Search is changing. Instead of scrolling through a list of links, people are now asking AI tools direct questions and getting a single written answer in return. That shift is why a new term has entered the SEO conversation: GEO, or Generative Engine Optimisation.
Before getting into tactics or strategy, it helps to understand what GEO actually is, why it exists, and how it fits alongside SEO rather than replacing it.
Quick summary
- Generative Engine Optimisation (GEO) is the practice of making content easy for AI-driven search tools to understand and trust
- GEO focuses on helping your content be used within AI-generated answers, not just ranked as a clickable link
- It prioritises clarity, structure, accuracy, and credibility
- GEO builds on traditional SEO rather than replacing it
- The goal is visibility through being referenced and relied on, even without a website visit
Why people ask “what is GEO?”
For a long time, search followed a familiar pattern. Someone entered a query, reviewed a list of results, and visited one or more websites to find the information they needed.
Over time, that pattern has continued to evolve.
Search experiences increasingly provide direct answers by drawing information from multiple sources and presenting it in a single response. In many cases, users can understand a topic without clicking through to a website at all.
As this approach has become more common, visibility has started to mean more than simply ranking well. It now also includes whether your content is used, referenced, or relied on when answers are generated.
The behaviour changed first. The terminology followed. GEO is simply a way of describing how content needs to adapt as search continues to prioritise direct, synthesised answers over lists of links.
What is generative engine optimisation?
Generative Engine Optimisation is the practice of making your content easy for AI-driven search and answer tools to understand, trust, and use when generating responses.
Put simply, GEO is about helping your content become part of the answer, not just a link someone might click.
A quick example makes this clearer.
In a traditional search, someone might Google “what is generative engine optimisation”, browse a few articles, and read one that explains it well.
In an AI-driven search, someone asks the same question and receives a single explanation written by the system. That explanation is built using information from selected sources. If your content is one of those sources, you still gain visibility, even if the user never visits your site.
That is the core idea behind GEO. It is not about shortcuts or tricks. It is about publishing content that is clear, well-structured, and trustworthy enough to be relied on.
GEO vs SEO: how they actually differ
At first glance, GEO can sound like a replacement for SEO. In reality, the two are closely connected.
SEO focuses on helping pages rank in search results so users can find and click them. GEO shifts the goal slightly. Instead of focusing only on rankings and traffic, it looks at whether your content is selected and reused when an AI system generates an answer.
The difference is not about competing strategies. It is about different outcomes.
With SEO, success is usually measured by rankings, impressions, and clicks. With GEO, success is about being referenced, cited, or relied on inside AI-generated responses.
In most cases, strong SEO is what makes GEO possible in the first place.
Why GEO is best viewed as an extension of SEO
AI-driven search tools do not create information from nothing. They rely on content that already exists on the web. That content still needs to be discoverable, readable, and credible.
This is why GEO works best when built on solid SEO foundations. Pages with poor structure, thin content, or weak credibility are far less likely to be used by AI systems.
Think of SEO as helping your content get discovered and indexed, and GEO as helping it get selected and reused.
This is also where concepts like experience, expertise, authority, and trust still matter. If your content lacks credibility, it will struggle to perform in both traditional search and AI-generated answers. If you want a deeper breakdown of how those trust signals work, our guide to experience, expertise, authority, and trust (E-E-A-T) explains why they remain critical as search evolves.
Example:
A professional services firm consistently publishes educational content under its brand name, and is regularly referenced by industry publications and third-party articles using branded mentions rather than generic links.
Over time, the firm’s brand becomes repeatedly associated with explanations of its core topic area. When answer-led systems review content across the web, they encounter the same brand name attached to similar insights across multiple sources.
This repeated association helps establish the brand itself as a recognisable source of information, making it easier for systems to reference the business when generating answers, rather than treating each article as an isolated page.
What has not changed
Despite new terminology, the fundamentals of search have not disappeared.
Content still needs to be technically accessible. It still needs to be useful, accurate, and relevant. Authority and trust still play a major role in whether information is surfaced or ignored.
The biggest change is not the rules themselves. It is how visibility is delivered. Instead of focusing only on rankings and clicks, businesses now need to consider whether their content is strong enough to be treated as a reliable source.
How AI-driven search actually works at a practical level
How generative search engines create answers
Most AI-driven search systems follow a similar process. They interpret the question, retrieve relevant information from available sources, and then generate a response by summarising that information into a single answer.
These systems shouldn’t invent facts (although sometimes, they do). They rely on content they can access, understand, and trust. If your content is unclear or difficult to interpret, it is unlikely to be used.
This is why clarity and structure matter so much. AI systems are looking for information they can confidently reuse, not vague explanations or marketing-heavy copy.
Example:
A hospitality business in Margaret River publishes a detailed blog titled The Best Family-Friendly Restaurants in Margaret River.
The article is structured around the needs parents actually care about, such as kid-friendly menus, space for prams, relaxed dining environments, and nearby attractions. Each section answers a specific question a family might ask when choosing where to eat.
When a user later asks an answer-led search system a conversational question like “what’s a family-friendly restaurant in Margaret River?”, the system does not rely on that exact wording alone. It expands the request into related queries and intent variations, reviews content that directly addresses those needs, and draws from sources that clearly cover the topic.
Because the blog was written to match that broader conversational intent, rather than a single keyword, it is more likely to be used when forming the response.
Why some content gets used and other content gets ignored
When multiple sources cover the same topic, AI systems have to decide which ones to rely on.
Content that performs well in generative search tends to answer questions directly, use logical headings, and present information in clear sections. It focuses on substance rather than filler.
Trust also plays a major role. Content that demonstrates real expertise and accuracy is far more likely to be selected than generic summaries.
This is especially true for topics that could impact someone’s health, finances, or legal decisions. In these cases, AI systems tend to be more cautious and selective, which mirrors how search engines already treat Your Money or Your Life (YMYL) content.
For guidance on how to write your content from both SEO and GEO purposes, check out our handy SEO content writing guide.
What GEO looks like in practice
In practice, GEO is about making your content easy to use as a reference.
This starts with clearly defining concepts, explaining ideas step by step, and structuring pages so the key points are obvious. Lists, definitions, and concise explanations help both readers and answer-led systems extract meaning quickly.
Example:
“A services business publishes a detailed article explaining a specialised topic. The content clearly separates educational information from service details, making it obvious that the page exists to explain a concept rather than sell a product.
Supporting structural signals reinforce this clarity by identifying the page as an article, the business as the publisher, and the service as a related but separate entity. As a result, there is less ambiguity about how the content should be interpreted, increasing the likelihood that it is treated as a reference source rather than promotional material.”
GEO also means prioritising accuracy and credibility. Content grounded in real experience and expertise is more valuable in an answer-led environment than surface-level commentary.
Rather than writing to impress algorithms, GEO encourages writing to be understood.
Example:
“Two articles cover the same topic. One opens with a long introduction about the business before reaching the main point several paragraphs later. The other opens with a clear definition and immediately addresses the core question the reader is asking.
When an answer-led system evaluates both pages, the second article makes it easier to identify relevance quickly. The core information is immediately visible, reducing uncertainty about what the page contributes. As a result, the clearer page is more likely to be reused when forming a summarised answer, even if both articles contain similar information overall.”
What GEO means for businesses going forward
What GEO is not
As interest in GEO grows, so does confusion.
GEO is not a replacement for SEO. Traditional optimisation still underpins how content is discovered and evaluated.
It is not about manipulating AI tools or chasing short-term tactics. These systems change too quickly for that approach to work.
And it is not a separate checklist you bolt on after publishing. GEO is about how content is planned, written, and structured from the start.
Do businesses need to care about GEO right now?
Not every business is affected in the same way or at the same pace.
Industries that rely heavily on informational content, advice, comparisons, or early-stage research are seeing the impact first. In these areas, AI-generated answers can replace multiple clicks that would previously have gone to blogs or guides.
For businesses focused purely on transactional searches, the shift may feel slower. Even so, understanding GEO now allows businesses to adapt gradually rather than react later under pressure.
How to think about GEO long term
The most useful way to think about GEO is as a mindset shift rather than a new tactic.
Instead of focusing only on where a page ranks, the focus moves to how well it answers a question. Content that is clear, structured, and trustworthy is more likely to be reused, referenced, and relied on over time.
GEO is not about chasing algorithms. It is about becoming the best answer available, wherever that answer is delivered.
Want to make sure your content stays visible as search evolves?
As AI-driven search becomes a bigger part of how people find information, businesses need content that performs beyond traditional rankings. We help businesses strengthen their SEO foundations while preparing for visibility inside AI-generated search results.
To learn more about our approach to GEO and how it fits alongside SEO, let’s talk.
