Right now, you can buy front row presence in AI search for the price of a serious content effort. In two years, you’ll need a budget and a media buyer. Most companies will only realize this in retrospect.
There’s a specific kind of regret in marketing—the kind tied to missing early opportunities across the broader digital marketing evolution.
Anyone who didn’t claim a Twitter handle in 2008 knows it. Anyone who didn’t run Facebook ads in 2013, when CPMs were a fraction of what they are today, knows it. Anyone who didn’t ship an iOS app in 2010 knows it. Anyone who looked at Google Ads in 2003 and decided clicks were too expensive at fifteen cents knows it most of all.
The pattern is always the same. A new surface opens. For a brief period, it’s underpriced. Early movers get disproportionate returns for the effort they put in. Then the surface matures, the rest of the market piles in, the price of attention rises, and what used to be a leverage play becomes table stakes.
We are squarely inside that brief period for AI search. And the people who will benefit most from it are not the ones writing about it. They’re the ones quietly executing on it while the rest of the market is still debating whether it matters.
What “cheap” actually means right now
Let’s be specific about what’s currently underpriced, because “AI visibility is cheap” is the kind of phrase that sounds vague enough to ignore.
This is where Generative Engine Optimization (GEO) becomes critical.
Right now, in the cybersecurity category, you can earn meaningful AI visibility by doing things that are largely free or that fit inside an existing marketing budget. Restructuring your service pages costs editorial time. Publishing one piece of original research per quarter costs a researcher and a designer. Pitching expert quotes to industry publications costs PR effort, not media spend. Building a named expert profile for your CISO costs coordination and a willingness to be public.
None of this requires you to outbid anyone. There is no auction. There is no rate card. The “cost” of being mentioned in an AI answer is the cost of the work that earns the mention. That work is not trivial, but it’s bounded, predictable, and sits well within the operating budget of any cybersecurity firm with a marketing function.
That’s what “cheap” means in this context. Not free. Underpriced relative to the value it produces and to what the same outcome will cost two or three years from now.
Why this won’t last
Every underpriced surface eventually corrects. AI visibility will correct in three predictable ways, and you can already see the early signals of all three.
The first correction is competitive saturation. Right now, in most cybersecurity sub categories, only a handful of firms are doing serious AEO and GEO work. That means the bar for being cited is “do the basics well.” When a hundred firms in the same sub category are doing the basics well, the bar moves. You’ll need original research that’s not just credible but distinctive. Named experts who are not just credentialed but well known. Authority footprints that are not just present but dominant. The work gets harder because the field gets crowded.
The second correction is paid placement. AI platforms are businesses. They will, eventually, monetize. Some already are, in early forms. Sponsored mentions, ad slots inside answers, premium placements, paid context windows. None of this exists at scale today. All of it is plausible within a few years. When it arrives, the firms with established organic citation will be hard to dislodge, and the firms without it will be paying retail to enter conversations that early movers entered for free.
This is exactly the arc Google Ads followed. In 2002, you could buy intent rich clicks for cents. The advertisers who built their funnels on those clicks compounded for years. By 2010, the same clicks cost dollars. By 2020, in B2B technology categories, they cost tens or hundreds of dollars. The platform didn’t change. The competition for the surface did.
The third correction is platform sophistication. AI engines are getting better at evaluating sources. They’re getting better at distinguishing genuine authority from manufactured authority. They’re getting better at noticing when a “named expert” is a marketing construct rather than a real practitioner. As these systems mature, the cost of faking your way in goes up. The firms that built real authority while the systems were still forgiving will benefit from inertia. The firms that try to enter later, with a hastily constructed footprint, will face skepticism the early movers never had to overcome.
All three corrections are coming. None of them are urgent today. All of them will be in two to three years.
The historical comparison nobody wants to take seriously
I’ve been in marketing long enough to remember when SEO was new, when paid social was new, when content marketing was new, and when influencer marketing was new. The arc is identical every time, and yet every time, the late majority insists it’s different.
Early SEO, around 2003 to 2007, was a land grab. You could rank for highly competitive terms with surprisingly little work, because most of your competitors didn’t yet believe the channel mattered. The firms that built ranking authority in that window owned their categories on Google for the next decade. By the time the late majority arrived in 2010 and 2011, the work had become twenty times harder for the same outcomes.
Early Google Ads, around 2002 to 2005, were similarly underpriced. Marketers who learned the platform when it was forgiving became the practitioners who, ten years later, were running multi million dollar accounts. The platform got harder. The early operators kept their advantage.
Early Facebook ads, around 2012 to 2014, allowed direct to consumer brands to acquire customers for a few dollars a head. That window closed brutally. By 2018, CPMs had multiplied many times over and the same brands were paying ten times more for the same customer.
Early LinkedIn organic, around 2018 to 2021, was a writing exercise that any thoughtful operator could win. Today, the platform is saturated, the algorithm is harder to please, and the same content effort produces a fraction of the reach.
Every one of these surfaces was once cheap. Every one of them stopped being cheap. The people who got rich, professionally and literally, were the ones who didn’t wait for proof.
AI visibility is the next iteration of the same pattern. The signals are all there: a new surface, growing user adoption, no auction, underdeveloped competitive response, and a small group of early operators starting to pull ahead. The only question is whether you’ll act on the pattern or wait for the consensus.
In each case, early adopters built momentum that fueled long term marketing growth strategy.
Some also turned that early traction into scalable lead generation system advantages.
Why the cost of inaction is higher than the cost of action
The clearest way I can frame this is through asymmetry.
If you act now and AI search develops slower than expected, the worst outcome is that you’ve improved your content structure, built original research, strengthened your named experts, and accumulated third party authority. Every one of those investments has standalone value. None of them get wasted. You end up with a better marketing foundation regardless of what AI search does.
You create a stronger foundation that helps increase business performance.
If you wait and AI search develops as fast as the trajectory suggests, the cost is structural. You miss the cheap window. You enter the surface as a follower, when the work has gotten harder and the early movers have established preference. You spend two years trying to displace incumbents who needed six months to establish themselves.
That’s not a balanced bet. That’s an obviously skewed one. The downside of acting is bounded and recoverable. The downside of waiting is unbounded and difficult to reverse.
The firms that frame this as “we’ll see how AI search develops” are making a decision, even if they don’t realize it. They’re choosing to absorb the cost of being late in exchange for the comfort of being certain. In emerging surfaces, that trade has historically been a bad one.
What “going early” actually looks like
Going early doesn’t mean being reckless. It doesn’t mean betting the company. It doesn’t mean abandoning channels that work today. It means allocating a meaningful, sustained portion of your marketing capacity to the new surface while it’s still forgiving.
Practically, for a cybersecurity firm, that looks like:
A standing investment in AEO work. Every page you publish, from now on, is structured for direct answer extraction. No exceptions. No “we’ll go back and clean up the old ones eventually.” Every new page meets the standard.
A quarterly cadence of original research. Not warmed over thought leadership. Real artifacts: surveys, threat reports, benchmarks, vulnerability analyses. Things other people in your industry will quote.
A systematic program for third party authority. Pitches to industry publications. Appearances on podcasts that publish transcripts. Conference talks that get recorded. Bylined articles. Expert quotes in journalist driven pieces.
A named expert program for your senior practitioners. Your CISO, your researchers, your senior engineers. Real public profiles. Real public points of view. Real visibility that the model can attach to your firm.
A measurement discipline that treats AI visibility as a primary KPI, not a curiosity. Manual queries, automated tracking, trend reporting, executive dashboards.
None of this is exotic. All of it is currently underpriced relative to what it produces. The firms doing this work in 2026 will be the firms that own AI visibility in 2028.
It’s not complicated.
It’s consistent execution.
- Structured content through a focused AI SEO strategy
- Ongoing original research
- Strong third party authority
- Review signals that support local business growth signals
All of this contributes directly to stronger demand and better positioning.
Strategic takeaway
The market is not going to politely warn you when the window closes. There won’t be a press release. There won’t be a Gartner report headline. The window will close the way these windows always close: gradually, then suddenly, and then it will be obvious in retrospect that everyone should have moved earlier.
Speed of execution is the actual competitive advantage right now. Not budget. Not brand recognition. Not how long you’ve been in the market. Speed.
The firms that move in the next two quarters will lock in semantic associations, third party footprints, and named expert recognition that will compound for years. The firms that wait until AI visibility is “proven” will arrive at a surface that’s no longer cheap, no longer forgiving, and no longer empty.
Every gold rush has the same structure. Early arrivals stake claims. Late arrivals pay rent. The ground itself didn’t change. Only the price of standing on it.
Closing
There’s a phrase I keep coming back to with the cybersecurity founders I work with: the work doesn’t get easier. The work gets more expensive.
The firms that move now will control category level visibility—and dominate long term sales performance.
Right now, the work of becoming visible in AI search is meaningful but manageable. A real commitment. A real sequence of moves. A real timeline. But manageable.
In eighteen months, the same outcome will require more research, more PR, more named expert investment, and more competitive jostling against incumbents who started while you were still deciding. The work itself doesn’t change. The price of doing it does.
This is the cheapest the surface will ever be. That’s not a sales line. It’s the unanimous lesson of every previous platform shift in digital marketing. Early was always cheap. Late was always expensive. The pattern doesn’t break.
The only question that matters is whether your firm wants to be the one paying entry level prices for category defining visibility, or premium prices to claw your way into a conversation that’s already happening without you.
The window is open. It won’t be open forever. The firms that act on that, instead of around it, are the ones who will be quoted, cited, and recommended in 2027 and beyond.
The rest will be writing case studies about how they wished they’d started earlier.
Written by Razvan Calarasu: Founder of High 5 Guru, specializing in AI visibility, GEO, and AEO strategies for Digital Marketing firms.
