Generative engine optimization (GEO) is the practice of positioning your brand and content so AI platforms such as Google's AI Overviews, ChatGPT and Perplexity cite, recommend or mention you in their answers. It borrows most of its methods from SEO, and Google's own guidance says that, from its perspective, optimizing for generative AI search "is optimizing for the search experience, and thus still SEO." As of 4 October 2026, GEO is a useful label for a measurement goal, not a separate rulebook.
Key Takeaways
- GEO aims at being cited or mentioned inside a generated answer, not at ranking a blue link.
- The term comes from a 2023 research paper; it later became an industry label, used interchangeably with AEO, LLMO and AIO by many practitioners.
- Google's guide says AEO and GEO are still SEO, and that llms.txt, content "chunking" and special schema are not needed for its generative features.
- Evidence for specific GEO tactics is thin and often vendor-reported. Be careful with any number promising a visibility lift.
- What does hold up: clear, distinctive content, strong entity signals, crawlable pages, honest third-party mentions and measurement that records the date and model.
- Anyone selling guaranteed AI rankings is selling something you cannot verify.
GEO: the definition
GEO is the discipline of improving how often, and how favourably, generative AI systems cite or mention a brand in their answers. Search Engine Land puts it as positioning your brand and content so AI platforms "cite, recommend, or mention you when users search for answers" (Search Engine Land). Semrush's version is "optimizing your presence and content to appear in responses generated by AI-powered search systems" (Semrush).
Notice what both definitions leave out: they do not say what the tactics are. That is deliberate and a little revealing. The goal is clear; the method is still being argued about.
Where the term comes from
The phrase was introduced in an academic paper titled "GEO: Generative Engine Optimization" by Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit and colleagues, accepted to KDD 2024. The authors proposed it as a paradigm to help creators improve visibility in generative engine responses, built a benchmark called GEO-bench, and reported that some strategies could "boost visibility by up to 40%" while noting that effectiveness varied by domain (arXiv:2311.09735).
That "up to 40%" is a result from the authors' experimental setup. It is not a promise for your site, and I would not repeat it in a client proposal without the qualifier. Semrush's guide repeats the finding that pages with quotes and statistics had 30-40% higher visibility in AI responses; that appears to rest on the same line of research, so treat it as one study, not settled law.
The "is GEO real" debate
Wikipedia's entry notes that as of early 2026 there was no consensus definition separating GEO from AEO, LLMO and AIO, and that the terms "are frequently used interchangeably." It also cites Forrester analyst Nikhil Lai arguing these approaches are "significantly, but not fundamentally, different from SEO" (Wikipedia).
Then Google weighed in. Its guide to optimizing for generative AI features, last updated 10 July 2026 per the page, says: "From Google Search's perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO." It lists tactics it says you can skip: llms.txt files, content chunking, special keyword variations and special structured data for these features (Google Search Central). Search Engine Journal reported the guide's original publication on 15 May 2026 (Search Engine Journal).
My position: Google is right about Google, and GEO is still useful for the rest. ChatGPT, Perplexity, Claude and Gemini each retrieve differently, and Google's statement covers only Google Search. The label GEO earns its place when you are tracking brand presence across several engines.
Glossary: GEO terms
| Term | Definition |
|---|---|
| Generative engine | An AI system that writes an answer from retrieved or learned information, such as an AI Overview or a chatbot with search. |
| GEO | Optimizing for citations and mentions inside generative answers. |
| AEO | Optimizing content to be selected as the answer; see the AEO definition. |
| LLMO / AIO | Other labels for the same broad idea, used inconsistently. |
| Citation | A linked source inside an AI answer. |
| Mention | The brand appearing in answer text, linked or not. |
| Share of voice | The share of tracked prompts where your brand appears versus competitors. |
| Entity | A clearly identified thing, such as a brand or person, that systems can recognize consistently. |
GEO vs SEO vs AEO
GEO targets inclusion in generated answers; SEO targets ranking and clicks from search results; AEO targets being chosen as the direct answer. The boundaries blur, and I use them mainly to decide what to measure.
| SEO | AEO | GEO | |
|---|---|---|---|
| Goal | Rank and earn clicks | Be the answer extracted | Be cited or mentioned in generated responses |
| Typical surfaces | Google, Bing results | Snippets, answer boxes, AI answers | ChatGPT, Perplexity, AI Overviews, Claude, Gemini |
| Metrics | Rankings, traffic, conversions | Answer inclusion, snippet wins | Citations, mentions, share of voice |
| Works with | Crawling, links, content | Structure, direct answers | Entities, authority, third-party mentions |
Conductor describes AEO and GEO as related but distinct, with GEO focused on generative systems broadly and AEO on answer engines specifically (Conductor). Others, including Contently, flip the scope: it calls GEO the broader strategy for how engines represent a brand and AEO the narrower answer-box work (Contently). Two reputable sources, opposite hierarchy. That is why I tell clients to define terms in writing at the start of a project.
What GEO tactics actually involve
1. Clarity and extractability
Write each section so it makes sense on its own: direct answer first, then detail. Tables with clear row labels help; I show how in comparison tables for AI search.
2. Entity clarity
Make sure your brand, product and author names are described the same way everywhere: your site, profiles, directories and press. Consistency makes it easier for systems to connect mentions.
3. Distinctive substance
Google's guide emphasizes non-commodity content. If your page repeats what ten others say, a generated answer has no reason to credit you. Original data, first-hand process and specific examples are what I add whenever I can.
4. Evidence
Include named sources, dates and numbers you can trace. This helps readers, and the GEO paper's quotes-and-statistics finding points the same way, with the caveat above.
5. Third-party presence
Semrush lists credible brand mentions and UGC platforms among its tactics. Google's guide, by contrast, says artificially seeking product mentions provides minimal value, per Search Engine Journal's summary. Earn mentions by being worth mentioning.
6. Crawlability
Server-rendered, accessible HTML is the base layer. If a crawler cannot read the page, nothing else matters.
What does not have good evidence
- Guarantees. No one controls a model's answers. My post on GEO agency red flags covers the proposals to avoid.
- A fixed percentage lift from any single tactic.
- Dashboards as proof. Variation between runs is large; see why most AEO case studies prove nothing.
- llms.txt as a trigger, at least for Google, per its guide.
How to measure GEO without fooling yourself
- Build a prompt panel of 30-50 real buyer questions.
- Run them on each engine you care about, on a schedule, recording date, model and location.
- Repeat each prompt several times, since answers vary.
- Log whether you are cited (linked), mentioned (named), or absent, and which competitors appear.
- Compute share of voice as appearances divided by total runs, per engine.
- Report ranges and trends, not single screenshots.
Tool-based tracking can save time but inherits the same noise; my take is in are AI visibility tools worth it.
Where I use GEO thinking
My work as an organic growth marketer is mostly the unglamorous parts: clear pages, consistent entities, and distribution. At Masai School, the social growth from 26K to 117K Instagram followers and 50K to 200K on LinkedIn came from repeatable content systems, which I describe in the Masai School case study. The same discipline, a measurable system over a trick, is how I approach AI visibility.
FAQ
What does GEO stand for?
GEO stands for generative engine optimization. It refers to improving how often AI systems that generate answers cite or mention your brand and content.
Is GEO different from SEO?
Partly in goals and metrics, mostly not in methods. Google's guide says optimizing for generative AI search is still SEO from its perspective. GEO adds measurement across non-Google engines.
Is GEO the same as AEO?
Many practitioners use them interchangeably, and Wikipedia notes there is no consensus definition. Some sources treat GEO as broader and AEO as narrower, while others reverse it. Define the term in your contract.
Who invented the term GEO?
It appeared in a 2023 paper by Aggarwal, Murahari, Rajpurohit and colleagues, later accepted to KDD 2024. Marketers adopted it afterward.
Does GEO work?
Some tactics showed gains in the paper's experiments, and the authors noted effectiveness varied by domain. Real-world results depend on engine, topic and competition, and variance between runs is high.
Do I need llms.txt for GEO?
Google's guide says Google Search itself does not use llms.txt and that it neither helps nor harms visibility there. Other engines may behave differently, and I have not seen firm evidence either way.
Do I need schema markup for GEO?
Google says structured data is not required for its generative AI features. Schema still helps describe your page accurately for other uses.
How do I measure GEO results?
Use a repeatable prompt panel, record date, model and location, repeat runs, and report share of voice as a range. Avoid single screenshots.
Can anyone guarantee I will be cited by ChatGPT or AI Overviews?
No. Answers are generated and vary. Treat guarantees as a red flag.
Work with me
I am Younus Fardeen, an organic growth and answer-engine marketer with 4+ years of marketing experience in edtech and startups. If you want a clear, honest baseline of where your brand appears in AI answers, see my work and reach out through the contact form at younusfardeen.in.
Verified as of 4 October 2026. Google statements are quoted from its documentation; vendor and study figures are attributed to their sources.