Here’s a scenario that should give you pause.
A specifier sits down at their desk, opens ChatGPT, and types: “What’s the best conferencing solution for a hybrid law firm?” A designer asks Claude for category recommendations before they write their next spec. A facilities manager uses Gemini to build a vendor shortlist before they ever pick up the phone.
Are you in those answers? Do you even know?
We spend a lot of time talking about what cool, useful tools we can build with AI to grow our businesses. Take a break from vibe coding for five minutes and ask a different question: What is AI saying about your company’s reputation? Because what AI is telling others about us is a very different question. And right now, it might be the more important one.
The Referral Network You Don’t Know You Have (Or Don’t)
Here’s how referrals work in our world. You do a great install, the client tells their architect, the architect puts your name in a spec, and suddenly you’re in the conversation before the client even knows they need you. Relationships, reputation, visibility. That’s the game.
AI-driven search works the same way. Except instead of your architect contact vouching for you over lunch, it’s a large language model pulling from hundreds of sources to decide who gets named and who gets passed over.
And here’s the uncomfortable truth: the brands winning that visibility aren’t necessarily the biggest or the best. They’re the most cited. The ones whose expertise lives in the publications, forums, and platforms that AI trusts as sources. The ones who’ve been building an earned media footprint, not just a social media presence, that AI can actually read and reference.
That changes the conversation about marketing entirely.
It’s Not SEO. It’s Not Social. It’s Something Else.
We’ve had the SEO conversation. Most AV integrators and manufacturers have, at some point, invested in getting their website to rank. And that work matters. But here’s what a lot of people don’t realize: early analyses of AI citation patterns suggest these platforms often pull from pages ranked well below the first page of traditional search. Your carefully optimized homepage may not be what AI pulls when a buyer asks about your category.
AI isn’t reading your meta descriptions. It’s reading your own website, plus the articles, reviews, case studies, and editorial features that live across the publications your industry trusts, and some that might surprise you. AI pulls from a wider range of sources than most marketing plans account for.
This isn’t a reason to panic. It’s a reason to pay attention.
The pushback I hear is predictable: AI hallucinates, the citations are unreliable, my buyers aren’t really using ChatGPT to pick vendors. Some of that is fair. But the buyers using AI to build a shortlist aren’t waiting for the tools to be perfect, and the ones who haven’t started yet will. The question isn’t whether AI gets every answer right. It’s whether your name shows up at all when it tries.
What AI Is Actually Saying (And How to Find Out)
Here’s a practical exercise. Open ChatGPT or Claude right now and type the query your ideal client would ask. Something like:
- “What AV companies should I consider for a corporate conference room redesign?”
- “Who are the leading integrators for higher education AV?”
- “What’s the best control system for a smart home?”
Read what comes back, not just the names, but the framing. Who gets described as a category leader? Who gets called a reliable option? Who isn’t mentioned at all? And then run the same query in another platform. ChatGPT, Claude, Gemini, and Perplexity will each give you a different answer, because each one is pulling from a different mix of sources. The brand that dominates one may be invisible in another.
That language didn’t materialize from nowhere. It came from the content those brands created, the publications that covered them, and the way those stories were told. The same dynamic that we talked about in terms of life-event marketing and business transition storytelling applies here: the narrative you put into the world is the narrative that gets repeated. The difference is that now, one of the entities repeating it (or not) is AI.
The Familiar Problem in a New Format
In the AV industry, we have a well-documented tendency to lead with specs instead of stories. We’ve talked about this in the context of residential clients who don’t want to hear about lumens, and commercial clients who don’t want to hear about wattage. But the spec-first habit shows up in our content, too.
Press releases full of technical features. Product pages that describe the what without ever explaining the why. Thought leadership that talks to the industry instead of talking to the buyer.
AI doesn’t just scan for brand names. It looks for context, authority, and relevance. A manufacturer who has published substantive content about the problems their category solves, written for the humans who need to solve them, is building something AI can actually work with. A manufacturer whose digital footprint is mostly product spec sheets is not.
The good news: this is fundamentally a storytelling problem, and storytelling is something we can fix.
Building Visibility That AI Can Find
You don’t need a massive budget or a technical SEO overhaul to start showing up in AI answers. What you need is the same thing that’s always driven great PR and marketing in this industry: consistent, credible, editorial-quality content in places that carry authority.
That means bylined articles in trade publications (yes, including this one). It means case studies that live somewhere with a real URL and real readership. It means being a quoted source in feature stories, not just running display ads around them. It means showing up in the conversations your buyers are having, in the language they’re actually using, before they ever reach out to you.
The brands building that footprint right now are doing something strategically smart: they’re investing in credibility at a moment when AI is actively learning which voices to trust. By the next ISE, by the next InfoComm, by the next time a major buyer pulls together a shortlist for a project you should be on, that gap between “cited” and “invisible” is going to be harder to close.
The Question Worth Asking
We’ve all gotten good at asking “where does my client look when they’re ready to buy?” The honest answer now includes AI platforms. And that’s not a future trend, it’s a current reality.
The follow-up question is the one most brands are skipping: What does AI find when it looks for me?
A quick search of your brand name, your category, and your most common use cases across a few AI platforms will tell you a lot. You might find out you have a strong presence you didn’t know you’d built. You might find out a competitor has quietly positioned themselves as the authority in language you’ve never used. You might find out you’re not showing up at all.
In our industry, we love data, and this is the kind you can actually act on. Armed with what you find, you can make informed, deliberate decisions about where to invest your time, your content, and your PR spend. A structured AI visibility audit, running your category, your competitors, and your most common buyer queries across the major platforms and tracking what comes back, turns that one-off search into a baseline you can actually measure against.
Whatever you find, you’ll know more than you did. And in a market where AI-driven discovery is quietly reshaping how specifiers, designers, and buyers build their shortlists, knowing is the only place to start.
Kat Wheeler
Kat Wheeler is an Account Executive at One Firefly, a role that allows her to combine her sales expertise and passion for marketing to help AV integrators grow. With 22 years in the AV industry, she has a successful track record of growing businesses, managing teams, boosting revenue, and creating marketing strategies across various sectors. Her love for technology began with her first computer, a Commodore64.
Currently based in Columbus, OH, Kat's career has given her the opportunity to live in seven states and visit 46. Not just about business; she’s authored two modern murder mysteries that creatively weave in technology, where the murders are both committed and solved using AV and you might see some familiar characters….
In her free time, you’ll find Kat practicing yoga, playing poker, and exploring new places. She dreams of one day owning a dog and making history as the first woman to win the World Series of Poker Main Event.
- Kat Wheeler
- Kat Wheeler
- Kat Wheeler
