The "Show Up" Fallacy
Agencies and consultants are selling the same old metric: visibility. They want you to "get found" in AI search.
But we see businesses show up in AI responses every day and still lose the deal.
Nobody talks about the Citation Trap. This happens when your content gets cited, the AI uses your data, your brand appears in the answer, and then the AI explicitly tells the user to go somewhere else. It says things like "Contact other lenders" or "Company X offers similar services."
You did the grunt work. The competition got the referral. Being cited isn't winning. Being recommended is.
Three Realities of AI Search
We ran tests on hundreds of queries across ChatGPT, Perplexity, and Google AI Overview. The results didn't fit a neat bell curve. They fell into three buckets.
First, you're invisible. The AI doesn't find you. You have no chance.
Second, you're cited. The AI scrapes your info but points the user to a competitor. You appear in the footnotes; someone else owns the answer. This is where most "optimized" businesses are stuck right now.
Third, you're recommended. The AI identifies you as the correct solution. You get the call.
The Rogue Sales Rep
Even when the AI talks about you, it often gets it wrong.
of AI-generated responses contained factual errors about the business being queried
Kodec analysis of 200+ query cycles
Think of it as a "Rogue Sales Rep." The AI is representing your business to thousands of prospects without your approval, using facts you didn't check, and making promises you can't keep.
We see revenue undercutting constantly. This is when the AI scrapes a price from a third-party reseller or an old listing. For example, we queried enterprise pricing for a mid-market cybersecurity platform. Google AI Overview returned only AWS Marketplace reseller rates—$35,000 to $141,000. The vendor's official pricing page wasn't cited once. Every prospect now anchors to a price the company doesn't control.
We also see entity confusion. The model merges you with a competitor or a company that went bust five years ago. Your reputation gets tangled with someone else's failures.
Then there are fabricated capabilities. The AI invents features you don't have or ignores the ones that actually matter. The prospect shows up expecting something you can't deliver, and trust dies on the first call.
Why You Can't Just "Edit" It
You can't call OpenAI and ask for a correction. There is no Google Business Profile for LLMs.
These models pull from the open web—your site, reviews, news, old blogs, and competitor comparison pages. It blends all that noise into one confident answer. If the web contradicts itself about your business, the AI flips a coin.
Training data is also static. If your pricing changed six months ago, the model might still be looking at a snapshot from last year. You can't retrain GPT-4. Even with live search, the system has to decide what to trust. If your site says $50k and a review site says $15k, it often picks the one with more backlinks, not the one that's true.
There is no feedback loop. When the AI lies about you—or recommends a competitor—you don't get an alert. You just lose the deal.
The Stakes
Prospects are asking questions about your industry right now.
"What's the best CRM for a 10-person sales team?"
"Who offers FHA loans for buyers with student debt?"
The AI is answering.
If it recommends you with the right facts, you win warm leads. If it cites you but recommends someone else, you are doing free marketing for your rivals. If it gets you wrong, you are competing against a ghost version of your own business.
You can't control the algorithm directly. But you can feed it. AI trusts structured data and clear signals about who you serve. You need a machine-readable source of truth that these systems can actually parse.
This is fixable. It just requires building infrastructure instead of writing more blog posts.