The AEO Industry Is Lying to You. Here's Why
AEO, SEO, and the three lies marketers are buying into
👋 Hey, I’m George Chasiotis. Welcome to GrowthWaves, your weekly dose of B2B growth insights—featuring powerful case studies, emerging trends, and unconventional strategies you won’t find anywhere else.
This note is brought to you by Minuttia.
Most people talking about AI search are still guessing.
We’re not.
Next week (May 21-22), we’re running a 2-day intensive AEO course for people who want to understand what actually works and how to apply it.
This isn’t theory. It’s the exact playbook we use:
How AI search really works (and how it differs from SEO)
How to build visibility across AI platforms
Where AI helps and where it kills quality
The workflows, templates, and tools behind our processes
The course is live, hands-on, and capped at 30 people.
If you want to move past noise and build real visibility in AI search, this is for you.
I gave a talk at a conference in Lithuania recently.
Going in, I knew it would be different from most of what the audience would hear over those two days.
The title alone made that clear:
The AEO Industry Is Lying to You. Here’s Why
I’m putting it down in writing now because the more I sit with the ideas, the more I think they need a wider audience than the room I was speaking to.
If you’re a marketer, an SEO professional, an agency owner, or someone running content strategy at a B2B SaaS company, this is for you.
A Quick Word on the Setup
Before getting into the lies, here’s how I see the current moment in search:
SEO got a bad reputation in the last three years. (Well, let’s make that 25 years, ever since search engines first showed up.)
And much of that bad reputation was created by the SEO community itself. Because search marketers are very good at harming their own profession.
While SEO’s perception was getting tarnished, interest around AI search exploded.
Pick whatever term you like: AEO, GEO, LLMO, AI SEO, whatever. (For simplicity, I’ll be using AEO from here on.)
You’ve seen the writing on the wall. Interest around AI search is picking up fast, while sentiment around traditional SEO has been trending downwards.
Zoom out and you see something more interesting.
SEO has been moving through phases since around the year 2000. November 2022 changed things, because ChatGPT pushed us into what I’d call the AI orchestration era.
Many of the things we do now are powered by AI. And AI search is becoming a real channel that adds to the existing pie of Google search.
We are operating in a complicated environment.
Marketers are looking for answers, which is partly why so many studies and data studies and reports keep getting published. People want data points to hold onto.
Our modus operandi has to change.
So far, so reasonable. Here’s where it gets uncomfortable.
The Three Lies (Overview)
The AEO narrative is broken in three specific ways. I’ll cover each one in detail, but here’s the short version.
Lie #1: AI search tracking tools. Sold as a new software category you can’t afford to miss. Visibility alone isn’t the alpha, and most tools can’t prove business impact.
Lie #2: AI search vs Google. We’re told AI search is a completely different game. In reality, there’s far more overlap with Google search than the SEO industry has communicated.
Lie #3: AI search metrics. New channel, new metrics. That’s the pitch. But many of the metrics being sold to marketers aren’t reliable enough to drive real decisions.
Let me explain each one.
Lie #1: AI Search Tracking
This is my favorite of the three.
In December 2025, Minuttia’s team conducted a study on the AI search software category.
The main objective was to get a better understanding of where the category actually stands and how healthy it really is. I have a personal interest in this beyond curiosity, since I’m also an investor in the space.
Our study used a combination of human analysts and AI agents. Every single data point was double-checked by a human.
In our dataset of 240 tools, we identified 176 that are AEO-native, meaning they were born to serve this category from day one. That’s 73.3% of the dataset.
Here’s the thing: even back in December, the category was already crowded. I expect that number to be higher now.
One of the most telling signals isn’t the number of tools. It’s the names.
You have AI Rank Pro. You also have AI Rank.Pro. And AI Rank Lab. And AI Rank Now. I’ll leave it there.
When that many tools converge on the same brand identity, you’re looking at a gold rush, not a market with clear differentiation.
Personally, I’m not very bullish on most of these tools. But before getting to my take, here’s what we found on funding.
Funding status
Roughly one in five AEO tools is known to have raised funding.
About one in five is still bootstrapped.
Just over half have no reliable funding status, which usually means they’re very small or very opaque.
Funding stages
Roughly seven in ten funded AEO tools are early-stage. As you’d expect from an emerging category.
Most of the capital is flowing into young companies, not into a wave of late-stage AEO giants. Many of these companies may not see another funding round.
For now, the category is full of early-stage businesses competing in an arms race.
Total funding
Total known funding across AEO tools sits at $257.9 million.
Which means…
A quarter of a billion dollars has been poured into a category we’re not even sure will exist in a couple of years.
To be fair, my doubt isn’t that AI search dies. ChatGPT and friends will keep doing web search to ground some of their answers.
My doubt is whether AEO survives as a standalone software category.
You see the Pareto principle at play, too. Roughly 73% of the capital is concentrated in a handful of Series A–B companies like Profound and AirOps.
Then you have a very long tail of obscure tools that managed to raise something.
What does this mean for you?
I split the implications into four buckets.
If you’re a software buyer: Not much changes for the worse. There’s no shortage of options, and competition will likely push prices down over time. Good for your budget.
If you’re building an AI search tracking tool: Unless you’ve raised serious capital or already have strong distribution, this might not be the most attractive category to build in right now. You might want to think about a another category instead.
If you’re an agency: You have plenty of tools to choose from. Look for partnership opportunities with these platforms. Shared audience growth is a real lever.
If you’re an investor: Expect volatility. Invest wisely. Don’t fall for the “future you don’t want to miss” pitch most of these tools will sell you.
My take (for now)
Here’s what I think happens next.
AI search tracking is already commoditized. It’s the core use case for almost all of these tools. Once a use case becomes a commodity, prices drop. That’s the first thing to expect.
Most of these tools will go out of business, consolidate or pivot. A handful of leaders will emerge (we are starting to see that already), but they’ll be under heavy investor pressure to grow faster, better, and more efficiently.
I doubt the opportunity is big enough to justify IPOs. From a liquidity standpoint, the realistic path for investors is acquisitions.
Which means companies like Ahrefs and Semrush (now under the Adobe umbrella) could end up buying some of these tools down the line. We’ll see.
And finally, expect headwinds. Especially around quality-of-results volatility, which is something Kevin Indig flagged in his 2026 outlook (link below).
The tactics that work today in AI search may not work in 12 to 24 months. The ground keeps moving.
That’s lie number one. Let’s move on to the next one.
Lie #2: AI Search vs Google
This one comes up almost weekly in conversations with marketing executives at Minuttia.
The line I keep hearing is some variation of:
“We want visibility in AI search, but we are not interested in SEO.”
Wait a minute. What do you mean?
Aren’t you aware of the overlap between the two? (Obviously not.)
Two reasons exist for this disconnect. Both worth discussing:
The perception hangover. SEO’s reputation has gone to hell over the last three years (or, if we’re being honest, the last 25). The SEO community has not done a good job of communicating the things that can come out of a strong organic search program. That perception bleeds into how marketing leaders make budget decisions today.
The relationship between AEO and SEO has never been clearly explained. Especially to marketing leaders who are far from ground truth and mostly influenced by peer chatter and influencer takes. The overlap is real. Most people just haven’t been told.
So when someone tells me they want AI search visibility but no SEO, my job is to stop, take a breath, and explain.
A reality check
Here’s how I lay it out:
There’s no universal answer in AI search. These systems are getting more personalized, with no fixed retrieval system you can game.
You can still influence the results, but you need a strong brand, up-to-date content, and strong off-site validation.
You shouldn’t disregard SEO. Don’t relent to internal pressure to drop it.
AEO covers a lot more than commercial prompts. That’s a common myth I keep running into.
AEO isn’t as simple as SEO used to be, but it’s not that complicated either.
There’s a big overlap between SEO and AEO, even though they aren’t the same thing.
That last point matters most. AI search adds to the search pie. It’s a good thing for SEO, not a replacement for it.
We need to do a better job of communicating the overlap.
Until we do, marketing leaders will keep making decisions based on a false dichotomy that wastes their budgets and their teams’ energy.
Let’s move on to the last one.
Lie #3: AI Search Metrics
There are lies, there are damned lies, and then there are AI search metrics.
I’ll use prompt volume as my example. It’s a metric marketers are being asked to make decisions on nowadays.
When a tool tells you that a specific prompt has X volume on ChatGPT, where does that number actually come from?
In most cases, it’s a combination of three things:
Panel data collection. Chrome extensions sit in a small number of users’ browsers and collect their ChatGPT (or other LLM) sessions. Desktop-only, partial coverage.
Keyword filtering. Out of that noisy dataset, the tool tries to isolate prompts that contain commercial terms.
Statistical extrapolation. That small panel sample then gets scaled up using modeling, to estimate what “market-level” prompt volume looks like.
In a nutshell, there’s a lot of data engineering between the raw signal and the number you see in the UI.
What I want you to take away is this: don’t take prompt volumes (or any other AI search metric) at face value.
What that looks like in practice
Steve Toth ran a side-by-side comparison every marketer should see.
He took prompt volume estimates from one of the most popular AI search tracking tools and compared them against Ahrefs Google search volume for the same keywords.
The differences are stunning.
The most striking one is “AI email agents.”
The tracking tool reported a volume of over 3 million on ChatGPT. Ahrefs reported around 170 for Google…
You don’t know what to believe when the gap is that big. Which is exactly the point.
Some tools handle this better
To be fair, not all tools publish raw extrapolated numbers.
Some, like AirOps (this is from work we are doing with one of our clients), use directional scoring instead. They give you a scale from Very Low to High rather than an exact figure.
That’s safer. It tells you something useful without inviting marketers to make budget decisions on the basis of inflated, easy-to-misread numbers.
Most marketers, especially junior ones, will take a precise-looking number at face value.
Directional scoring is one way to break that habit.
What to do about it
Four things to keep in mind when you’re evaluating any AI search metric.
Sanity-check volumes. Compare prompt estimates against an SEO tool and Google Search Console. If the gap is extreme, question the number.
Treat volumes as directional. Prompt volume is extrapolated panel data. Use it as signal, not as an absolute demand metric.
Understand the method. Chrome panel data plus keyword filtering plus scaling equals what, exactly? Know what you’re buying and what your decisions are resting on.
Expect noisy data. Most prompts aren’t commercially focused. They include all sorts of questions and tasks, and the filtering used to extract “commercial” prompts is imperfect.
That’s the third lie.
Final Thoughts
Be skeptical of any narrative being sold to you with the urgency of a gold rush.
The AEO category is real. AI search visibility matters. But the way the story is being packaged right now, by tools, by influencers, sometimes by people I generally respect, is making it harder, not easier, for marketing leaders to make good decisions.
Inflated metrics. False dichotomies between SEO and AEO. A flood of tools competing on the same commoditized use case. None of this serves the people who actually have to deliver results next quarter.
My advice: do the work, run the experiments, trust your own data over someone else’s marketing slides, and stay close to the people who are actually shipping content and watching it perform.
The fundamentals haven’t changed as much as the noise wants you to believe.
And if you’re at a B2B SaaS company and want to know how you’re doing in AI search (and Google search, because that’s still there), we can run a free AEO report for you. Click below and request your report.
Thank you for reading today’s note, and see you again next week.
Research Disclaimers and Limitations
GrowthWaves and its author are not sponsored by or compensated by any company mentioned in this note. This is independent editorial analysis and does not constitute investment, financial, or legal advice. The author may have relationships with, work with, or hold equity in companies referenced; however, no content in this piece was influenced, commissioned, or incentivized by any such relationship. AI tools were used as a research assistant in the preparation of this piece. All claims are sourced and linked throughout.
Sources
Steve Toth, “The Problem With Prompt Volume”