What is Generative Engine Optimisation (GEO)?
Generative Engine Optimisation (GEO) is the process of improving your content’s visibility within AI-powered generative search tools such as Google’s AI Overviews, Bing Copilot, and ChatGPT Search. Unlike traditional SEO, which aims to rank your pages on search engine results pages (SERPs), GEO aims to get your content cited or used in AI-generated answers that appear before traditional links, often resulting in zero-click outcomes.
What are generative search engines?
Aside from additional functionality such as the integration of structured data and modifications to SEO algorithms, traditional search engines have been around in close to their current form since the mid-late 90s. And whilst they are effective in terms of speedy access to up-to-date content and relevance ranking via SEO keyword inclusion, they struggle with placing individual queries into a wider context.
Generative AI in the form of chatbots was designed to parse messages for user intent and place subsequent messages into the context of previous ones, as well as isolate the keywords and phrases from within more conversational text. As chatbots, however, they do not have access to the internet, so their responses are limited to the latest information that they have been trained with.
Enter generative search engines – the contextualisation and language parsing of a chatbot with the wider and more current access to information of a search engine. There are a number of more specialised examples which are often paid-for services, but the three main providers of generated AI-augmented search are Microsoft, Google and Chat GPT.
Microsoft Bing with Copilot
Along with Google and Yahoo, Microsoft’s Bing is one of the most widely used search engines. They have now integrated their AI engine Copilot, which runs on OpenAI using GPT-4 – currently the most up-to-date version of Chat GPT. Its use of GPT-4 helped it to grow in popularity, as until recently, it was the only way to use GPT-4 for more than 15 queries a day without a paid account.
People tend to choose Bing if they already prefer it as their standard search engine or if they are also heavy users of the Microsoft 365 suite, since Copilot has now been fully integrated into all of their software.
Chat GPT Search
Chat GPT Search (formerly called SearchGPT) is a more recent development and runs within OpenAI’s purpose-built search engine. Running on GPT-4o, it is available within the app, in web browsers and through a Chrome browser extension and as of February 2025 does not require an account to access.
People tend to choose Chat GPT Search if they already make use of Chat GPT, or if they prefer the user interface of this to Bing. Functionally, they are very similar since they are based on the same AI Large Language Model (LLM).
Google AI
Google have not fully integrated their AI into search yet, and it is currently limited to AI Overviews and visual search (image and video) using Lens. This is something which Google are focusing on in 2025 with more features and integrations planned.
Although not currently as fully developed as the OpenAI-powered options, test searches performed at the time of writing showed that Google’s loading time was significantly faster and the information was more up-to-date. This is even more evident in searches which connect to other Google-owned services such as YouTube.
People tend to use Google if this is already their search engine of choice or if they are invested in the Android ecosystem.
What are the benefits of Generative Search?
- LLMs are trained to understand context and user intent. This means that as they improve, they should return more relevant search results than SEO alone.
- Generative AI is built to retain context between search entries, so a generative search engine can understand follow-up search queries within the context of the original search.
- Because they are based on the code for AI chatbots, searches which are phrased using conversational language are more likely to be understood correctly than with a traditional search engine.
- Responses are presented in a conversational format, and the information asked for is displayed directly within the results page, which can save time for simpler queries as this minimises the need to click through to individual entries.
- The information from several pages can be combined into one answer, particularly in Google AI Overviews, which can also save time.
How is generative search different to SEO?
Traditional Search
- Picks out isolated keywords
- Results can be personalised based on search history
- Each search query is an isolated event
- Results presented as a list of links with snippets
- Links to information already published
Generative Search
- Understands whole sentences
- Responses can be personalised based on conversation history
- Strings of queries are treated as a conversation with contextual understanding maintained
- Results presented as answers in a conversational style
- Can generate original material based on the contents of search results
How can you optimise for generative search?
- Optimise for SEO. The same keywords which help you to achieve higher search rankings will also present your content as more relevant to an AI engine.
- Utilise prompt-based language. Phrasing your titles and subheadings as questions or instructions signposts the subject of your content and makes it easier for AI models to recognise that content’s relevance to the topic.
- Follow the E-E-A-T principles. Google’s Search Results Evaluator programme is designed to prioritise well-written, trustworthy content which is written with authority and expertise and train the search algorithms to do so. Since LLMs understand longer strings of text and can ascribe contextual meaning to them, this is something which generative search engines can also be trained to give higher weighting to.
- Be specific. Shorter content which addresses a single topic or question is more accessible to both users and AI crawlers than a longer piece which lacks focus.
- Adopt a multi-format approach. Including graphics, tables, and bullet lists in your content makes it more approachable to users, making it both easier to skim for relevant sections and more comfortable to look at for a full read versus a large body of plain text. Including these elements in your content, along with the appropriate markup code, also means that it is easier to isolate relevant sections of the page to display in a wider variety of ways on the SERP.
How is content attribution handled in generative search?
One of the biggest challenges in the age of generative search is attribution. Unlike traditional search, where a user clicks through to a specific webpage, generative AI often aggregates and rewrites content in its own words, sometimes without obvious source links. This means your brand visibility and authority must be baked into your content.
Tips to ensure attribution:
- Use clear branding in your writing (e.g., “At [Your Brand], we recommend…”).
- Include unique statistics or frameworks that AI models can’t easily paraphrase.
- Make use of structured data to help models parse and cite your content.
- Build backlinks and maintain topical authority so your domain is recognised as a trusted source.
Generative Search Engines to Watch
While Microsoft Bing Copilot, ChatGPT Search, and Google AI dominate the space, several other platforms are emerging with powerful generative search capabilities:
- ai: Known for real-time search with citations, often preferred by power users who want sourced, up-to-date answers in a clean interface.
- com: Offers a blend of generative answers, classic links, and vertical-specific tools (like code and academic search).
- Andi: A newer AI search engine designed for younger users, using natural language responses instead of lists of links.
These alternatives are gaining traction for specific use cases and demonstrate the ongoing shift away from traditional link-first search engine models.
Final thoughts
The integration of generative AI into search engines is a relatively recent development, but as more sophisticated functionality is added, it is one which has the potential to drastically alter the way that people search for information.
Frequently Asked questions
What is generative engine optimisation (GEO)?
GEO is the process of optimising content to appear in AI-generated search results and answers, rather than just ranking on traditional search engine pages.
How do I know if my content is showing up in AI-generated answers?
Currently, attribution is inconsistent. You can monitor mentions of your brand or specific phrases using tools like Google Alerts, or test generative engines by asking them questions related to your niche.
Is traditional SEO still important in the age of generative search?
Yes. Traditional SEO practices like keyword optimisation, backlinks, and EEAT still underpin how generative models assess content quality and authority.
What types of content perform best in generative search?
Clear, focused content that answers specific questions, includes unique insights, and is written in natural language is more likely to be included in AI-generated summaries.
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