GEO vs SEO: What Changes When AI Answers the Question

For twenty-five years, winning search meant one thing: rank on the first page of Google, earn a top result, capture the click. That game has not vanished. A second one now sits on top of it, and most people have not noticed the rules changed.

When someone asks ChatGPT, Gemini, Perplexity, or Google’s own AI Overviews about you or your category, they no longer get ten blue links to weigh. They get one synthesized answer. No scrolling, no comparison, often no click at all. If you are not in that answer, you effectively do not exist for that decision. And if the answer is wrong, the damage is quiet and immediate, because you never see what the machine said.

In my work advising executives and public figures, this is the most underestimated shift in how reputations are made and lost today. Let me lay out the difference between traditional SEO and the newer disciplines built for AI answers, and why I no longer treat them as separate problems.

The short version

The cleanest way I can put it: SEO earns a ranking. GEO earns a place inside the answer.

Search engine optimization is the long-established practice of getting a web page to rank highly on a results page so a human clicks through. Generative engine optimization, or GEO, is about influencing how generative AI models describe a person, brand, or topic, by shaping the sources and signals those models draw on. The term comes from a 2024 academic paper, accepted to the KDD conference, that formally defined generative engines as systems that gather and summarize information to answer a query, and introduced GEO as the discipline for improving visibility inside those generated responses (Aggarwal et al.).

A close cousin, answer engine optimization, or AEO, focuses on structuring information so engines select you as the direct answer in features like AI Overviews, featured snippets, and voice results. People use GEO and AEO loosely and sometimes interchangeably. The distinction that matters is not the acronym. It is the shift from competing for a click to competing for a sentence.

Why this is not a niche concern anymore

The scale here is easy to miss until you see the numbers. Google reported that its AI Overviews reached two billion monthly users by mid-2025, up from 1.5 billion only months earlier (TechCrunch). This is no longer an experiment bolted onto search. It is the default experience for an enormous share of the people who look you up.

And these answers change behavior. A Pew Research Center analysis of the March 2025 browsing activity of 900 U.S. adults found that users who saw an AI summary clicked a traditional search link in just 8 percent of visits, compared with 15 percent for users who did not see one (Pew Research Center). Clicks on the sources cited inside the summary were rarer still, at roughly 1 percent of visits. People read the answer and move on.

That is the heart of why GEO matters. The reader is forming a judgment about you from a paragraph they will never trace back to a source. In the same Pew analysis, the typical AI summary ran about 67 words. Sixty-seven words, often unsourced in the reader’s eyes, now stand in for the page of results they used to scan. If you have ever wondered what ChatGPT says about you, this is why the question is not vanity. It is the new first impression.

What actually changes

A few things shift in ways that matter for anyone whose reputation has value.

Visibility becomes binary. On a results page, ranking sixth still earns some traffic. In an AI answer, you are either named or you are absent. There is no honorable mention.

Citations replace clicks as the prize. Models lean on sources they treat as authoritative. The Pew analysis found Wikipedia, YouTube, and Reddit were the most frequently cited sources across both AI summaries and standard results, and that government sites appeared in AI summaries at three times the rate of standard results (Pew Research Center). Becoming part of the authoritative record a model reads from is the new front line.

Question-shaped queries trigger answers. Pew found that 60 percent of searches beginning with words like who, what, when, or why produced an AI summary, and that longer queries did so far more often than short ones (Pew Research Center). The exact moment someone asks a question about you is the moment a machine is most likely to answer for you.

Accuracy becomes the whole game. A model that confidently repeats an outdated lawsuit, a stale headline, or a competitor’s framing does real harm, and it does it without you ever seeing the exchange. There is no comments section to correct, no editor to email. You cannot edit the model directly. You can, however, strongly influence what it says by changing the record it reads from.

Does GEO replace SEO? No. It sits on top of it.

This is the part most coverage gets wrong, and the part Google itself has been blunt about. In its own guidance, Google states that the same fundamentals that have always supported good search performance also support visibility in its AI experiences, and that there are no separate requirements, special files, or unique schema needed to appear in AI Overviews or AI Mode (Google Search Central).

In plain terms: the strong, accurate, genuinely useful content that ranks well in traditional search is largely the same content these models trust enough to cite. SEO builds the foundation. GEO and AEO determine whether that foundation gets quoted in the answer. Treating them as rival strategies is a mistake. The two reinforce each other.

The research backs the upside of doing this deliberately. The GEO study tested optimization approaches against a large benchmark of queries spanning multiple domains and found that the right methods could lift a source’s visibility in generated answers by as much as 40 percent. The authors stress that what works varies by domain (Aggarwal et al.). That last point matters in our world. The signals that earn citation for a consumer brand are not the same ones that earn it for a public figure facing a sensitive narrative.

What this means in practice

I will not pretend there is a tidy checklist that solves this. If there were, it would already be commoditized and worthless. What I can tell you is how we think about it.

The goal is to be the most accurate, authoritative, and consistently corroborated voice on the subjects that matter to you, across the surfaces these models actually read. That means a record that is current and clean, inaccuracies addressed wherever they live, and steady monitoring of what the assistants are saying, because the answers drift and the models update without warning. The reactive version of this work, waiting until a wrong answer surfaces in a board meeting or a press call, costs far more than the proactive one.

For most of our clients, the real work is not chasing a ranking or a citation in isolation. It is treating traditional search and AI answers as a single surface and managing both at once. That is precisely what our Search and AI Visibility practice exists to do, and it sits alongside the broader discipline of online reputation management, because an inaccurate AI answer is, in the end, a reputation problem with a new delivery mechanism.

The first impression about you is now written by a machine. The only real question is whether you had a hand in writing it.

If you want to know where you stand today, the honest first step costs nothing: open an assistant and ask it about yourself the way a stranger would. What you find there is already shaping decisions about you. The work is making sure it is right.

Sources

• Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., and Deshpande, A. “GEO: Generative Engine Optimization.” arXiv (KDD 2024). https://arxiv.org/abs/2311.09735
• Chapekis, A., and Lieb, A. “Google users are less likely to click on links when an AI summary appears in the results.” Pew Research Center, July 22, 2025. https://www.pewresearch.org/short-reads/2025/07/22/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results/
• Wiggers, K. “Google’s AI Overviews have 2B monthly users, AI Mode 100M in the US and India.” TechCrunch, July 23, 2025. https://techcrunch.com/2025/07/23/googles-ai-overviews-have-2b-monthly-users-ai-mode-100m-in-the-us-and-india/
• Google Search Central. “AI Features and Your Website.” Google for Developers. https://developers.google.com/search/docs/appearance/ai-features