Generative Engine Optimization (GEO): Why SEO Is Becoming AI Engine Optimization

Generative engine optimization (GEO) is the practice of structuring content so that AI systems such as ChatGPT, Google AI Overviews, Gemini and Perplexity cite it when they generate an answer. Traditional SEO earns a position on a results page; GEO earns a citation inside the answer itself, so the page has to be specific, sourced and quotable enough for a model to lift a passage from it. The same discipline goes by AI engine optimization, answer engine optimization (AEO) and LLM SEO, and it is spelt “optimisation” outside the US. This guide uses the spelling most of the research and most searchers use.

Why Is the Organic Click Disappearing?

The click is disappearing because AI answers now sit above the results, and most people stop there. For twenty years, SEO was straightforward: research keywords, publish content, earn backlinks, watch traffic climb. That playbook isn’t dead, but the game it was built for has changed, and most marketing teams haven’t caught up.

The numbers are stark. Seer Interactive tracked 3,119 informational queries across 42 organisations and found that organic CTR on queries with AI Overviews fell from 1.76% in June 2024 to 0.61% in September 2025, a decline Seer puts at 61% (Seer Interactive, Sep 2025). An Ahrefs study of 300,000 keywords corroborates this: position-one organic CTR was 58% lower when an AI Overview appeared, comparing December 2025 with December 2023 (Ahrefs, Feb 2026).

Seer’s April 2026 follow-up, covering 53 brands and 5.47 million queries, adds a twist. Organic CTR on AI Overview queries bottomed at 1.3% in December 2025 and climbed back to 2.4% by February 2026 (Seer Interactive, Apr 2026). That is a recovery, not a restoration. Pages cited in the AI Overview earned 120% more clicks per impression than uncited pages on the same results page, and still 38% fewer than pages on queries with no AI Overview at all.

Zero-click is now the majority case. SparkToro’s analysis of Similarweb clickstream data found 68.01% of US Google searches ended without a click in the first four months of 2026, up from 60.45% in 2024 (SparkToro, Jun 2026). Google’s AI Mode passed 1 billion monthly active users by July 2026 (Alphabet Q2 2026 earnings, Jul 2026). ChatGPT reached 900 million weekly active users in February 2026 (TechCrunch, Feb 2026), and OpenAI said in July that its models reach more than one billion active users across its products (BNN Bloomberg, Jul 2026).

In Southeast Asia, where I run 2Stallions across four markets, we’re seeing this hit client campaigns in real time. If your growth model depends on organic clicks, understanding generative engine optimization isn’t optional anymore. So what does the shift actually look like?

TL;DR: Organic CTR on queries with AI Overviews fell 61% between mid-2024 and late 2025, recovered to 2.4% by February 2026, and remains well below the pre-AI baseline (Seer Interactive, Apr 2026). 68% of US Google searches now end without a click (SparkToro, Jun 2026). Google’s own May 2026 guidance says GEO is still SEO and the “hacks” are unnecessary. This article covers what generative engine optimization is, where Google is right and where its guidance stops, a 5-step transition framework, and the mistakes most teams make when adapting.

What Is Generative Engine Optimization?

Generative engine optimization (GEO) is the practice of structuring content so AI systems cite it as a source when generating answers. Where traditional SEO targets ranking positions on a search results page, GEO targets citations inside AI-generated responses from tools like ChatGPT, Perplexity, and Google AI Overviews.

Citation capsule

Generative engine optimization (GEO) means structuring content so AI systems cite it when generating answers, rather than only ranking it on a results page. The term was formalised by researchers at Princeton, Georgia Tech, the Allen Institute for AI and IIT Delhi, who found that adding sourced statistics, expert quotes and clear definitions raised a source’s visibility in generative engine responses by up to 40%. (Aggarwal et al., KDD 2024, 2024)

The term was formalised in a 2024 study by researchers at Princeton, Georgia Tech, the Allen Institute for AI, and IIT Delhi, presented at KDD 2024 (Aggarwal et al., 2024). Their findings showed that specific content optimisations, including statistics with sources, expert quotes, and clear definitions, boosted visibility in generative engine responses by up to 40%.

The field is moving fast. A September 2025 study found that AI search systems show systematic bias toward earned media over brand-owned content (Chen et al., Sep 2025). A month later, researchers at CMU introduced AutoGEO, a framework for automatically learning what generative search engines prefer to cite (Wu et al., Oct 2025). And in May 2026 Google published its own guidance on the subject, covered in the next section. This is not a temporary trend.

You’ll also hear this called AI engine optimization, answer engine optimization (AEO), AI SEO, or LLM SEO. The labels vary but the principle is the same: your content needs to be structured for extraction, not just discovery. Is your content built to be quoted by a machine, or just found by one?

What Does Google’s Own Guidance Say About GEO?

Google says GEO is still SEO, and that most of what gets sold as GEO is unnecessary. On 15 May 2026, Google Search Central published its first official guide to appearing in AI Overviews and AI Mode (Google Search Central, May 2026). Its position is blunt: “our generative AI features on Google Search are rooted in our core Search ranking and quality systems,” and “optimizing for generative AI search is optimizing for the search experience, and thus still SEO” (Google, 2026).

Citation capsule

Google’s official guidance, published 15 May 2026, states that AI Overviews and AI Mode are “rooted in our core Search ranking and quality systems” and that optimising for them “is optimizing for the search experience, and thus still SEO.” It tells site owners they do not need llms.txt files, content “chunking”, AI-specific rewrites, inauthentic mentions or extra markup to appear in Google’s generative features, and to focus instead on unique, non-commodity content and foundational SEO. (Google Search Central, 2026)

The guide names the tactics it considers a waste of effort: llms.txt files, “chunking” content into fragments, rewriting pages specifically for AI, chasing inauthentic mentions, and over-investing in structured data. “You don’t need to create new machine readable files, AI text files, markup, or Markdown to appear in Google Search (including its generative AI capabilities), as Google Search itself doesn’t use them.” What it asks for instead is “non-commodity” content: unique expert or experienced takes that go beyond common knowledge.

I agree with Google on Google. The framework later in this article contains no llms.txt step and no AI-only rewrite, and the elements it does ask for (direct answers, sourced numbers, clear definitions, topical depth) are the foundational work Google is describing. Two things the guidance does not settle. First, it covers Google Search only. ChatGPT, Perplexity and Gemini retrieve differently, and Google’s document says nothing about them. Second, it is silent on measurement. Google did move on that separately: Search Console gained generative AI performance reports on 3 June 2026, showing impressions and pages surfaced in AI Overviews and AI Mode, and rolled them out to every site worldwide on 31 August 2026 (Google Search Central, Jun 2026). Those reports show impressions, not clicks or citations, so they are a start rather than a full picture.

Read as a whole, the guidance is a warning against vendors selling GEO as a bag of tricks. It is not an argument that AI search changes nothing for your content. Would the average page on your site pass Google’s “non-commodity” test?

How AI in Marketing Is Changing

AI Overviews peaked at 24.6% of Google queries in July 2025, settled to roughly 16% by November, then rebounded sharply: BrightEdge’s industry tracker now shows them on ~48% of tracked queries as of early 2026, a 58% year-on-year increase (BrightEdge via Search Engine Land, 2026). AI Mode alone serves more than a billion people a month. That alone would be enough to force a rethink. But the shift in AI in marketing goes beyond one channel changing shape; the whole retrieval model has changed.

Citation capsule

Being cited in an AI Overview is the new ranking signal. Seer Interactive’s analysis of 53 brands, 5.47 million queries and 2.43 billion organic impressions found that pages cited in an AI Overview earned 120% more organic clicks per impression than uncited pages on the same results page, yet still 38% fewer than pages on queries with no AI Overview. Organic CTR on AI Overview queries recovered from a 1.3% floor in December 2025 to 2.4% in February 2026. (Seer Interactive, Apr 2026)

Citation replaces ranking. In traditional search, you competed for position one. In AI-generated responses, the model pulls from multiple sources and attributes them. Your goal shifts from outranking competitors on a results page to being the reference an AI model trusts enough to cite. Seer’s 2025 study found that brands cited in AI Overviews earn 35% more organic clicks than non-cited brands on the same query (Seer Interactive, Sep 2025); its 2026 update put the per-impression gap at 120% (Seer Interactive, Apr 2026).

How deeply you cover a subject now matters more than how many times you mention a keyword. Google’s AI Overviews and ChatGPT both assess source credibility before citing. Publishing one article on a topic isn’t enough. You need depth across related topics, which is why pillar pages linking to detailed articles are becoming essential architecture for AI visibility.

At 2Stallions, we started tracking AI citations alongside traditional rankings in late 2024. We quickly realised that ChatGPT, Perplexity, Gemini, and Google AI Overviews all retrieve differently. Some pull from web crawls. Some use real-time search. Some weight recent content more heavily. A page cited consistently by Perplexity may not appear in ChatGPT at all. Treating “AI visibility” as a single channel makes as little sense as treating “social media” as one platform.

When someone asks “what is generative engine optimization?” and your content opens with three paragraphs of preamble, the AI skips you. It cites the page that leads with a clear definition. Front-loading value has moved from best practice to requirement.

What We Changed at 2Stallions

When we saw the CTR data in mid-2024, we didn’t wait for a playbook. We started testing.

The first change was measurement. We added AI citation tracking to our internal workflow as part of our Search Everywhere Optimisation (SEO) service. For key topics, we search across ChatGPT, Perplexity, and Google AI Overviews monthly to check whether content appears. The AI Visibility Audit tool I built as a prototype started as a way to test the concept and became something we offer to clients during onboarding. That process, manual and imperfect as it is, catches gaps that traditional rank tracking misses entirely.

Then came content restructuring. We rewrote service pages and key blog posts to lead with direct answers, add structured data, and include the citable elements the Princeton GEO study identified: statistics with sources, expert quotes, and clear definitions (Aggarwal et al., 2024). What surprised us was how quickly the changes showed up. Not in rankings, those moved slowly, but in whether AI tools started referencing the restructured pages.

Creating AI Content vs Optimising for AI Search

There’s a confusion I hear regularly from marketing teams: they conflate using AI to create content with structuring content so AI cites it. These are different disciplines, and treating them as interchangeable is risky.

Using AI to generate blog posts, ad copy, or social content is a production question. It’s about efficiency. Generative engine optimization is a distribution question. It’s about whether your content appears when someone asks ChatGPT or Perplexity a question in your domain.

You can write entirely with AI and still get zero AI citations if the content lacks structure, sources, and depth. Conversely, you can write every word by hand and dominate AI-generated answers if you structure content around clear questions, include verifiable data, and build topical authority. The two skills complement each other, but they aren’t the same skill. Which one is your team actually investing in?

How Do You Move From SEO to Generative Engine Optimization?

Five steps: audit, map to questions, build citable structure, earn entity authority, and measure. This is the framework I use with clients and within 2Stallions. None of it conflicts with Google’s May 2026 guidance; steps two and three are the “foundational SEO” Google describes, and steps one and five cover the measurement its guide leaves out.

1. Audit your AI visibility first. Search your key topics in ChatGPT, Perplexity, and Google AI Overviews. Note whether you’re cited, which competitors appear instead, and which queries return AI-generated answers at all. Try the AI Visibility Audit to benchmark where you stand, and open the generative AI report in Search Console for Google’s side of the picture. This gives you a baseline that traditional rank tracking can’t provide.

2. Map content to questions, not just keywords. AI models are question-answering systems. Reframe your content calendar around the specific questions your audience asks, and answer them directly in the opening paragraph of each section. Content structured around clear questions and direct answers performs significantly better in generative responses (Aggarwal et al., 2024).

3. Build structured, citable content. Write each article as a reference document an AI could extract a clean, accurate paragraph from. Tables, numbered lists, clear definitions, and cited statistics all increase your citability. This article uses every one of those elements intentionally. Google’s caution applies here too: structured data helps machines read a page, but it does not substitute for content worth citing.

4. Invest in entity authority. Backlinks still matter, but so do brand mentions, expert quotes, presence across multiple credible platforms, and consistent topical coverage. The more an AI model encounters your brand in authoritative contexts during training and retrieval, the more likely it is to cite you. Earn those mentions; Google’s guide specifically warns against buying or faking them.

5. Track AI metrics alongside traditional ones. Organic rankings and traffic remain useful, but add AI citation monitoring to your reporting, ideally inside a decision-first marketing dashboard. Search Console now reports impressions in AI Overviews and AI Mode; tools like Otterly.AI, Profound, and Ahrefs’ AI tracking cover the other engines. The data will be imperfect. Start measuring anyway, because by the time perfect tools exist, the early movers will already have adapted.

ChatGPT drives 87.4% of all AI referral traffic across major industries (Conductor, Nov 2025). SE Ranking’s study of 101,574 websites puts ChatGPT at roughly 80% of AI referrals, with Gemini and Perplexity growing fastest, and all AI platforms combined at about 0.24% of global web traffic in January 2026 (SE Ranking, Mar 2026). That last number is worth sitting with: AI referrals are still small in absolute terms, which is exactly why the citation, not the click, is the thing to measure. Where your audience searches determines which platform you optimise for first.

What Most Teams Get Wrong

The most common mistake is treating generative engine optimization as a tactic you bolt onto your existing SEO workflow. Running the same keyword-stuffed playbook and hoping AI models pick it up doesn’t work. AI models are good at identifying thin, derivative content and skipping it entirely, which is the same point Google makes when it asks for “non-commodity” content.

The second mistake is underestimating the scale. AI Overview penetration peaked at 24.6% of Google queries in July 2025, settled to roughly 16% by November, and has since rebounded to ~48% of tracked queries in early 2026 (BrightEdge via Search Engine Land, 2026). Google desktop searches per US user fell nearly 20% year-over-year (Datos/SparkToro, Q4 2025). Factor in ChatGPT with 900 million weekly active users, AI Mode past a billion monthly users, plus Perplexity, Gemini, and AI-integrated browsers, and the share of queries where AI mediates the answer is substantially higher. Are your quarterly reports even measuring this?

The third mistake is assuming this shift doesn’t apply to your market. In Southeast Asia, over US$55 billion has been committed to AI infrastructure across Singapore, Malaysia, Indonesia, and Thailand, with investment compounding at 25% annually (WEF, Nov 2025). Singapore leads the region with 48% of businesses having adopted AI. Thailand is at 32%, Indonesia at 28%, Malaysia at 27%, and Vietnam at 18% (AWS/Strand Partners, 2025).

If you run digital marketing in this region, your audience is already using AI search tools daily. You can’t game AI visibility the way you once gamed search rankings. There’s no equivalent of a title tag hack, and Google has now said so in writing. What you can do is build content that is clearly authoritative, well-structured, and genuinely useful. That has always been the promise of good SEO. The difference now is that the “rankings” are citations inside AI-generated responses, and the bar for quality is higher than it’s ever been.

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I run a digital marketing agency that’s adapting to this shift across four Southeast Asian markets. If your team needs to understand generative engine optimization, let’s talk.

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Frequently Asked Questions

What is GEO in SEO?

GEO stands for generative engine optimization: the work of making content citable by AI systems such as ChatGPT, Google AI Overviews, AI Mode, Gemini and Perplexity. "GEO SEO" is the same thing described from the search side, because the content practices that earn AI citations (direct answers, sourced figures, clear definitions, topical depth) are the same practices that rank well in conventional search. Google's May 2026 guidance treats GEO as part of SEO rather than a separate discipline.

Is GEO the same as AI SEO?

In practice, yes. GEO, AI SEO, LLM SEO and AI engine optimization all describe optimising content so AI answer engines cite it. The differences are mostly which vendor coined the label. The one distinction worth keeping is between GEO and answer engine optimization (AEO): AEO originally covered featured snippets and voice assistants, while GEO is specific to generative AI answers. Today the two overlap almost completely.

What is AI engine optimization (AEO)?

AEO usually stands for answer engine optimization, and some teams expand it as AI engine optimization; both describe structuring content so it gets cited by AI tools like ChatGPT, Perplexity, and Google AI Overviews when they generate answers. Unlike traditional SEO, which targets ranking positions on a search results page, AEO targets citations inside AI-generated responses. It involves clear definitions, sourced statistics, structured formatting, and building the topical authority AI models use to decide which sources to reference.

What is generative engine optimization?

Generative engine optimization (GEO) is a methodology for improving content visibility in AI-generated search responses. Formalised by researchers at Princeton, Georgia Tech, the Allen Institute for AI and IIT Delhi in a 2024 KDD paper, GEO includes adding citations, statistics, and structured answers to content. Their research found these methods boosted source visibility by up to 40% in generative engine responses across multiple query types. Outside the US it is often spelt generative engine optimisation.

How do you get cited by ChatGPT?

Publish pages that answer a specific question directly in the first paragraph, back the answer with a named source and a date, and keep the page crawlable so OpenAI's crawler can read it. ChatGPT's browsing retrieves live web pages, so recency and clarity matter: a self-contained, quotable paragraph with a statistic and a source is far likelier to be lifted than a general overview. Then check monthly whether your pages appear for your key questions, note which competitors are cited instead, and close the gap on those topics.

Does GEO replace SEO?

No. Google's May 2026 guidance states that its AI features are rooted in the same core ranking and quality systems as ordinary search, so the foundations still decide who gets cited. Backlinks, content quality, and technical SEO all still matter. What has changed is where people find answers: with AI Mode past a billion monthly users and 68% of US Google searches ending without a click, optimising only for the classic results page misses a growing share of your audience. GEO is SEO extended to cover citation as well as ranking.

How is AI used in digital marketing?

AI in marketing spans content creation, campaign automation, and audience targeting. But the most significant strategic shift is the rise of AI search: ChatGPT, Perplexity, and Google AI Overviews are pulling users away from traditional organic results. ChatGPT alone drives roughly 80% to 87% of all AI referral traffic depending on the study. Optimising for AI citation, not just ranking, is becoming a core marketing discipline.

How do you optimise content for AI search engines?

Lead each section with a direct answer to a specific question. Include cited statistics and expert sources. Structure content with clear headings, tables, and numbered lists that AI models can extract cleanly. Build topical depth across related articles rather than publishing standalone pieces. Then track your visibility across ChatGPT, Perplexity, and Google AI Overviews regularly, not just traditional rankings.

What's the difference between SEO and GEO?

SEO optimises content for search engine ranking positions, targeting clicks from a traditional results page. GEO optimises content for citation inside AI-generated responses from tools like ChatGPT, Perplexity, and Google AI Overviews. SEO focuses on keywords and backlinks. GEO focuses on citable structure, source credibility, and topical depth. Both matter, and Google's position is that the second is an extension of the first rather than a replacement for it.

How do you track AI citations?

Search your key topics across ChatGPT, Perplexity, and Google AI Overviews monthly and record whether your content is cited. Google Search Console now includes a generative AI performance report showing impressions and pages surfaced in AI Overviews and AI Mode, available to all sites since 31 August 2026. Tools like Otterly.AI and Profound cover the other engines. The process is still imperfect, but measuring imperfectly beats not measuring at all. Start with your top 10-20 topics and expand from there.

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