Mike Downer: Hey everybody, I’m your host, Mike Downer, the Chief Storytelling Strategist for Jar Consulting Group, and I am joined once again by the president, CEO, founder, and the main man himself, Kevin Wosmansky. How are you doing today, Kevin?

Kevin Wosmansky: Good, Mike. How’s it going this sunny Friday afternoon?

Mike Downer: Oh, you know what? I couldn’t be happier if I were twins, buddy. Today, I know we want to dive a little deeper into how businesses are suffering from BD—and the reasons why business development is struggling in the age of artificial intelligence.

Kevin Wosmansky: Exactly.

Mike Downer: Today, I know that you wanted to talk about the Echo Effect and some third-party validation. Do you want to just scratch the surface on that?

Kevin Wosmansky: Yeah, absolutely. We’re trying to educate all of our clients—and really anyone who’s interested—in these little bite-sized nuggets. So yeah, let’s talk about the Echo Effect and third-party validation.

I guess the first thing I’d share with you is that AI models don’t simply trust a brand’s self-proclaimed expertise. This is probably one of the biggest changes in terms of how we’ve operated over the last 10 to 20 years and where the world is going today. It used to be that we could just throw some information out there, and if some of the algorithms picked it up, that was fine. There wasn’t a whole lot of background checking going on.

With artificial intelligence, we’re moving away from searching for a blue link and instead just getting the answer. Our AI goes out and gives us the answer. The reason we humans are going to get comfortable with having the answer given to us is mainly because the AI goes out and does the background check. Essentially, your AI is acting like a digital detective that goes out and performs the research. It verifies your claims.

Mike Downer: Let me ask you this, Kevin. We know that AI models are inherently skeptical. They don’t just take a brand’s word for it anymore. So how do we create an echo effect across the web that forces models to recognize us as the definitive authority?

Kevin Wosmansky: Yeah, great question. Basically, before AI cites you, it goes out and looks for corroborating evidence. It’s looking for different sources to verify that what you’re saying is real, authoritative expertise.

The thing is, AI is looking at multiple independent sources to ensure your brand is safe, consistent, and credible before it recommends you.

Mike Downer: Okay, that makes a lot of sense. So why is earning both a mention and a citation the secret to staying visible in AI answers?

Kevin Wosmansky: Yeah, I like the flow here. Let me break this down for you.

Before I jump into why earning both a mention and a citation is the secret to staying visible in AI, let me wrap up that Echo Effect.

In 2026, authority is built through cross-platform reinforcement. Those are some fancy words, but what it really means is that your expert voice gets recognized across lots of diverse places. For instance, our podcast—you and I working on this right now—we want this to appear on YouTube, Amazon Prime, Spotify, and Pocket Casts. You want your voice to show up across all these different channels.

Every business has different places they like to be. It could be Reddit. It could be industry journals. All of these different channels spike the model’s confidence in your brand as a legitimate entity.

So when we talk about the Echo Effect, what we really need to think about as business owners or brand managers is this: when we put out our expert opinions, expert analysis, and case stories, it’s critical today that we don’t just put this on a website blog. We need to share this information across all these different mediums and verticals. Whether it’s traditional news sources or other platforms, the more sources we can put out there, the more AI is going to trust what we’re saying.

Now to your second question: why is earning both a mention and a citation the secret? I call it the secret sauce.

The most visible brands, Mike, earn both mentions—their names are being named in a response—and a citation, meaning they’re being linked as the source. It’s kind of like, “Hey, I’m going to mention Mike, and I’m going to cite Mike.” That’s where you get the most impact.

Earning both of these signals really is the secret to stability. You read a lot of different things out there, but it’s pretty common to hear that brands with dual visibility are 40% more likely to stay present in AI answers than those that are just a footnote.

So it’s really important as we move forward into this new world to be mentioned and cited.

Mike Downer: So how do you extract that whole scenario for your business?

Kevin Wosmansky: Well, Mike, that’s a whole other episode. But just to wrap it up, how do you extract the perfect version of your content so you get cited and mentioned?

I’ll introduce a new phrase to you here: entity tokens. Using really high-value entity tokens in your dialogue makes the resulting transcripts really relevant to AI retrieval systems.

Now we’re talking about AI retrieval systems. They’re able to process and compute so much data so quickly across so many digital spectrums that when we’re looking to extract our high-value content, that’s really just fancy language for saying we want to make sure the expert analysis we’re talking about is easily digestible for large language models to find, reference, cite, and mention.

By seeding conversations with terms like AI models and citation authority, what we’re doing is literally engineering our transcripts to be the answer that AI pulls when users are looking for something specific.

This isn’t cheating. This isn’t black hat. This is just giving really genuine, organic, original content and analysis about what you’re doing—and making sure you’re talking about it in a way AI can understand.

At the same time, we’re humans, right? I have to make sure that you, Mike, understand what I’m talking about here. So there’s a little bit of method to the madness when you talk about producing content that is valuable and organic. I think that’s really the key.

Mike Downer: Very good. So like you were just saying, you want to make sure that I understand it. Do me—and all the people out there who are similar to me—a favor: take everything you just said, put it in a little bowl, and talk to me like I’m five. Make it super simple, because you used a lot of big terms and guys like me go, “Huh?” Just summarize everything you just said in very simple terms, like I’m a five-year-old.

Kevin Wosmansky: I got you, Mike.

If you’re a business owner or a brand manager—and this isn’t just for the multi-billion-dollar Fortune 100 companies—this is for the average Joe who has his own business. Maybe they’re the owner-operator, maybe they’ve got two or three employees, or maybe they’re a brand manager at a very large company.

What’s going to be critical in this new world really boils down to this: you have to share your expertise. You have to share your case studies, your stories, your real-life examples, your testimonials, and your opinions. That’s really critical.

As a business owner, whether you’re trimming trees or doing something else, your real-life experiences are what matter. When you’re cutting down a major tree over a house, experience matters. Opinions matter.

So you’ve got to be able to take that information and share it widely across as many different mediums as you can. YouTube has always been referenced as the second-largest search engine in the world, so that’s where we are today—right here on YouTube. If you’re able to, it only makes sense to share that information across other areas too.

If you’re doing a podcast format like we are, let’s get that up on Apple Podcasts. Let’s get it on Amazon Prime. Let’s get it on Audible. Let’s put it on Pocket Casts. Why not?

And when we do that, we want to make sure we’re talking in a way that large language models start to recognize that we’re a source of truth when it comes to our specific area of expertise. We also want to make sure that the average person watching this can learn from it and get something out of it.

Mike, I think that’s pretty much what it boils down to.

Mike Downer: See, that’s—you did a great job of summing that up and keeping it in very simple, understandable language. Everything you said before made sense, but now it really makes sense. So you did a great job driving your point home.

The only thing I have to ask you is this: as a business owner, if I’m sitting here and thinking, “Wow, that makes a lot of sense. How the heck do I do that? Is that something you can help people with?” Because I know personally I can hit a record button and I can hit the stop button, and then I’m done. My technical skills are nothing. So how does someone approach getting that out there like you said?

Kevin Wosmansky: Well, they could call Jar Consulting Group.

Mike Downer: There you go. That was what I was getting to. Shameless plug. But I mean, plug the company a little bit.

Kevin Wosmansky: Yeah, I appreciate that. No, really, here’s what I want the business owner and the brand manager to think about: how do you produce your content, and how do you do it in a way that’s valuable to your audience? And then how do you do that so all of the large language models can understand it and find it?

There’s a lot of technical stuff that goes into this. Step one would simply be: start producing some content. That is step one.

Now, depending on how far you want to go and how quickly you want to go, companies like ours specialize in this. There are things we’re able to do because we have systems, scale, and processes in place that allow us to help businesses get ahead.

I want to say one thing because I think it’s so critical for businesses to understand. In this new age of AI—and we’re specifically talking about business development, lead generation, and how your customers are going to find you—it is imperative that you start to initiate some type of system, or put some type of resources, toward large language model sentiment training.

There are going to be winners, and there are going to be losers in business very quickly. Businesses that used to get found organically and generate business simply because they showed up are going to find that this will go down and phase out. Businesses that have always been great at producing content and have always focused on expert analysis—even if they didn’t have a lot of clientele before—are going to start getting a lot more calls.

I have clients right now telling me that people are calling them because they found them on ChatGPT or because another AI recommendation engine suggested them.

So I can’t stress enough how critical this is for the business owner. We work with a lot of small to midsize businesses, and we work with a few pretty large businesses too. But as a small business owner myself, my heart and my passion are really there.

My purpose in spending time doing this is just to provide information and train people based on what we see and what we’re doing. We do this for a living. We produce content on a very large scale for many clients. We help them get all of that content out across all these different mediums.

So I just wanted a way to give back and help other business owners at least understand the importance of what’s happening and how quickly things are changing.

Mike Downer: Perfect. That’s all I’ve got.

Mike Downer: Great summation. I think we’ll wrap it up for today here. Kevin, you gave us a lot of information and a lot of things to think about—a lot of new knowledge—because this stuff is coming out quicker than anyone behind the scenes realizes. You’re helping everybody get on top of it, and we appreciate you.

Kevin Wosmansky: Appreciate it, man. Hey, you have a great day, Mike.