What Is Generative Engine Optimisation (GEO)?
Generative Engine Optimisation (GEO) is the practice of optimising your brand, content, and digital presence so that AI-powered search engines and assistants recommend you in their responses. Think of it as SEO's next evolution -- built for the age of ChatGPT, Perplexity, Claude, and Google AI Overviews.
Why a New Discipline?
For over two decades, search engine optimisation (SEO) has been the bedrock of online marketing. You researched keywords, published content, built back-links, and climbed Google's ten blue links. That model still exists, but it is no longer the only game in town.
In 2026, a growing share of commercial queries never reach a traditional search results page. Instead, users ask an AI assistant -- and the assistant answers directly. Gartner estimates that by the end of this year, nearly 40 percent of search queries in Western markets will pass through an AI layer before the user sees a result. If your brand is absent from those AI-generated answers, you are invisible to a rapidly growing audience.
That is precisely the problem GEO addresses. Where SEO asks "How do I rank in Google's organic listings?", GEO asks "How do I get mentioned and recommended when an AI answers a question about my industry?"
How GEO Differs from Traditional SEO
On the surface, the two disciplines share DNA. Both care about authority, relevance, and trustworthiness. But the mechanisms diverge in important ways.
Ranking vs. Recommendation
Traditional SEO revolves around ranking positions. You aim for position one on a search engine results page (SERP). GEO, by contrast, focuses on being included in an AI's synthesised answer. There is no numbered list; the AI simply names the brands it deems most relevant and helpful.
Keywords vs. Conversational Queries
SEO targets typed keywords -- often two or three words. GEO must account for full, natural-language questions that people pose to AI assistants. "Best CRM for a 10-person accountancy firm in Manchester" is a typical AI query, not a typical SEO keyword.
Links vs. Training Data and Citations
Back-links tell Google a page is authoritative. AI models draw on a combination of training data, retrieval-augmented generation (RAG), and live web access. Being cited in high-authority sources that AI models trust -- industry publications, structured data, well-maintained knowledge bases -- carries more weight in GEO than a profile link on a low-traffic directory.
Static Pages vs. Dynamic Answers
A Google ranking is relatively stable once earned. AI responses are generated fresh each time. The same question, asked a day later, might produce a different set of recommendations. This makes ongoing monitoring essential -- and it is one of the reasons tools like RivalScope exist.
How AI Models Decide What to Recommend
Understanding the mechanics behind AI recommendations is the first step toward influencing them.
Training Data
Large language models are trained on vast corpora of text scraped from the open web. If your brand appears frequently and positively in high-quality sources during the training window, the model develops a statistical association between your brand and relevant topics.
Retrieval-Augmented Generation (RAG)
Platforms such as Perplexity and Google AI Overviews do not rely solely on static training data. They fetch live web results at query time and synthesise an answer from those results. This means that your current SEO presence feeds directly into your GEO presence on RAG-based platforms.
Citation Patterns
When an AI model cites sources, it tends to favour content that is clearly structured, factually dense, and hosted on domains with established authority. Thin marketing pages are rarely cited; comprehensive guides, original research, and well-structured product pages are.
Brand Signals
AI models pick up on the same trust signals that search engines use: consistent NAP (name, address, phone) data, presence on authoritative review sites, mentions in reputable media, and a coherent brand identity across channels.
Five Practical GEO Strategies
Below are five strategies you can begin implementing today.
1. Create Comprehensive, Citable Content
Publish long-form content that answers specific questions thoroughly. Structure it with clear headings, bullet points, and data. AI models are more likely to cite content that is easy to parse and rich in factual detail. Aim for content that an AI would consider a reliable source -- not a sales pitch, but a genuinely helpful resource.
2. Strengthen Your Presence on Authoritative Platforms
AI models learn from and retrieve content from high-authority domains. Contribute guest articles to industry publications, maintain an up-to-date Wikipedia presence where appropriate, ensure your business is accurately listed on major directories, and seek coverage from reputable media outlets.
3. Optimise for Conversational Queries
Research the questions your target audience asks AI assistants. These tend to be longer and more specific than traditional search queries. Create content that directly addresses these questions, using the same natural language your audience uses. FAQ pages, how-to guides, and comparison articles are particularly effective formats.
4. Build a Consistent Brand Entity
AI models recognise brands as entities. Ensure your brand information is consistent across the web -- your website, social profiles, business directories, and data aggregators should all tell the same story. Structured data markup (schema.org) helps AI models understand what your business does, where it operates, and what it offers.
5. Monitor and Iterate
GEO is not a one-off exercise. AI responses change over time as models are updated and new content is indexed. Track how AI assistants talk about your brand, identify gaps, and adjust your strategy accordingly. This is where AI visibility tracking becomes essential.
How to Measure GEO Performance
Measuring GEO performance requires a different toolkit from traditional SEO analytics. You cannot simply check your Google Search Console for AI visibility data. Instead, you need to:
- Track brand mentions across AI platforms. Run the queries your customers would ask and record whether your brand appears in the response. Do this across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews.
- Monitor citation frequency. When AI models cite sources, track how often your content is included. This is especially important for RAG-based platforms like Perplexity.
- Measure sentiment. It is not enough to be mentioned; you want to be mentioned positively. Track whether AI models describe your brand favourably or raise concerns.
- Compare against competitors. Your absolute visibility matters less than your visibility relative to your competitors. If they are being recommended and you are not, you have a problem regardless of your raw numbers.
RivalScope automates this entire process. It runs your industry queries across multiple AI platforms, tracks which brands are recommended, analyses sentiment, and delivers actionable recommendations so you know exactly what to do next.
The Relationship Between SEO and GEO
It is worth stressing that GEO does not replace SEO. The two disciplines are complementary. Strong SEO performance feeds RAG-based AI systems with your content. Strong GEO practices ensure that your brand is well-represented in AI training data and responses.
If you are already investing in SEO, you have a head start on GEO. The additional work involves understanding how AI models select and synthesise information, and tailoring your strategy to those specific mechanics.
For a detailed walkthrough of optimising for specific AI platforms, read our AI search optimisation guide.
Getting Started
If you are new to GEO, here is a simple starting point:
- Audit your current AI visibility. Ask the major AI assistants questions relevant to your industry and see whether your brand appears. Note which competitors are mentioned and what sources are cited.
- Identify gaps. Where are you missing? Which platforms mention competitors but not you? Which queries return no mention of your brand?
- Prioritise actions. Focus on the strategies above that address your specific gaps. If you are never cited, invest in authoritative content. If you are mentioned but with outdated information, update your web presence.
- Track progress. Set up ongoing monitoring so you can measure the impact of your changes over time.
GEO is still a young discipline, and the brands that invest in it early will have a significant advantage as AI-powered search continues to grow. The question is not whether to start -- it is how quickly you can begin.
Ready to see how your brand performs in AI search? Start your free RivalScope trial and get your first AI visibility report in minutes.