What Is Generative Engine Optimisation and How Does It Differ from SEO?

Search is changing. For the past two decades, appearing in search results meant earning a position in a list of links. The user saw the list, chose one, and visited the site. The game was: rank in that list for the right terms.

A different model is emerging alongside that one. Increasingly, when people search, they receive a synthesised answer generated by an AI, drawing on multiple sources, summarising relevant information, and sometimes citing the sources it used. The user gets an answer without necessarily visiting any site at all.

Generative Engine Optimisation is the discipline of making sure your content is one of the sources that answer draws from.

How AI Search Differs From Traditional Search

In traditional search, Google indexes pages, ranks them for relevant queries, and presents a list. The user exercises judgement about which result to click. Your site gets a visit if they choose yours.

In AI search, the engine reads multiple sources, synthesises the information into a coherent answer, and may cite some of those sources inline. The user receives the answer directly. Whether they click through to your site depends on whether they want more detail beyond what the summary provides.

This has two significant implications:

First, brand and authority signals matter in a different way. If an AI model has learned from content across the web that your business is a credible source on a particular topic, it is more likely to draw from your content in forming answers.

Second, visibility is decoupling from traffic. Your content might be used to generate an answer without generating a visit. For businesses that rely on informational content to attract potential customers, this is a structural shift that requires a response.

What AI Engines Are Looking For

The content characteristics that tend to get cited by AI search tools are distinct from, but overlapping with, what earns traditional search rankings:

Factual Clarity and Accuracy

AI engines are attempting to synthesise reliable information. Content that makes clear, well-supported factual claims is more useful to them than vague, hedged, or promotional content. Write as if your goal is to inform, not to impress.

Structured, Parseable Content

Headings, lists, tables, and well-organised paragraphs make content easier for AI systems to parse and summarise. A wall of unbroken text is harder to extract value from than a well-structured document with clear sections.

Depth Over Thin Coverage

A comprehensive article that thoroughly covers a topic is more likely to be cited than a brief page that skims it. AI engines draw on sources that actually answer the question being asked, and often prefer sources that go deeper.

Authority and Trust Signals

Content attributed to real people with demonstrable expertise, published on sites with genuine links and reputation, and aligned with structured data (particularly Entity and Organisation schema) carries stronger authority signals. Authorship, credentials, and domain reputation all play a role.

GEO and SEO: Complementary, Not Competing

A common question is whether businesses need to choose between traditional SEO and GEO. The answer is no. They are built on the same foundation.

A well-structured page with strong content, good on-page SEO, appropriate schema markup, and genuine backlinks performs well in both traditional search and AI-generated answers. The incremental work for GEO is relatively modest if the SEO fundamentals are already in place: clearer entity signals, deeper content on key topics, and an llms.txt file to guide AI crawlers.

The biggest risk is treating them as separate programmes. The businesses that will win in the AI search era are those that build content and authority consistently, across both traditional and emerging signals.

To explore the full range of AI search optimisation techniques, visit the AI search hub. If you want to discuss how this applies to your specific business, our SEO agency in Lincoln can help you build a strategy that covers both the present and where search is heading.