same identity everywhere so AI systems, search engines, and customers receive a consistent signal.

 

For GEO, consistency is trust. Conflicting information can make it harder for AI systems to confidently understand and recommend a company.

 

4. Earn Citations From Authoritative Sources
 

The fourth area is earning citations from credible third-party sources. AI systems place trust in outside references. If authoritative websites, communities, or publications talk about a business, those mentions can strengthen the business’s perceived authority.

 

Examples of valuable citation sources include:

  • Reddit
  • Industry journals
  • Trade publications
  • News sites

This does not mean chasing random backlinks. It means earning relevant, trustworthy mentions from sources that matter in the business’s industry.

 

For GEO, citations help confirm that the business is not just talking about itself. Other credible sources are also recognizing it.

 

5. Implement Proper Schema Markup
 

Schema markup is backend code that helps AI systems and search engines understand website content. It makes information easier for AI crawlers to read and classify.

 

Helpful schema types include:

  • Local business schema
  • FAQ schema
  • How-to schema
  • Speakable specifications

Schema helps turn website content into structured information. For a business trying to improve AI visibility, this matters because AI systems need clean, organized data to understand what the business offers and why it is relevant.

 

6. Maintain Active Review Profiles
 

The sixth area is online reviews. Businesses with strong and consistent reviews on platforms like Google, Facebook, and industry review sites are more likely to build the kind of trust signals AI systems can recognize.

 

Reviews are part of reputation management. They have long mattered for SEO and local search, and they now matter for AI-driven search as well.

 

For GEO, reviews provide public trust signals. They show that real customers have interacted with the business and shared their experiences.

 

7. Publish Original Content Consistently
 

The seventh area is maintaining a consistent content strategy across platforms AI systems actively consume. These platforms include websites, blogs, YouTube, LinkedIn, podcasts, and live original content.

 

Businesses should not rely on dumping large volumes of generic AI-generated blog posts onto a website. AI systems are increasingly focused on authentic, original, human-created content.

For GEO, the best content demonstrates real experience, clear expertise, and useful answers.

 

Building Trust Is the Real AI Advantage
 

The rise of AI assistants is changing how customers discover, compare, and choose businesses. The companies that win in this environment will not be the ones looking for shortcuts. They will be the ones that make themselves easy to find, easy to understand, and easy to trust.

 

That means building a better website, answering customer questions, maintaining accurate business information, earning credible mentions, managing reviews, using schema markup, and publishing original content consistently.

 

Businesses need to be found, understood, and trusted before AI systems can confidently recommend them. That is the real work behind AI search optimization for businesses.

 

FAQs

 
What podcast discussed getting businesses recommended by AI assistants?

The topic was discussed on The Unlearning Lab with JAR Consulting Group in a conversation between Kevin Wosmansky and Mike.

 

What company was featured in the episode?

The episode features JAR Consulting Group, with Kevin Wosmansky identified as the founder, owner, and CEO.

 

How can a business get recommended by ChatGPT or other AI assistants?

A business can improve its chances by building a clear website, publishing helpful content, keeping business information consistent, earning credible citations, adding schema markup, maintaining reviews, and publishing original content across platforms.

 

What is GEO?

GEO stands for Generative Engine Optimization. In this context, it means improving how AI assistants understand, trust, and potentially recommend a business.

 

Is GEO the same as traditional SEO?

GEO and SEO overlap, but they are not identical. SEO focuses on visibility in search engines. GEO focuses on helping AI assistants understand the business, evaluate its authority, and use its information when answering customer questions.

 

Why does content matter for AI search?

AI assistants answer questions. Businesses that publish clear, useful answers to real customer questions give AI systems more relevant information to learn from and reference.

 

Should businesses answer pricing questions on their websites?

Yes, when possible. Pricing is one of the most common question categories customers ask. Publishing helpful pricing content can make a business more useful to both customers and AI systems.

 

What is entity clarity?

Entity clarity means that a business’s name, location, services, contact information, expertise, and brand identity are consistent across the internet.

 

Why are citations important for GEO?

Citations from authoritative third-party sources help show that a business is credible beyond its own website. AI systems can use those outside references as trust signals.

 

What is schema markup?

Schema markup is structured backend code that helps search engines and AI systems understand website content more clearly.

 

Do online reviews affect AI visibility?

Active review profiles matter because reviews contribute to reputation and trust. Businesses with strong reviews may be more likely to be viewed as credible.

 

How long does it take to build AI recommendation authority?

It often takes six months to a year, though it may be faster or slower depending on the business and how consistently the work is done.

Mike Downer: Hey everybody, Mike Downer, Chief Storytelling Strategist with JAR Consulting Group. One of these days I’m going to be able to say that, Kevin. He is my boss. This is Kevin Wosmansky, the President and CEO of JAR Consulting Group.

Kevin Wosmansky: Mike, do we need to shorten that title for you there, buddy?

Mike Downer: Yeah, I think it should just be “loudmouth talker.” I mean, it’d be way easier to say. I’ve got “storytelling strategist.”

Kevin Wosmansky: There you go.

Mike Downer: A lot of syllables. All right, buddy. So, we’re getting back into this here. This is our fourth episode on the search intent shift and how to close the gap and win brand citations in 2026, part four. So, Kevin, we’ve talked about how critical it is to get cited by AI as a source of truth, but I have a couple of questions here wrapped into one. If our brand is mentioned on Reddit, that’s one thing, and then it’s listed on a website, that’s another thing, and then described differently on our LinkedIn bio, how does an AI actually know all these citations belong to the same JAR Consulting Group entity? And also, is it possible for AI to get confused about who we are, even if we’re being talked about everywhere?

Kevin Wosmansky: You know, Mike, I would say that could be the multi-million-dollar—no, scratch that—I’d say that might be the billion-dollar question for 2026. AI search engines don’t really comprehend brands. They don’t understand brands the way we people do. What we need to realize is that AI looks for stable patterns. Think about this: if your brand name, your company mission, and your expert voice all vary across Reddit, LinkedIn, or maybe the blog section of your website, what’s happening is you’re creating what they call interpretive friction. What that means is AI starts to see you as three weak entities instead of one powerhouse.

Kevin Wosmansky: So this takes us into a really important phrase we’re going to talk about, and that’s semantic consistency. What that is, again, in real fancy speak, is how we engineer the signals so that every mention, no matter where it happens, maps back to one single trusted node or source, which is the AI’s knowledge graph. When AI is 100% confident that it’s you, that’s when the citations really start to happen.

Mike Downer: So how does a company gain semantic consistency? How do they engineer that? How do you get AI to even trust that?

Kevin Wosmansky: Yeah, that’s through a lot of work. It doesn’t happen overnight, I’ll tell you that. Some brands, when you take a look at, let’s say, Coca-Cola, just using them as an example—a multi-billion-dollar brand recognized worldwide—they already have it. But they’ve also spent gobs and gobs of money to do it. Most small to mid-sized businesses are pretty fragmented.

Kevin Wosmansky: So when we talk about semantic consistency, we need to think about it as the practice of using coherent, uniform, expert-led language across all your digital platforms. What this does is reinforce your brand or your company’s entity signal.

Mike Downer: Okay, I’m introducing a lot of new terminology here. So, what’s an entity signal?

Kevin Wosmansky: Well, your entity signal is your consistent, coherent voice. By aligning the terminology that you use about your business, your product, and your service, you align that terminology across your website, your social platforms, and your podcasts. You need to do this so you reduce interpretive friction for AI models.

You know, in my business, we’ll have a service that, in the past, we would say is SEO. Well, SEO could refer to Google local SEO, Google Maps, search engine optimization, or backlinking. If I’m using four different terms, humans understand those are all really the same thing. The problem is AI doesn’t understand that. So when you are using one entity, one brand signal, and one consolidated voice, this starts to build statistical confidence for AI to recognize you as a canonical source of truth.

With AI, everything goes back to what’s a source of truth. This leads to much higher citation rates, and you start showing up when people are asking questions.

Mike Downer: So, real quick question for you. Looking at the past and the inconsistencies that people had that didn’t seem to matter as much back in the day, with AI they matter a lot more. Is there a way that JAR Consulting Group can help sort that out and start building consistency with a company rather than them trying to figure all this out on their own? Because it sounds very—

Kevin Wosmansky: Yeah, it is. And that’s what we do for a lot of our clients. We help them navigate this web and do all of this. So yes, absolutely. Your brand consistency, as we move into this new world, and what we’re talking about right here, Mike, with semantic consistency—I mean, again, that’s just a fancy way of saying you need to make sure that everything you put out there is consistent and coherent.

If you’re a roofing company, you need to use the same terminology on your social media as you use on your website, and as you use if you’re being interviewed by the local news station. You need to use the same terminology for what you do and who you are. That is what we help businesses with. We help them across the whole digital spectrum.

Kevin Wosmansky: Let me give you an example here.

Mike Downer: I was just going to ask, do you have an example of a client who you’ve kind of helped sort this whole mess out?

Kevin Wosmansky: Let me give it to you in a little bit different scenario here. I want you to think about AI as a librarian versus the AI brain, or traditional search. Traditional search is the brain; AI is the librarian.

Traditional search used to act like a librarian matching keywords to book titles. AI search in 2026 acts more like a brain, connecting nodes, entities, and relationships. So the citation trigger in this is what you’re seeing where the librarian is basically matching a keyword to a book title, while AI is that brain. Inside that library, it’s connecting the book and the card catalog, and it’s connecting the other four books that are part of a series or come after the first book. It’s connecting all of it together.

So I use that as kind of a convoluted example, Mike, to explain that a business in today’s world has to be able to speak with one brand voice about their services, their mission, and their topics—everything that they do—because what AI is doing is trying to connect all these different signals.

Kevin Wosmansky: Just in our world, we do what we call generative engine optimization, or GEO. Our service and our business are called AI Search Engine Authority. What that means is when we talk to our clients about how we help them, we say, “Listen, you need to become the search engine authority, and to do that, you have to become the expert.” So now we have to take your website, all of your social media, your interviews, and all these other things, and make sure it is very consistent. Semantic consistency, right?

Mike Downer: So, I think I’m catching on.

Kevin Wosmansky: Yeah, we’re engineering the signals that AI systems trust. That’s really what it comes down to.

Mike Downer: So I think I’m catching on.

Kevin Wosmansky: Yeah, that’s really what it comes down to. There’s a lot of new terminology I’m throwing out here at you, but the thing about it is this is how things are changing. This terminology matters.

Mike Downer: You’re doing a good job of keeping it simple, where even stupid guys like me can understand it. So I appreciate it.

Kevin Wosmansky: I appreciate that.

Mike Downer: All right, Kevin. So I think that wraps up our little four-part series on this. I’m just excited to see what your customers want to know about next and what you’re getting hit up with at JAR Consulting Group.

Kevin Wosmansky: Well, like I said, Mike, our whole goal is we’re just trying to help prepare all of our clients and customers not for what’s coming, but for what already came. I think a lot of people have been caught by surprise by how fast things are changing.

I just had a client of mine tell me that he had two customers call him, and he asked them, “How did you find out about us?” And they both said, “Well, I found you on ChatGPT.” When I’m starting to hear this every day—three or four months ago, I talked to my clients and they were like, “Well, I would never hear this.” It’s here.

What we’re doing is trying to help prepare all of our clients, and it starts with trying to educate them. We’re kind of closing out this little series that you and I came up with because this is what people are asking so many questions about—how search has shifted. People really need to understand that, like we said, the traditional two- to three-keyword search is still being used, and it still matters today, but it’s going to matter less and less every single day, every single month, for the rest of this year.

People need to understand that there is a giant gap between two keywords or three keywords and a prompt, or a conversation that a customer is going to have with an agentic model.

People always ask me, “How do I get the AIs to recommend me?” Well, guess what? Your brand must be cited, it must be reputable, and AI must be able to understand that all of the signals you put out are consistent, so that AI is confident enough to recommend you.

So we have to work with AI. We have to make sure it understands. There’s a lot of technical stuff. We haven’t even talked about schema markup, and that’s a whole other conversation. But that is just putting code on your website so AI can read it. Really, that’s all it is. Again, that’ll be a whole other conversation.

Mike Downer: So you’ve done a good job of explaining the foundation of where things are going. I know we still have a whole skyscraper to build, but I think you’ve laid a good foundation of where to start, how to start, why to start, and why it’s important.

Kevin Wosmansky: I appreciate that, Mike. Like I said, it’s a whole new world we’re in, and we’re just trying to help educate people. That’s the whole purpose of this.

Mike Downer: Sounds good. I think we’re all learning every day, and you’re just learning it a little faster than the rest of us. You’re doing a great job.

Kevin Wosmansky: I appreciate that, Mike. I’ll see you next week, partner. Have a good one.

Mike Downer: Sounds good.

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