Korea AI Pulse

What GEO actually is — read off measured AI answers, not theory

2026-07-27 · Figures update whenever the measured data is refreshed

GEO — Generative Engine Optimization — is the work of getting a generative AI like ChatGPT, Claude, Gemini or Grok to name and recommend your brand inside its answer. SEO competes for a position in a list of results. GEO competes for a place in a sentence: when the model compresses the whole web into one paragraph, is your name in it or not?

How it differs from SEO

SEOGEO
What exposure looks likeRank in a list of resultsA mention inside the answer text
Unit of exposureA page (a URL)A brand, plus the stated reason, plus the citation
StabilityRankings move slowlyThe same question can return a different answer each time
How you measure itRank tracking toolsAsking the same question repeatedly and recording what comes back

The last two rows are the whole problem. An AI answer isn’t a value you can look up, so nobody knows whether your brand appears until somebody asks— and one week’s answer is no guarantee of the next week’s.

Three things the measured data shows

Korea AI Pulse puts the same real user questions to four AI engines every week and records what comes back. What that data shows is fairly different from the standard GEO explainer.

1. Each engine shows a different world

86%

Of the questions where at least two engines named real brands, the share where the four engines had zero recommended brands in common (measured)

“Being visible in AI” is really four separate problems. One engine can recommend you while the other three have never heard of you. In our data, 60–73% of the brands each engine named were named by that engine alone.

2. Every category has a different shape

Some markets are concentrated — insurance answers settle on a small set of names (38 distinct brands appeared). Others are fragmented— nobody owns restaurants (212 distinct brands). A concentrated category is hard to break into; a fragmented one is still up for grabs by whoever publishes first. Knowing which one you’re in is where strategy starts — the statistics page breaks this down by vertical.

3. Visibility is a flow, not an asset

When the same question was put to the same model again about three days later, GPT had replaced 97% of the sources it cited. A screenshot of “we showed up in ChatGPT” is a record of one moment, nothing more. That is why GEO behaves less like a one-off optimization project and more like continuous observation plus ongoing content work.

So where do you start

  1. Find out whether your brand appears in AI answers at all right now — how to check properly
  2. Work out which sources the engines read in your category — the engine playbook
  3. Apply what the already-recommended brands have in common — four patterns from the data

Every figure here comes from data we are still collecting, so it shifts a little over time. The current values always live on statistics.