AI has quietly become the layer buyers use to discover and vet brands. It is describing your company right now — and nobody on your team approved the copy.
Your brand's first impression is no longer something you designed. Increasingly it is a paragraph, generated on demand, delivered to a buyer you will never meet, assembled from whatever an AI could piece together about you. You didn't write it. You didn't approve it. You will probably never read it.
Try it before you read on. Open ChatGPT, Gemini, and Perplexity, and ask each one to describe your company. You'll likely get three different answers. At least one will be vague. At least one will be wrong. And if your name resembles another company's, one of them may be describing someone else entirely.
That used to be a party trick. It is now a distribution problem, because the search box is no longer the front door. Surveys suggest around 42% of US consumers have used ChatGPT to research a brand or product, and the behaviour is climbing fast in B2B — where the buyer doing quiet research months before they ever fill in a form is the norm, not the exception.
Citation is not ranking
Here is the part most teams miss: getting cited by an AI is not the same as ranking on Google. Google ranks your pages, so the work is making your page the best answer. An AI engine doesn't rank — it synthesizes an answer and cites the sources it already trusts, and your own website usually isn't one of them. What it leans on instead is what it can resolve: a consistent identity across the places it reads.
So the work splits into two problems most brands have never separated.
The first is resolution — can the machine reliably identify you at all? Same name, same category, same identifiers across Wikidata, LinkedIn, Crunchbase, industry directories, all agreeing with each other. This is unglamorous entity hygiene, and it is simultaneously the most skipped and the highest-leverage step in the whole game. If the model can't confidently tell who you are, it stays vague, picks the wrong company, or simply doesn't mention you.
The second is truth — when it does describe you, does it say the right thing? Your actual positioning, your actual claims, the things you are required to phrase precisely, rather than a plausible-sounding guess. This is the same failure mode teams are already living with internally. An IAB study found 70% of marketers have had an AI incident — an off-brand output, a claim they couldn't back, a hallucination that shipped. Forty percent had to pull ads over it, and only 6% believe their current safeguards are enough. The mechanism outside your walls is identical to the one inside them: a fluent model, filling a gap you left.
The same root cause
Both problems have the same root cause. The model is improvising because nothing authoritative ever told it the answer. And the instinct — check the output, correct the record afterwards — doesn't survive contact with the volume. Jasper's 2026 report found cross-functional review friction rose 3.4x in a single year, and that is for content you actually control. You cannot review an answer generated privately, on demand, for a buyer you can't see.
You don't control the model. You do control whether there is a clean, consistent, machine-readable version of your brand for it to find. Brands that build that get described accurately and cited by name. Brands that don't get summarized by an algorithm's best guess — to buyers who never knew a better answer existed.
The AI is going to describe you either way. The only real choice is whether you wrote the source it is reading from.
kbie is brand governance for the AI era — it turns your brand into a verified knowledge graph, so everything you and your AI tools publish stays on-brand, accurate, and safe to ship. → https://kbie.ai
