“AI isn’t killing search – it’s teaching us to talk to machines like people.” This idea sits at the heart of Generative Engine Optimization (GEO).

In 2025, marketers are not only trying to get blue links on a search results page; they are also trying to join a discussion between people and smart assistants.

Google’s AI Overviews already appear in almost half of search queries and cover three‑quarters of the mobile screen. ChatGPT alone now receives over 10 million queries per day, surpassing Bing’s daily volume.

Large language models (LLMs) like OpenAI’s GPT‑4, Claude and Google’s Gemini have become guides, researchers and decision‑makers and, to stay visible in these platforms, brands must learn how to feed these engines with the right signals.

This article talks about the science underpinning GEO, what makes generative engines work, how GEO is different from AI Overviews, and the strategic building blocks you need to succeed. The idea is to make GEO less mysterious and help you come up with content strategies that are ready for AI, whether you are a marketing leader, product manager, or entrepreneur.

How Generative Engines Work

Traditional search engines crawl pages, index keywords and rank results based on relevance and authority.  On the other hand, generative engines understand, combine, and respond. They use big neural networks that have been trained on massive amounts of data, such as books, articles, code, and transcripts. They improve their comprehension through reinforcement learning and feedback in real time.

Generative engines follow a multi‑step process –

• Query understanding and intent detection –  Models can understand natural language prompts, find entities, and figure out what the user wants. They even use what was said in previous conversations and the user’s context. To understand context and nuance, AI models use pattern recognition and natural language processing.
• Retrieval and augmentation –  Instead of scanning a fixed index, engines access a mixture of training data and external knowledge. Google’s AI Overviews pull from indexed pages, while ChatGPT and Perplexity may call plug‑ins, search APIs or proprietary datasets. Personal data (e.g., calendar, email) can also refine responses.
• Generative synthesis –  Relevant facts are combined into a coherent narrative. Models decide how to answer (step‑by‑step explanation vs. bulleted summary) and may cite sources. Generative engines search for relevant answers and synthesize information into a straightforward response.
• Continuous learning –  Engines update their knowledge through user interactions. Feedback loops (clicks, dwell time, “thumbs up/down”) teach the model which answers are useful. LLMs integrate ongoing interactions, new data inputs and search results to adapt to recent events.

Understanding this workflow is essential because GEO aims to make your content easier for LLMs to discover, parse and cite during these steps.

What Is Generative Engine Optimization?

The goal of Generative Engine Optimization is to get content and digital assets ready so that generative engines can read and use them again. It’s not only about the number of keywords or backlinks; it’s also about providing content rich in context, well-organized, and clear in meaning so that AI models can use it to provide solutions.

The stakes are significant.

 Statista projects the global AI market to reach US$305.9 billion by 2025 (Source). A 2024 HubSpot report found that 61 % of marketers were already integrating generative AI tools into content workflows and 74 % of them reported increased engagement and better SEO performance.

Generative engines are moving from novelty to necessity.

If you want to learn more about how to make your content AI-ready, check out our GEO Guide.

GEO vs Traditional SEO

Search is no longer just about ranking well on Google – it is about being named in the answer. The purpose of both traditional SEO and Generative Engine Optimization (GEO) is to make things more visible, but they work in quite different ways. While SEO focuses on optimizing for human clicks from search engine results, GEO optimizes for AI systems that may deliver the answer directly to the user without a click.

Aspect	Traditional SEO	Generative Engine Optimization
Goal	Rank pages in search results and drive clicks	Secure citations and mentions in AI‑generated responses
Key signals	Keywords, backlinks, crawlability	Entities, structured data, conversational tone, context
User journey	Clicks on SERP listings lead to site visits	Users may receive answers without clicking, but they see cited brands
Metrics	Traffic, rankings, conversions	Frequency of brand citations, share of voice in AI answers
Platforms	Single platform (Google/Bing)	Multi‑platform (ChatGPT, Perplexity, Gemini, Copilot, DeepSeek etc.)

SEO is still important – roughly 75 % of links cited in Google’s AI Overviews come from the top 12 organic results. (Source)

However, relying solely on rankings is risky when AI summaries increasingly dominate the visible screen space. GEO fills in this gap by making sure that AI engines can access and trust your information. This way, your brand can be part of the conversation even when there are no clicks.

Why GEO Matters in 2025

The search landscape is going through its biggest transformation since Google first launched.

Generative AI is no longer just a side feature; it’s becoming the main way people look for information, weigh their options, and make choices. And these shifts are redefining what “visibility” means.

• Zero‑click search is rising –  AI Overviews now appear in up to 47 % of Google searches and occupy 75.7 % of the mobile screen (Source).

More and more users now read the AI summary and move on, meaning your content must be referenced within that summary to be seen.

• Generative engines are multi‑platform – ChatGPT, Perplexity, Gemini, and Bing Copilot process tens of millions of questions every day. Last year, ChatGPT even pulled ahead of Bing in traffic. People are no longer loyal to one search box – they are hopping between AI tools. And, to stay visible, your brand has to travel with them to each of those platforms.

• AI Overviews are expanding to all queries –   Google’s AI Overviews have already crossed 1 billion user mark and will soon appear for every query as part of a new experimental AI Mode.(Source)

Google also plans to integrate ads into AI Overviews, pushing organic results even further down. This means that soon ranking on page 1 will not be enough if your brand is not cited.

• Same Brand But Different Stories –  BrightEdge analysed thousands of prompts and found that ChatGPT and AI Overviews recommend the same brands 76 % of the time, yet they describe those brands differently.(Source)

ChatGPT uses functional language like “offers” or “provides” 3 × more often than AI Overviews. While ChatGPT behaves like a digital marketplace, AI Overviews emphasise more on competitive positioning and curated lists.

• Device Shapes the Experience –  Another report found that mobile AI Overviews appear three times more often for shopping queries than on desktop. While mobile feels like a guide for discovery, desktop focuses more on depth and details. If your content is not tuned for both, you are missing half the conversation.

These trends suggest that getting citations on all platforms is quite crucial. People used to care a lot about where they ranked in the SERPs, but that’s not the case today. The future is all about making sure that your brand is always included in AI-generated answers to questions that your audience asks.

The Building Blocks of GEO

Generative Engine Optimization or GEO is not about chasing every new AI platform – it’s about creating a repeatable system that ensures your brand is present, trusted, and easy for AI to reference.

A good GEO strategy combines the accuracy of technical SEO with the flexibility of content that is made for AI-driven discovery. You need to know how people ask questions, how AI engines pick sources, and how to organize your information so that it can be easily read and cited.

And, a well-rounded approach includes in-depth research, technical accuracy, storytelling backed by credible sources, and distribution across multiple channels to maximize reach.

1. Research & Analysis

GEO starts by understanding how users phrase questions and how AI engines answer them. Key steps include –

• Prompt and intent research –  Look beyond keywords to identify long‑tail questions, prompts and conversation patterns. Tools like Perplexity and ChatGPT can reveal how people ask questions in real language. Compare AI responses for your target topics to see which sources they cite.

• Competitive analysis –  Examine how competitors appear in generative engines. Are they being cited for specific facts, definitions, benchmarks, or data points? Identify the type of content or proof points earning them citations and use this insight to uncover content gaps you can fill to compete more effectively.

• Share of voice measurement. Track how often your brand appears in AI answers compared to competitors, and whether you are the first cited source or further down. Pair manual checks with custom reports in Google Analytics 4 to monitor traffic coming from generative engines. This helps you connect changes in your content to shifts in AI-driven visibility and site visits.

2. Structured, Semantic Content

Generative engines need content that is easy to parse, extract, and reuse in different contexts. Formatting matters as much as the information itself- tables, lists, TL;DR summaries, and FAQ sections make your content more “liftable.” Structured data (schema markup) adds another layer, giving AI clear context about entities – people, products, and organizations and improving discoverability.

Specific tactics include –

• Schema markups- Use formats like FAQ Page, How To, Person, and Product schema to help AI interpret relationships, roles, and attributes. This makes it easier for engines to surface the right snippet in the right context.

• Modular content design –  Create concise introductions, bullet points, and self-contained content blocks that can stand alone without losing meaning.

• Conversational tone –  Use natural language and Q&A formats to mirror how users ask questions. ChatGPT and similar engines tend to cite sources that answer questions directly with clear, unambiguous phrasing.

• Captions and alt text – Add descriptive captions and alt text to visual content. As multimodal AI models mature, they will pull information from these fields to answer queries.

3. Authority & Credibility

Generative engines favor authoritative, trustworthy sources, and GEO puts credibility at the core. Expert quotes, data points, and external references build the trust needed to earn citations.

To strengthen authority –

• Demonstrate E-E-A-T – Show expertise, experience, authoritativeness, and trust. Assign identifiable authors with clear bios, cite credible studies, and include relevant references so both users and AI engines see your content as reliable.

• Earn high-quality backlinks and media mentions – Traditional SEO still matters because generative engines often pull from top-ranking organic results. PR, guest contributions, and thought leadership in respected industry publications can increase the likelihood of being cited.

• Use accurate data and timely updates – Generative engines cross-check facts. Outdated or incorrect information can harm your credibility and reduce your chances of appearing in AI-generated answers.

4. Brand Mentions Across Platforms

GEO is inherently multi-platform. Building authority across different AI assistants increases your chances of being referenced, as tools like ChatGPT, Perplexity, and Gemini each have their own training data, indexing methods, and content preferences.

To build cross-platform visibility =

• Distribute content – Share your articles, whitepapers, and infographics in places where AI engines gather data – forums like Reddit and Quora, social networks like LinkedIn, and Q&A sites. Broader distribution expands the pool of sources that can be cited.

• Encourage reviews and user-generated content – Positive, detailed reviews on trusted platforms such as Amazon, Trustpilot, or G2 can influence AI-generated recommendations for both products and brands.

• Localize your information – Use structured data like Local Business and ensure accurate NAP (Name, Address, Phone) details to help generative models surface your brand for location-specific queries.

5. Technical Foundations

Without a strong technical foundation, even the best-crafted content can remain invisible to AI engines. Make sure you have –

• Fast, mobile-friendly sites – Page speed, responsive design, and clean URLs are still important ranking factors and directly affect user experience. A technically sound site increases the likelihood of your content being indexed and cited.

• Crawlability and accessibility – Use clear navigation, proper heading hierarchy, and avoid blocking AI or search engine bots in robots.txt. Generative engines rely on accessible, well-structured content to understand, index, and reference your site.

• Measurement infrastructure – Set up analytics to track generative AI traffic, conversions, and citations. This allows you to connect technical performance with GEO outcomes and continually optimize.

GEO vs AIO vs AEO

As AI reshapes search, three terms dominate the conversation – often used interchangeably but each with a distinct scope and purpose.

• GEO (Generative Engine Optimization) –  This is the practice of optimizing your content so it’s cited in generative AI answers across multiple platforms like ChatGPT, Perplexity, Gemini, Bing Copilot, and emerging assistants. GEO is multi-platform and measured by share of voice in AI-generated responses, as well as conversions from AI-driven referrals.

• AIO (AI Overviews) – A Google Search feature that generates a paragraph or list summarizing results at the top of the SERP. AIO is just one output of Google’s AI capabilities, so optimizing here means increasing your chances of being cited in Google’s summaries. It’s Google-only and performance is measured mainly by click-through rate and engagement on the search result.

• AEO (Answer Engine Optimization) – An older but still relevant concept that focuses on making your content answer-ready for search engines. Originally tied to featured snippets and voice search, AEO is about structuring content (tables, bullet points, FAQs) so engines can quickly extract direct answers – whether in traditional snippets or generative outputs.

Term	Scope	Primary Goal	Key Metrics
GEO	Multi-platform (ChatGPT, Perplexity, Gemini, Bing Copilot, etc.)	Be cited in AI-generated answers	Share of voice, AI-driven conversions
AIO	Google Search only	Be included in Google’s AI Overviews	CTR, engagement on SERP
AEO	Any search engine (traditional or AI)	Provide direct, answer-ready content	Snippet capture rate, answer accuracy

Strategic Imperatives for Marketing Leaders, Product Teams and Founders

As AI-driven search shifts the way people discover, compare, and choose products, businesses will need to adapt faster than their competitors to stay ahead.

Generative Engine Optimization is not just a marketing tactic – it’s a company-wide capability that touches SEO, content, product, and customer experience. The following imperatives shows how leaders across functions can prepare for this new discovery landscape –

• Embrace a unified content strategy – Research shows there is significant brand overlap between platforms like ChatGPT and Google’s AI Overviews. To be effective, you should plan write content that performs across multiple AI engines by combining three elements –
  • Functional benefits – What your product does and how it works.
  • Selection and variety – The range of options, use cases, and scenarios you serve.
  • Competitive positioning – Why you’re different and better than alternatives.

Avoid building separate websites for each AI interface. Instead, design modular content that can be adapted to different AI summaries.

• Understand the query landscape – Make sure your content matches what real users are looking for. Find out what kinds of questions cause AI Overviews to show up and how ChatGPT and Google summaries are different. For commercial questions, keep in mind that even small changes to the wording, like adding “buy online,” can greatly increase the chances of including a brand. Use these trigger patterns to make your copy and metadata better

• Develop mobile-first educational content – Mobile AI Overviews often serve an educational purpose at the beginning of the buying process. Make short guides, comparison tables, and explainer videos that help users quickly look at their options on small screens. Desktop users who are further along in their decision-making process should only have access to more technical information, long-form case studies, and in-depth resources.

• Measure what matters – Keyword rankings that are based on AI will become less important as AI-driven interfaces become the norm. Use analytics to keep track of how many people come to your site from ChatGPT and other AI assistants, how often people mention your brand in AI answers, and how many of those interactions lead to sales. Use available tools or make dashboards to keep GEO performance at the top of your mind.

• Invest in cross-functional collaboration – GEO sits at the intersection of SEO, content marketing, product documentation, and customer support. Product teams need to keep their specifications and FAQs up to date, marketing teams need to write interesting stories, and support teams can use real customer questions to help with research. Founders and executives should make sure that everyone in the company knows how to use AI.

• Prepare for AI Overview expansion and monetization – Google’s “AI Mode” and built-in ads will make it even harder to get organic citation spots. The fight for visibility will get even tougher as paid placements push organic mentions lower. So, the best thing to do is to start optimizing now to protect your place before monetization changes the AI Overview landscape.

Conclusion

Generative Engine Optimization is not just a buzzword,  it’s the next step in the evolution of digital visibility in an AI‑first world.

While traditional SEO taught us how to get people to find our websites, GEO teaches us how to make information understandable and usable by machines. As generative engines become the main way to search and find things, brands that know how to use these building blocks will be talked about, trusted, and remembered.

The path forward is clear but will demand extensive unlearning and relearning coupled with active experimentation. You will need to think beyond keyword rankings and start asking: Will an AI engine understand, trust, and reference this?

From here on , every other part of your strategy- research and analysis, technical readiness, authority building, multi-platform distribution, and measurement becomes a lever for that single goal –  being part of the AI conversation.

In a world where more answers arrive without a click, GEO ensures your brand still has a seat at the table.

Frequently Asked Questions

1. What’s the real difference between SEO and GEO?

SEO is about ranking pages for clicks. GEO is about getting cited inside AI-generated answers. One optimizes for SERPs, the other for machines that synthesize.

2. How do generative engines actually decide what to include in answers?

They parse queries, retrieve from training data plus external sources, synthesize into a coherent response, and learn from user feedback. They favor structured, clear, and frequently cited content.

3. Why might my brand rank on Google but not show up in AI Overviews or ChatGPT?

Because AI engines don’t just crawl rankings — they pull from schema, entities, trusted forums, review sites, and knowledge hubs. If you’re not cited there, you’re invisible.

4. What kind of content structure helps LLMs surface my brand?

Tables, lists, TL;DR summaries, schema markup, modular content blocks, and conversational Q&A formats. Anything easy for a model to “lift” into an answer.

5. How can I measure GEO performance if keywords don’t matter as much?

Track brand share of voice in AI answers, frequency of citations, referral traffic from AI assistants, and conversion rates from AI-driven discovery — not just keyword rankings.

6. Do mentions across platforms like Reddit or G2 really influence AI answers?

Yes. Generative engines lean on multi-platform signals. Positive reviews, forum mentions, and accurate Wikidata entries can carry more weight than a single blog post.

7. How should founders and product teams prepare for AI search expansion?

Adopt unified content strategies, align technical SEO with GEO signals, update product docs and FAQs, publish across multiple platforms, and measure AI visibility as rigorously as you once did rankings.