Generative Engine Optimisation (GEO)
Generative Engine Optimisation (GEO) is the practice of optimising content and digital presence so that generative AI systems (such as ChatGPT, Claude, Gemini, and Perplexity) accurately represent, cite, and recommend a business in their generated responses.
What Is Generative Engine Optimisation?
Generative Engine Optimisation is an emerging discipline focused on ensuring that AI systems include, cite, and accurately represent a business when generating responses to user queries. Where traditional SEO aims to place a link on a search results page, GEO aims to place a business inside the answer itself. When a buyer asks an AI assistant to recommend suppliers for a specific product category, the businesses that appear in that synthesised response have been effectively "optimised" for generative engines, whether deliberately or through the natural strength of their digital presence.
GEO encompasses a range of practices that influence how AI models perceive and represent a business entity. These include creating authoritative, well-structured content that AI systems can extract and reference with confidence, implementing structured data for commerce using Schema.org vocabulary, building consistent entity profiles across the web, and producing content that directly addresses the questions buyers are asking AI tools. The goal is not to manipulate AI outputs but to ensure that AI systems have access to accurate, comprehensive, and well-organised information about your business.
The term "generative engine" refers to any AI system that generates responses rather than simply returning a list of links. This includes conversational AI platforms like ChatGPT and Claude, AI-powered search tools like Perplexity and Google AI Overviews, and the growing number of AI purchasing agents that autonomously research and evaluate suppliers. GEO is the umbrella practice for ensuring AI visibility across all of these systems.
Why GEO Matters
The way B2B buyers discover and evaluate suppliers is undergoing a fundamental transformation. An increasing proportion of procurement professionals now use AI tools as part of their research process, and that number is accelerating. When these buyers ask AI systems to compare suppliers, recommend solutions, or evaluate options, the AI generates a synthesised response drawing from its understanding of the market. Businesses that are absent from these responses are effectively invisible to a growing segment of their potential customer base.
GEO matters because the dynamics of AI-generated recommendations are fundamentally different from search engine results. In traditional search, a business might rank on page two and still receive some traffic. In AI-generated responses, there is no page two. The AI either includes you or it does not. This binary nature makes GEO especially high-stakes for B2B businesses where a single contract can represent significant revenue. Being included in an AI's shortlist of recommended suppliers can mean the difference between winning a major account and never knowing the opportunity existed.
For manufacturers and B2B suppliers, the urgency of GEO is compounded by the rise of agentic commerce. As AI agents begin handling procurement tasks autonomously, GEO transitions from a marketing concern to an operational necessity. An AI purchasing agent evaluating suppliers on behalf of a buying organisation will rely entirely on its ability to discover and assess businesses through digital channels. Without a GEO strategy, businesses risk being systematically excluded from the AI procurement workflows that are replacing traditional supplier discovery.
How GEO Works
GEO operates across several layers of a business's digital presence. At the content layer, it requires creating authoritative, comprehensive material that directly addresses the questions buyers and AI systems are asking. This means moving beyond marketing copy towards substantive, extractable content, including clear product specifications, definitive capability statements, detailed service descriptions, and expert insights that AI systems can confidently reference. Content structured with clear headings, definitions, and factual statements performs significantly better in AI retrieval than vague promotional language.
At the technical layer, GEO relies heavily on structured data. Implementing Schema.org markup in JSON-LD format gives AI systems machine-readable access to your business information, including product catalogues, pricing, availability, organisation details, and service offerings. This structured data serves as a reliable signal that AI systems can use with high confidence, complementing the unstructured content they extract from your pages. The relationship between GEO and Answer Engine Optimisation (AEO) is close: AEO focuses specifically on being extracted as direct answers, while GEO encompasses the broader goal of accurate representation across all AI interactions.
At the entity layer, GEO requires consistency. AI models build entity profiles by aggregating information from across the web. If your business name, product specifications, certifications, and contact details are consistent across your website, industry directories, government registrations, and third-party platforms, AI systems can build a higher-confidence profile. This entity consistency is what enables an AI system to confidently recommend your business rather than hedging with qualifiers or omitting you entirely. GEO is ultimately about making your business legible and trustworthy to the AI systems that are increasingly mediating B2B commerce.
Key Takeaways
- GEO is the practice of optimising for inclusion and accurate representation in AI-generated responses, a fundamentally different goal from traditional SEO.
- AI-generated responses have no "page two." Your business is either included in the answer or it is not, making GEO a high-stakes priority for B2B.
- The three layers of GEO are content (authoritative, extractable material), technical (structured data and Schema.org markup), and entity (consistency across digital properties).
- GEO is increasingly a prerequisite for participating in agentic commerce, where AI purchasing agents discover and evaluate suppliers autonomously.
- Businesses should begin with a GEO audit, checking how AI systems currently represent them, and build a systematic optimisation strategy from there.