Last updated: 16 July 2026
AI visibility is how often AI answer engines mention, cite, and recommend your brand when buyers ask them questions. It's the AI-era version of ranking. Instead of ten blue links, the buyer gets one synthesized answer. If your brand isn't inside that answer, you don't exist for that buyer.
TL;DR: AI visibility measures whether AI engines like ChatGPT, Perplexity, and Google AI Overviews put your brand in front of buyers. It has three layers: getting surfaced (mentioned), getting cited (named as a source), and getting recommended (landing on the "best X" shortlist). GET SCORED rolls those three into one 0–100 SCR score across five engines, so you can see where you stand and track it over time.
Traditional search sends people to your site to decide for themselves. AI search decides first, then hands the buyer a short answer. Your brand is either in that answer or it isn't. That's the shift AI visibility tracks, and it's why "are we ranking?" is turning into "are we in the answer?"
They're mostly different names for the same job: getting your brand into AI-generated answers. GEO, AEO, and LLMO each emphasize a slightly different angle, and "AI SEO" is the loose umbrella term. The practical work overlaps heavily. Don't get stuck on the acronym; focus on whether engines surface, cite, and recommend you.
| Term | Stands for | What it emphasizes | How it relates |
|---|---|---|---|
| GEO | Generative Engine Optimization | Getting cited inside generative answers | The most common label. Closest to what we do day to day. |
| AEO | Answer Engine Optimization | Being the source an answer engine pulls from | Overlaps with GEO. Leans toward question-and-answer intent. |
| LLMO | Large Language Model Optimization | Showing up in the model's responses, including training data | A model-centric framing of the same goal. |
| AI SEO | AI Search Optimization | Broad umbrella covering all of the above | Useful as a catch-all. Too vague to plan against on its own. |
Our take: the acronym doesn't matter, the outcome does. Whatever you call it, you want to know three things. Do engines mention you? Do they name you as a source? Do they put you on the shortlist? That's what the SCR framework measures, and it's engine-agnostic.
You measure AI visibility by asking real buyer questions across the engines your market uses, then scoring what comes back. GET SCORED uses the SCR framework: Surfaced, Cited, and Recommended. Each answer is scored on those three signals, weighted, and averaged across five engines into a single 0–100 SCR score.
Here's how the SCR score works:
The formula is SCR = S×0.30 + C×0.30 + R×0.40, averaged across ChatGPT, Perplexity, Gemini, Google AI Overviews, and Copilot. Recommended carries the most weight because that's where buying decisions actually get made. A brand can be surfaced everywhere and still lose if it never makes the shortlist.
Alongside the score, we track Share of Voice: out of all the brands an engine names for a given query, how big a slice is yours? Share of Voice tells you where you stand against the field, not just against yourself. For the full method, including the query set and how re-scoring works, see how we measure.
Because buyers have already moved. According to G2 (2026), half of B2B software buyers now start their research with AI chatbots. When the first stop is an AI answer instead of a search results page, being absent from that answer means being cut from the shortlist before a human ever sees your name.
This isn't a far-off trend. It's a live change in how deals begin. If a buyer asks an engine "what's the best tool for X" and gets three names back, those three brands just made the consideration set. Everyone else has to fight to get considered at all, usually without knowing they were skipped.
The direction is set to continue. Gartner forecasts that by 2026, search engine volume will drop 25%, with users turning to AI chatbots and virtual agents. That's a forecast, and it's about search volume, not your organic traffic specifically. Still, the signal is clear: attention is moving from search results to synthesized answers.
SEO gets you ranked on a results page so a human can click through and choose. AI visibility gets you into the answer itself, where the engine has already narrowed the choices. SEO optimizes for position in a list. AI visibility optimizes for inclusion in a recommendation. Different game, different scoreboard.
Bottom line: keep doing solid SEO. It still matters. But treat AI visibility as its own discipline with its own scoreboard, because the two no longer measure the same thing.
Close enough to use interchangeably in most conversations. GEO (Generative Engine Optimization) is the most common name for the work. "AI visibility" is the outcome that work produces: how often engines surface, cite, and recommend you. We measure the outcome with the SCR score.
We track five: ChatGPT, Perplexity, Gemini, Google AI Overviews, and Copilot. They cover where most B2B buyers actually ask their questions. The right emphasis depends on your market, which is one of the first things we check.
It can be measured. You run a fixed set of real buyer queries across the engines, score each answer on Surfaced, Cited, and Recommended, and roll it into one 0–100 SCR score plus a Share of Voice figure. Same queries, same method, repeatable over time. The score is the product.
It varies by engine and by how deeply the work reaches. In our experience, Perplexity tends to reflect changes within a few days, ChatGPT within a week or two, and Google AI Overviews can take up to a couple of months. Measuring first is how you tell whether it's moving.
Want to know your current SCR score and where you sit against the field? Book a 15-minute call