What Is GEO in Plain English?

Picture the old library. You'd walk up to the reference desk, ask a question, and the librarian would walk you over to a shelf and hand you three books. You did the reading. That's Google. It hands you links and lets you pick.

Now picture a different librarian. This one has read everything in the building, and when you ask a question, she just tells you the answer out loud, in a couple of sentences, and maybe names the book she pulled it from. If your book isn't one of the two or three she mentions, you don't exist to the person asking. It doesn't matter how good your book is if it's sitting on a shelf nobody heard about in her answer.

That second librarian is what ChatGPT, Gemini, Claude, and Perplexity are doing every time someone types a question into them instead of Googling it. GEO, short for Generative Engine Optimization, is the work of making sure that when the librarian talks, she's talking about you.

A lot of people hear "GEO" and assume it's a rebrand, like when "webmasters" became "growth marketers." It isn't. The mechanics are genuinely different.

When Google ranks pages, it's mostly answering the question "which of these ten pages should I show first." When an AI engine answers a question, it's doing something closer to writing a mini essay on the fly, and it has to decide which two or three sources are worth pulling into that essay at all. Everyone else it read gets left out entirely, not just pushed to page two.

Researchers at Princeton, Georgia Tech, and IIT Delhi tested this directly. In their 2023 paper introducing the term "Generative Engine Optimization," they measured how different content changes affected how often a source got cited by AI generated answers. Adding statistics, quoting authoritative sources, and citing credible references all improved visibility, in some tests by up to 40 percent (arXiv 2311.09735, "GEO: Generative Engine Optimization"). The paper is public at arxiv.org/abs/2311.09735 if you want the technical breakdown of which content changes moved the needle by how much.

Semrush ran a much bigger, more recent study of the same shift from the search side: an analysis of over 10 million keywords found AI Overviews appeared on roughly 6.5 percent of tracked queries in January 2025, and had climbed to somewhere around 15 to 16 percent by late 2025 (Semrush, "AI Overviews Study"). That's not a niche behavior anymore. It's a fast-growing share of ordinary searches getting an AI-written answer instead of a list of links.

The practical upshot: writing that's built to rank on Google (broad keywords, long lists, lots of internal links) doesn't automatically get you quoted by an AI. Writing that's built to get quoted by an AI (clear direct answers, specific facts, plain language a model can lift and restate) doesn't automatically rank on Google either. You need both, and they pull in slightly different directions.

Most GEO articles reach for the same local-service examples: a plumber, a dentist, a roofer. Here's a different one. OMG worked with JamShare, a music sharing app, on exactly this problem. JamShare had done reasonably normal marketing work, some blog content, App Store optimization, the usual playbook. None of it was written for a machine that answers questions out loud. When we first ran JamShare's own product pages through a test prompt, the app's tagline described it as "social music, reimagined," which is the kind of line a person could read a dozen times and still not learn what the app actually does differently from just texting someone a Spotify link.

After running weekly AI visibility scans through OMG and fixing what came back (clearer descriptions of what the app actually does differently, FAQ content answering the comparison questions people actually ask, and technical cleanup so AI systems could parse the app's purpose correctly), JamShare rewrote that tagline. The rewrite: "JamShare turns a Spotify link into a link that opens in Apple Music, YouTube Music, or Tidal, whatever the recipient actually uses." Three months later, new signups started naming ChatGPT as their discovery channel. JamShare started seeing new users mention, unprompted, that they'd found the app through a conversation with an AI tool rather than a search or an App Store browse. That's a different acquisition channel than anything their prior SEO work had ever touched. It didn't replace their existing traffic. It ran alongside it.

Traditional SEO is largely a guessing game: you publish something and wait weeks to see if Google likes it. AI engines, especially the ones with live web access like Perplexity or ChatGPT's search mode, will tell you almost immediately if they've misunderstood your business, because you can just ask them.

Go type "what does [your business] do" into ChatGPT or Perplexity right now. Read what it says. It's probably wrong in some small way, maybe your pricing is off, maybe it's describing something you stopped offering two years ago, maybe it just doesn't mention you at all. That gap between what the AI says and what's actually true is the practical opening for GEO work. Your job, or your tool's job, is to close that gap by publishing the specific, structured, quotable content that gives the AI a better source to pull from next time.

Google has treated this shift as real enough to redesign its own results page around it. When it rolled out AI powered summaries at the top of search results, Google described the goal as helping people get a useful answer faster instead of clicking through a pile of links to piece one together themselves (Google, "Generative AI in Search: Let Google do the searching for you"). OpenAI built the same behavior directly into ChatGPT, adding real time web search so it can pull in current sources and cite them in its answers (OpenAI, "Introducing ChatGPT search"). Two of the biggest players in search and AI are building toward the same thing, at the same time.

If you strip away the jargon, GEO comes down to a handful of unglamorous habits.

Answer the exact question, in the first sentence. AI models tend to pull the most direct, self contained answer they find. Open with three paragraphs of scene-setting before you get to the actual point, and you've made it harder to be quoted.

Be specific instead of impressive sounding. "We use licensed technicians with an average of 12 years of experience" gets quoted. "We're passionate about excellence" doesn't, because there's nothing in it an AI can actually restate as a fact.

Structure your site so machines can parse it, not just read it. Schema markup (the behind the scenes code that tells a computer "this is a business, here's its hours, here's its address") acts like labeled folders instead of a messy desk. AI crawlers find what they need faster, and faster found tends to mean more likely to be used.

Show up consistently, not just once. One great blog post rarely flips an AI model's understanding of you. A steady drip of updated FAQs, fresh pages, and consistent facts across your site is what actually rewires how the model describes you over time, which is exactly why OMG treats this as a weekly job, not a one-time project.

None of this replaces your website or your ad spend. It's a new layer sitting on top of the old one, because a growing share of your future customers are going to meet your business for the first time inside a chat window, not a search results page.

It's worth being honest about the limits here, because overselling this stuff wastes your time. AI answers aren't stable the way a Google ranking is. A January 2026 study from SparkToro's Rand Fishkin and Patrick O'Donnell of Gumshoe.ai ran 2,961 prompt tests across ChatGPT, Claude, and Google AI with 600 volunteers across 12 categories, and found that asking an AI to recommend brands in a category 100 times gives you less than a 1-in-100 chance of seeing the same list twice (SparkToro, "New Research: AIs Are Highly Inconsistent When Recommending Brands or Products"). Ranking position in AI answers is a lot less stable than it is in traditional search.

On top of that, the exact factors that get you cited are opaque, they change without notice, and there's no guarantee that getting mentioned once means you'll get mentioned again next week. Different AI models also weigh different signals: a fix that gets you cited more often in ChatGPT may do nothing at all in Gemini, because the two systems aren't reading and weighting the web the same way. Some questions also just don't have a single "winner" the way a search results page implies one exists, the AI returns a short list of reasonable options, and no amount of GEO work turns a list question into a single-answer question.

What GEO actually gives you is meaningfully better odds of being one of the businesses named when your name could plausibly be named. It does not guarantee it, and anyone selling it to you as a guarantee is selling you something else. GEO work shifts your odds meaningfully. It doesn't buy you a permanent, guaranteed slot.