For many years, search engine optimisation (SEO) has remained an integral aspect of internet marketing. Companies have optimized websites for search engine crawlers, indexing, and ranking. But how people search is evolving rapidly.
Rather than typing out searches into engines and browsing through links, users are increasingly resorting to generative AI tools, such as ChatGPT, Google Gemini, Microsoft Copilot, and Perplexity, to receive direct, synthesized responses. These tools do not retrieve information: they create it. This is building a new challenge and opportunity for marketers: Generative Engine Optimization (GEO).
GEO is not a rebrand of SEO. It’s a distinct and new discipline dedicated to getting your brand, product, or content into the answers that are returned by artificial intelligence. Since marketers used to have to learn how Google’s search algorithm ranked sites, now they must learn how big language models (LLMs) choose and integrate information.
1. From Search Engines To Generative Engines
Traditional SEO relies on how search engines evaluate a website’s relevance and authority based on factors like keywords, backlinks, content quality, and site performance. Rankings are determined by algorithms that reward optimized structure, trustworthy content, and technical accessibility. Generative engines, powered by AI models trained on massive datasets, work differently. Instead of listing links, they compose answers by pulling from a mixture of training data, online content, APIs, and context from the user’s question.
Ask ChatGPT: “What are the best budget electric cars in 2025?” and it won’t show you websites, it will list models, prices, and pros/cons. Your brand needs to be part of that generated content if you want to stay relevant.
That’s what GEO is about: ensuring your brand or product is present in generated content, not just search results.
2. GEO vs. Traditional SEO: Key Differences
Whereas SEO focuses on optimizing a specific page, GEO optimizes one page for all target locations.
2.1. Search Engine Optimisation
Centers on refining content for search engine algorithms, with an emphasis on keywords, backlinks, and metadata for SERP ranking improvement.
2.2. Generative Engine Optimization
Focuses on content optimization for AI engines so that information is contextually pertinent, authoritative, and designed for easy adoption within AI-generated content.
In a way, whereas SEO is directed toward optimizing for the algorithms of search engines, GEO works on aligning content with generative AI models’ processing and output mechanisms.
3. Why GEO Matters Right Now
3.1. User Behaviour is Changing
AI is increasingly taking over regular search for most tasks. According to a 2024 study by Pew Research, 47% of internet users under age 35 prefer using AI assistants rather than search engines for getting quick answers or product suggestions. With artificial intelligence built into browsers, operating systems, and gadgets, consumers are bypassing Google entirely. If your company is depending solely on SEO, you’re missing where things are moving.
3.2. Zero Click Reality
Search engines have shifted toward zero-click results, where the answer is shown directly on the page, think feature snippets or Google’s AI Overviews. In generative engines, the zero-click format is even further: the answer is the product.
If your product, company, or content isn’t included within that generated response, you’re invisible, zero clicks, zero impressions, zero traffic.
3.3. New Playing Field, New Rules
GEO is not well established, and therefore, there is a strategic benefit for acting now. Marketers who succeed in affecting generative models will get noticed before competitors are still acclimating themselves to SEO.
4. How to Approach Generative Engine Optimization
4.1. Write for Humans, Not Bots
Generative engines pull from sources that are well-written, clear, and easy to understand. Long-winded or over-optimized content confuses LLMs. Instead:
- Use plain language
- Break up text with headings
- Provide direct answers to common questions
- Include relevant facts and context
Think less about keyword density, more about information clarity.
4.2. Target Natural Language Queries
Search engine optimization has often revolved around specific keyword phrases. GEO, however, thrives on natural language. People ask full questions: “What’s the best VPN for travelers in 2025?” Your content should reflect and answer those exact queries.
Try creating FAQ sections, product comparisons, and guides written in a conversational but informative tone.
4.3. Build Topical Authority
Generative models prefer sources considered credible as well as consistent. Which implies:
- Publishing detailed articles on precise subject matters
- Securing mentions on legitimate third-party sites
- Maintaining a uniform brand presence on the web. The greater the association of your brand with a given subject, the better the chances of being included within content created by artificial intelligence for that subject.
4.4. Increase Brand Mentions Across Web
LLMs learn from an immense quantity of publicly available content. They will have higher probabilities of mentioning brands that are often cited frequently with positive sentiment across the web.
This includes
- Reviews from places such as Reddit, Trustpilot, or G2
- References in print news stories and blogs
- Listings on product directories and comparison sites
- Forums for discussion and Q&A. These are GEO’s key signals—perhaps even more so than backlinks.
4.5. Use Structured Data Where Possible
Unlike Google, generative engines do not scan structured information, though clean formatting is still preferable. Cleverly formatted, well-labeled pages are preferred by web-trained AI tools.
Use structured data (such as Schema.org) and semantic HTML where possible. This doesn’t guarantee inclusion within a generative response, but it makes your content easier for parsers.
4.6. Participate in The AI Ecosystem
Certain generative tools interface with live data via plugins or APIs. For instance:
- The OpenAI ChatGPT is based on third-party booking, shopping, and browsing capabilities
- Perplexity draws directly from real-time web sources
- Google’s Search Generative Experience quotes sources inline
You can enhance your prospects of being included by making your content accessible through APIs or joining the ecosystems of such tools.
5. Challenges in GEO Implementation
While GEO provides major benefits, it certainly doesn’t come without its fair share of challenges:
5.1. Understanding how AI acts
Generative models are intricate and many function as “black boxes,” so it is not easy to know how they process and apply content.
5.2. Sustaining Content Authenticity
Preserving content authenticity and credibility while optimizing for AI inclusion is essential to avoid misinformation.
5.3. Ethical Implications
With evolving GEO strategies, ethical issues of manipulation of AI-generated outputs, as well as dissemination of biased information, can potentially emerge.
Conclusion
GEO will increasingly become a standard part of digital marketing strategies as AI continues to transform the digital scene. Marketers need to adjust by creating content not only appealing to human readers but also appropriate for the mechanisms of generative AI as well. GEO adoption by businesses can help increase their presence within AI-generated content, allowing them to stay on top as the information landscape becomes increasingly shaped by AI.