From SEO to GEO – The Evolution of Search

Introduction

For over two decades, “search” has been practically synonymous with Google. The act of Googling became the default way people found information online ( ^[1] ). In that time, Search Engine Optimization (SEO) rose to dominate digital marketing, as businesses large and small vied for visibility in those all-important search results. But today, the search landscape is shifting under our feet. A new breed of AI-powered answer engines – led by generative models like ChatGPT – is changing how people seek answers.

Users are increasingly turning from traditional search engines to AI chatbots that deliver instant, conversational responses. This article examines how we got here, why generative AI is disrupting search as we know it, and what Generative Engine Optimization (GEO) means for marketers aiming to stay visible in this new era. We’ll explore the legacy of SEO, the seismic impact of AI on search behavior, define GEO in a marketing context, and explain why optimizing for AI-generated answers has become mission-critical in 2025.

The Legacy of SEO

SEO has been the backbone of online marketing for the past twenty years. Since the early 2000s, ranking high on search engine results pages (SERPs) – especially on Google – meant a flood of organic traffic and potential customers. In fact, an estimated 68% of online experiences begin with a search engine, underscoring how crucial search visibility has been for businesses ( ^[2] ). From finding a new restaurant to researching B2B software, users overwhelmingly turned to Google’s results, and companies invested heavily to appear at the top. Over the past 15+ years, SEO became a cornerstone of digital marketing, credited with powering startups to massive growth.

One analysis notes that SEO-centric strategies helped numerous startups and scaleups reach billion-dollar valuations ( ^[3] ). The formula was straightforward in concept: understand what keywords your audience is searching, create relevant content, and optimize your website’s technical factors and backlinks so that Google’s algorithm ranks you highly for those searches. Achieving a top organic ranking on a high-volume query could transform a business’s fortunes. Unlike paid ads, these clicks were “free” (after the upfront content and optimization effort), making SEO a high-ROI strategy for those who mastered it. 

The dominance of SEO in driving traffic is evident from industry data. Even as of a few years ago, organic search was the single largest driver of website traffic across most industries. For example, BrightEdge research found that in 2019, organic search accounted for 53% of trackable website traffic on average, far more than social media or other channels ( ^[4] ). Marketers often quoted “Page 1 or bust,” emphasizing that if you aren’t on the first page of Google results, your content might as well be invisible. This pressure to rank led to an entire ecosystem of SEO professionals, agencies, and tools devoted to understanding Google’s ever-changing ranking algorithms.

The SEO industry ballooned into a multi-billion dollar sector. By recent estimates, companies worldwide were spending nearly $80 billion on SEO by 2023, up from $47 billion in 2020 ( ^[5] ). This spend includes everything from hiring SEO experts and creating optimized content to investing in platforms like Moz, SEMrush, or Ahrefs for analytics. The rationale was clear: as long as search engines drove the lion’s share of web traffic, investing in SEO meant tapping into a huge audience. Over time, SEO best practices evolved (from keyword-stuffing in the early days to focusing on high-quality content and user experience today), but the end goal remained the same – get to the top of Google’s results.

It’s hard to overstate Google’s dominance in this era. Google became the default homepage of the internet for many. Capturing one of the top organic slots on a popular Google query could yield thousands or millions of monthly visitors. Marketers optimized for Google above all else, since Google has long held around 90%+ of the search engine market share globally ( ^[6] ). Microsoft’s Bing and others lagged far behind. Naturally, search engine optimization in practice largely meant Google optimization. This legacy of SEO is one of continuous adaptation.

Google constantly tweaked its algorithms (with major updates like Panda, Penguin, Hummingbird, RankBrain, and countless core updates), keeping SEO practitioners on their toes. Yet, despite these shifts, the fundamental premise held: if you publish valuable, relevant content and earn authority (through quality backlinks and references), your site can rank well and attract visitors from organic search. SEO became a standard discipline in marketing departments, alongside advertising and PR. For many businesses, organic search traffic became a key performance indicator (KPI) and a reliable source of leads or revenue. However, even before AI chatbots arrived, cracks in the traditional SEO model had begun to appear.

Google’s own changes started to reduce organic visibility – for instance, more ads and rich features now occupy the top of many search results, pushing organic links further down ( ^[7] ). By the late 2010s, Google was answering more queries directly on the results page (through Featured Snippets, Knowledge Panels, etc.), leading to a rise of “zero-click searches.” Studies found that over 60% of Google searches now end without any click to a website – users get their answer from Google’s snippet itself ( ^[8] ).

Even a #1 ranked page doesn’t guarantee a flood of traffic like it once did; the top result’s average click-through rate has fallen to around 27%, with the second result around 8% ( ^[9] ). This trend of users not needing to click a result was an early sign that the search landscape was shifting. Still, those snippets often pulled from websites (for example, a featured snippet quoting a line from a blog), so SEO experts adapted by optimizing for Answer Boxes and snippets – a tactic dubbed Answer Engine Optimization (AEO).

In essence, SEO was already evolving to feed answers directly to users via Google’s interface. In summary, the legacy of SEO is one of immense impact on digital marketing. It dominated the last two decades as the primary way to drive online visibility ( ^[10] ). Companies that cracked the SEO code reaped enormous rewards in traffic and sales, fueling the growth of an $80B industry. But just as marketers thought they had mastered the art of pleasing Google’s algorithms, a new disruption has emerged – one that doesn’t play by the old rules of web search.

AI Disrupts Search

A major upheaval began in late 2022 with the advent of powerful generative AI chatbots. OpenAI’s ChatGPT burst onto the scene and within months reached viral adoption. In fact, ChatGPT’s user growth was unprecedented – Morgan Stanley research noted it hit 100 million monthly active users faster than any consumer application in history ( ^[11] ). Practically overnight, millions of people started asking ChatGPT all sorts of questions, from coding help and academic research to advice and general knowledge.

For the first time, a significant number of users were getting direct answers from an AI instead of typing queries into Google. This shift has been swift. By early 2023, the buzz around AI chatbots grew so loud that Google’s management reportedly issued a “code red.” Internal teams were told to treat the rise of ChatGPT as an existential threat to Google’s core search business ( ^[12] ).

(To put that business in perspective: Google’s search advertising revenue was about $149 billion annually ( ^[13] ), so anything that might pull users away from Google search was a huge concern.)

Google wasn’t alone in noticing the trend – Microsoft invested heavily in OpenAI and quickly integrated GPT-4 into Bing, launching a new AI-enhanced Bing Chat in early 2023. For the first time in years, Google Search had a compelling alternative nipping at its heels, offering conversational answers integrated with search results. What’s driving this AI-fueled disruption? User experience. 

AI chatbots can deliver one-stop answers in a conversational format, which many users find more convenient than clicking through multiple links. For example, when someone asks ChatGPT “best project management tools for startups,” they receive a concise recommendation list with explanations – not a cluttered page of 10 blue links ( ^[14] ).

The AI filters out the noise and presents what it “thinks” is the best answer, often drawing from information across numerous sources. This means the user spends less time hunting and more time getting insights. It’s a fundamentally different paradigm of information retrieval – more of a dialogue than a traditional query-and-results process. Real-world data confirms that people are indeed shifting some of their search behavior to AI platforms. One major survey in early 2025 found that 27% of Americans now use AI chatbots like ChatGPT instead of search engines for at least some queries ( ^[15] ).

In the UK, similar numbers were reported, reflecting a broad international trend. And among younger, tech-savvy users, the preference for AI answers can be even higher. Another study by Elon University in 2025 revealed that half of U.S. adults have used an AI system like ChatGPT, Google’s Gemini, Anthropic’s Claude, or similar – and two-thirds of those users treat these tools like search engines to find information ( ^[16] ) ( ^[17] ). In other words, a sizable chunk of the population has already begun searching via chat interfaces. Users cite the speed and convenience of getting direct, context-rich answers. Rather than comb through several webpages, they can ask an AI and get a synthesized answer that feels tailored to their question ( ^[18] ). 

Generative AI tools like ChatGPT are rapidly becoming alternative gateways to information, often bypassing traditional search engines entirely. A 2025 survey found that more than a quarter of Americans now turn to AI chatbots (such as ChatGPT, Bing Chat, or Google’s Bard) instead of using Google for certain queries ( ^[15] ). This shift indicates that search behavior is moving from keyword queries toward conversational interactions, cracking the dominance of the classic “Google search” experience. 

Crucially, it’s not just ChatGPT in the game. Following OpenAI’s breakthrough, Google launched its own generative AI search initiatives . In mid-2023, Google unveiled the Search Generative Experience (SGE) – an AI-powered summary that appears at the top of search results for certain queries, synthesizing information with cited sources. They also rolled out Google Bard, a conversational AI, and invested in a next-gen language model called Gemini to power future search features. By late 2024, Google’s AI Overviews (the result of these efforts) were reaching over 1 billion users and expanding globally ( ^[19] ).

Google is effectively augmenting its familiar search results with AI-generated answers, so that users might not need to click external sites for many questions. Microsoft’s Bing, meanwhile, integrated OpenAI’s GPT-4 into Bing’s interface and saw a surge of interest, albeit from a smaller base. Other tech players jumped in as well – Meta released open-source LLMs like LLaMA that others could adapt, Anthropic pushed its Claude chatbot known for a very large context window, and in late 2023 xAI (Elon Musk’s AI venture) debuted “Grok”, an AI assistant with a bit of a personality.

Even Apple signaled moves in this space, announcing that AI-driven search engines (like a ChatGPT integration) would be offered as options via Siri ( ^[20] ). In short, the search market that was once basically Google, with a dash of Bing/Yahoo, is now fragmenting into a plethora of AI-driven alternatives . Some of these new AI search entrants are particularly noteworthy. 

Perplexity AI, for instance, launched as an AI-centric search engine that delivers answers with cited sources. It gained attention by providing a conversational interface with transparency about where information is coming from (something ChatGPT lacked initially). By early 2025, Perplexity’s usage was climbing rapidly – their daily active users grew 800% year-over-year to 15 million ( ^[11] ) – indicating real demand for AI-enhanced search tools.

Even OpenAI introduced a version of “ChatGPT search” (sometimes referred to as SearchGPT ) that allowed the chatbot to browse the web and present sources. In one month in late 2024, OpenAI’s own search referral traffic (people clicking out from ChatGPT’s answers to external websites) jumped 44%, while Perplexity’s grew 71% ( ^[21] ). These are small players compared to Google, but they’re growing fast. BrightEdge data noted that by 2025, ChatGPT’s built-in search functionality was on pace to capture about 1% of total search market share (in terms of query volume), which might sound tiny but would equate to a $1.2+ billion shift in value if realized ( ^[22] ).

All of this has profound implications for the $80B SEO ecosystem. As Andreessen Horowitz (a16z) quipped in a 2025 analysis, “The foundation of the $80 billion+ SEO market just cracked.” ( ^[20] )

The traditional model – optimize for Google, get traffic, get conversions – is being upended. If users no longer need to click links (or if they’re not even using Google to begin with), then the old playbook needs rewriting. We are essentially witnessing the end of “search as we knew it.” The familiar “ten blue links” on a Google results page are giving way to what one expert calls “direct answer engines” ( ^[23] ). In these new AI-powered search experiences, the engine doesn’t just rank websites, it composes an answer drawing from its trained knowledge or real-time web data. The user’s attention goes to the AI’s response, not necessarily to a specific website. If the AI’s answer happens to cite sources or suggest follow-up links, those become bonus visibility opportunities – but they are not guaranteed.

From a consumer standpoint, search is becoming more of a conversation. Instead of formulating the perfect keyword query, users can ask questions in natural language and even ask follow-ups for clarification. The AI will remember the context (to an extent) and refine answers. This conversational search approach was accelerated by ChatGPT’s mainstream moment ( ^[14] ).

Soon after, we saw multi-turn dialogue capabilities integrated into Bing and Google’s search UIs as well. The result is that the barriers between “searching” and “chatting” are blurring – a revolution in how we discover information. For online marketers, this is a disruptive change. The traffic streams long taken for granted may dwindle if more people get what they need from an AI’s answer.

Early evidence of impact can be seen in consumer behavior shifts: ask yourself, how often do you now receive an answer directly from Siri, Alexa, or an AI chatbot, without needing to scroll a website? That frequency is only increasing. Marketers have noticed instances of declining click-through rates when Google displays an AI-generated summary on top – users might get their answer from the summary and not scroll further. If this trend continues, optimizing solely for classic web search will no longer be enough.

Defining Generative Engine Optimization (GEO)

The rise of AI-driven answers has given birth to a new concept: Generative Engine Optimization (GEO) . Just as SEO is all about making your content visible and highly ranked on search engines, GEO is about making your content visible and favored by generative AI answer engines . In other words, how do you ensure that when an AI like ChatGPT, Bard (Gemini), Claude, or Bing Chat is answering questions in your domain, it includes your brand’s knowledge, content, or offerings in its response? GEO is the discipline of optimizing content for AI systems that generate responses, rather than simply for indexing and ranking links on a page ( ^[24] ).

Let’s unpack that. A traditional search engine (Google) uses a crawler and an index, matches keywords to documents, and ranks those documents (webpages) based on relevance and authority signals. If you did good SEO, your webpage might rank #1 and users clicking that result would see your content. A generative AI, on the other hand, might have read your webpage during its training or via real-time search, and when asked a question, it might pull information from it – not by showing the user your webpage, but by weaving the info into its own answered text.

The user might not ever visit your site or even know the answer came from you unless the AI explicitly cites sources (and not all do, or they might cite only a few of many sources). Optimizing for these AI platforms requires new strategies . It’s about ensuring the AI knows about your content and trusts it enough to use in answers, and ideally that it cites or attributes your brand so the user is aware of your contribution. In practical terms, GEO involves several facets, many of which are still being figured out by the industry.

At its core, it means creating content and site structures that AI can easily ingest, understand, and regurgitate accurately . Some aspects include: using clear, structured formats (so that facts or instructions from your content can be extracted correctly), maintaining strong credibility (so that AI models consider your content authoritative and worth including), and providing fresh, up-to-date information (since AI systems, especially those with real-time retrieval, favor current data for many queries ( ^[25] )).

GEO also means considering how an AI prioritizes information . Unlike Google’s algorithm, which heavily weights backlinks and keywords, an AI model might prioritize contextual relevance or factual accuracy . For instance, AI engines often cite official studies, data, or highly authoritative sources even if those didn’t rank high in Google ( ^[26] ). This suggests that in the GEO era, creating genuinely authoritative content (research, whitepapers, expert insights) can pay off even more, as the AI may latch onto those facts.

Another difference is personalization across AI systems. Each AI platform has its own way of sourcing and presenting info. As one analyst observed, “Every AI model prioritises different signals. ChatGPT values semantic depth, Perplexity emphasizes structured data, [Google] Gemini takes a trust-first approach. Optimising for AI feels like targeting a million different search engines.” ( ^[27] )

In SEO we mainly optimized for one dominant algorithm (Google’s). In GEO, we might need to consider multiple AIs – e.g., ensuring our content is formatted with schema markup and sources (helpful for Bing/Perplexity which value citations), written with rich context and detail (helpful for ChatGPT’s style), and backed by trustworthy reputations (helpful for Google’s SGE/Bard). This fragmentation adds complexity: GEO isn’t a single algorithm to game, but a spectrum of AI behaviors to accommodate.

So how do we practically define success in GEO? The basic idea is your brand becomes part of the AI-generated answer . Suppose someone asks an AI, “What are the top security software for small businesses?” Under the old model, success is if your company’s website ranks on page 1 of Google for “security software small business.” Under GEO, success might look like: the AI’s answer text says, “You should consider XYZ Security Suite (by YourCompany) as it’s highly rated for small businesses…” or the AI cites YourCompany’s blog as a source of expert information on the topic.

In either case, the user is exposed to your brand within the answer itself . It’s a win even if they don’t immediately click a link, because your brand entered their consideration via the AI’s recommendation. This is fundamentally what GEO aims to achieve – to maintain brand visibility when the “answers” are coming from an algorithmic interlocutor instead of a list of web links .

It’s worth noting that GEO builds on some concepts from earlier in the search evolution. A few years back, marketers started talking about Answer Engine Optimization (AEO) – optimizing for featured snippets and voice assistant answers (like Siri/Alexa responses). GEO is like AEO on steroids, expanded to all generative models and chat-style interactions. With voice search and snippet optimization, you were still often trying to get a specific bite-sized answer from your site to be showcased (for example, a definition or step-by-step list).

GEO encompasses that but also the broader goal of being woven into AI’s knowledge base . It’s not always a one-shot factual snippet; it could be being referenced as an authority or having your data used in an AI’s explanation. We are still in the early days of formalizing GEO tactics, but it’s clearly emerging as a parallel to SEO.

In May 2025, one industry commentator declared, “We’re witnessing the birth of Generative Engine Optimization – a new discipline that will be as important as SEO was for the last two decades.” ( ^[10] ) Forward-thinking marketing teams are already experimenting with techniques: injecting likely Q&A prompts into their content, publishing FAQ-style pages that match conversational queries, ensuring their content is included in public knowledge bases (like Wikipedia or scholarly databases) that AI models are known to scrape, and even using the AI tools themselves to audit whether and how their brand appears in answers ( ^[28] ).

We’ll delve into specific strategies in later articles, but the key point here is that GEO is about influence without a click. It asks: Will the AI mention or recommend us? – a very different question from Can we rank and get a click? The concept of Generative Engine Optimization (GEO) centers on ensuring your content is favored by AI-driven answer engines. Rather than competing for a top spot on a search results page, GEO is about earning a place in the AI’s generated response itself ( ^[29] ). This means creating authoritative, well-structured content that conversational AI systems trust and cite. As AI search grows, GEO is becoming the new frontier of digital visibility, where the goal is to have your brand’s information seamlessly woven into the answers that chatbots and AI assistants provide.

Why GEO Matters Now

The urgency around GEO is growing by the day. We are witnessing a rapid pivot in how consumers find information – a pivot that could leave traditional SEO-reliant strategies in the dust if businesses don’t adapt.

Here are several key reasons why GEO demands attention right now : Users are bypassing traditional search :

As discussed, a significant and growing percentage of users are going straight to AI assistants for answers. If one-quarter or more of searches shift to AI by 2025–2026 (as Gartner predicts about 30% by 2026 ( ^[30] )), that’s a huge chunk of queries where the Google SERP might not even be seen. If your marketing strategy today is 100% based on getting clicks from Google, you risk losing reach as those eyeballs move to chat-based interfaces.

GEO matters because it’s the way to regain visibility in those interactions. It’s no longer hypothetical – over 50% of U.S. adults have now used an AI chatbot, and many use them like search tools ( ^[16] ) ( ^[17] ). This trend will only accelerate as AI becomes integrated into smartphones, virtual assistants, and everyday apps. 

The rise of zero-click answers : Even within traditional search engines, the trend is toward answers without clicks . Google’s introduction of features like featured snippets, Knowledge Graph panels, and now AI Overviews means users can often get what they need without leaving Google at all. By 2024, about 60% of Google searches ended without any click to external content ( ^[8] ). With AI-generated answers (which are even richer and more comprehensive than a simple snippet), the proportion of zero-click experiences could climb higher. For marketers, this means that even if people use Google, they might not be visiting your site unless your information is part of Google’s answer. GEO is about making sure your information is that answer . It’s a direct response to the zero-click phenomenon – if the user won’t click out, you need your brand to live inside the answer unit. 

New traffic and branding pathways : While an AI answer might not send a click, it can send customers . For example, if an AI assistant recommends a particular product (say, “The user asks: what is the best noise-cancelling headphone?” and the AI responds with a short list of models), being named in that list is invaluable brand exposure. A user might then directly navigate to your site or search your brand name later – an attribution path that is hard to track but very real ( ^[31] ). This is what some have dubbed the “attribution black hole” of AI: customers influenced by AI recommendations who convert later via direct or brand search traffic. GEO matters because it positions your brand to be in those crucial AI-driven recommendations. In essence, GEO can drive implicit traffic and demand, even if it’s not the classic referral click. Ignoring it means ceding those invisible opportunities to competitors. 

Competitors (including new ones) are seizing AI visibility: One startling observation in the post-ChatGPT world is that the brands dominating AI answers aren’t always the ones that dominated SEO. Unknown or niche competitors who have content structured well for AI can suddenly surface in answers where bigger SEO players are absent ( ^[32] ). If your competitor’s content is being used by the AI to formulate answers and yours isn’t, they effectively become the voice that consumers hear.

Early adopters of GEO tactics are likely already gaining an edge. This is especially true in industries where factual data or community Q&A content (like StackExchange, Wikipedia, etc.) feed the AI – a smaller player who happens to be active on those platforms might be all over AI answers. GEO is the proactive response to ensureyou don’t become invisible in the new landscape while agile competitors leapfrog you in AI presence.

AI integration is everywhere: Beyond just search engines, consider how generative AI is creeping into many consumer touchpoints. AI chat is being built into smart home devices, office productivity tools, customer service bots, and more. If a user asks their AI-powered personal assistant, “Book me a flight and hotel for Athens next weekend,” and the assistant uses generative AI to recommend options, travel brands will want to have their offerings included.

This extends to virtually every domain – personal AI assistants could soon handle a large share of queries that traditionally would be web searches ( ^[30] ). GEO principles (making sure the AI has your data, and cites your services) will apply in all these contexts. In short, the future of discovery isn’t just a search engine results page; it’s ambient AI-driven discovery . Ensuring your content is AI-friendly now is what will keep you discoverable as this future arrives. 

Trust and accuracy considerations : It’s worth noting that AI answers, while convenient, bring along issues of accuracy (hallucinations) and bias. As a brand, one might fear being misrepresented by an AI or omitted due to some quirk of the model’s training data. Engaging in GEO isn’t just an opportunity; it’s also a defensive move. By actively optimizing and providing reliable, well-structured information, you increase the chances that AIs will pull correct info about your brand (rather than outdated or incorrect data). For instance, if your product pricing or specs aren’t clearly available in structured form, an AI might scrape a third-party site and give a wrong answer. 

GEO involves feeding the AI ecosystem with accurate data about your brand – through schema markup, data feeds, or updated web content – to mitigate misinformation. Given that generative models sometimes “make up” answers, having your authoritative content in their training or retrieval sources is crucial to ensure factual representation. In summary, GEO matters now because user behavior has already changed and the platforms are quickly following. The search and discovery ecosystem in 2025 is not the one we knew in 2020. We’re at an inflection point where AI-driven answers are becoming mainstream, and businesses must adapt or risk losing visibility.

As one SEO expert put it, the task ahead is not just to capture traffic from search engines, but to become the source that AI engines cite and recommend ( ^[33] ). That is the essence of GEO. It’s the next blog post in the evolution of search marketing, picking up where traditional SEO leaves off. Companies that recognize this shift early and integrate GEO strategies stand to maintain and even grow their reach in the age of AI. Those that don’t may find themselves witnessing their hard-earned Google rankings bringing diminishing returns, as the audience simply bypasses the old pathways. 

Closing thought: The evolution from SEO to GEO represents a fundamental change in how we approach online visibility. SEO isn’t dead – far from it. Traditional search still drives massive value, and Google isn’t going away overnight ( ^[6] ). But the playing field is expanding . It now includes AI chatbots, voice assistants, and other generative experiences as additional “front doors” through which customers will find information. Marketers need to broaden their optimization efforts accordingly. The following articles will dive deeper into how SEO is converging with new practices like Answer Engine Optimization and Large Language Model Optimization, the inner workings of LLMs like ChatGPT and Google’s Gemini, and practical strategies to thrive in this new environment. The key takeaway for now is: search is no longer just about being ranked, it’s about being referenced . GEO is about ensuring that when the answers are generated, your brand’s voice is part of the conversation ( ^[14] ) ( ^[29] ).

The evolution of search has begun – and it’s time for marketers to evolve with it.