What’s Replacing SEO?
SEO is not disappearing, but it is evolving into something bigger: Generative Engine Optimization (GEO). GEO is the practice of making your brand visible and citable inside AI search results. Instead of fighting only for Google rankings, businesses now need to ensure that AI platforms like ChatGPT, Google Gemini, and Perplexity recognize and cite their content when answering user queries.
In other words: SEO helps you rank on Google, GEO makes you part of the answer in AI Search. Together, they form the new foundation of digital visibility.
In this guide, we’ll explore:
•How SEO and AI Search differ
•What GEO is and how it works
•Key strategies to implement it
•Why acting early matters for your business
"This is definitely an exciting opportunity. Early adopters of SEO reaped huge rewards in the 2000s; now early adopters of AI Search optimization (GEO) have a chance to leapfrog competitors. It’s not about throwing away your SEO playbook, but rewriting parts of it to include AI." Superlines' Growth Lead Hannes Jersenius.
How is traditional SEO different from AI search?
AI Search refers to platforms like ChatGPT, Google Gemini, and Perplexity that generate a single synthesized answer instead of showing a list of links. In traditional SEO, the goal is to rank as the top result on Google. In AI Search, the goal is to be part of the AI’s answer, cited or referenced as a trusted source.
Traditional SEO has always been about convincing Google you are the best answer through tactics like keywords, backlinks, and optimized metadata. With AI Search, the rules shift: You no longer compete for “10 blue links”, but instead you compete for inclusion in a single, authoritative response.
This creates a new challenge for businesses. If your brand’s information is not included in that AI-generated answer, it effectively disappears for that query and you risk losing market share by being invisible.
And the shift is already measurable:
- Google’s global market share fell below 90% at the end of 2024 and has remained under that line into mid-2025, the first time in nearly a decade.
- AI Overviews now appear in around 13% of Google searches, showing how quickly AI is being built into mainstream search.
- ChatGPT has reached 700 million weekly active users by July 2025, processing billions of prompts daily.
- Perplexity has surged to 153M monthly visits as of May 2025, a 192% increase from March 2024.
In plain English: search is no longer just “Googling.” AI Search is not replacing SEO overnight, but it is transforming how users find information. To stay visible, businesses must optimize not only for Google but also for AI assistants that are becoming everyday discovery engines. Google is also shifting toward an AI-first search experience, just more slowly due to legacy systems and ad dependencies.
What is Generative Engine Optimization (GEO)?
Generative Engine Optimization (GEO) is the practice of making your brand visible and citable inside AI-generated answers. Where SEO focuses on ranking web pages on Google, GEO ensures that platforms like ChatGPT, Perplexity, and Google Gemini recognize, trust, and reuse your content when they deliver responses to users.
In other words: SEO gets you seen in a list of links, while GEO gets you mentioned in the answer itself. Together, they form the new foundation of digital visibility.
Why GEO matters
AI assistants don’t rank results,they compose answers. To be included, your brand must be consistently present, structured, and credible across the web. That requires a different kind of optimization. GEO is less about keywords and backlinks, and more about creating signals that AI systems can easily parse, verify, and cite.
What are the core pillars of GEO
The five core pillars of GEO are:
1.AI-Optimized Content: Content written in a way that AI can directly reuse.
2.Structured Data and Metadata: Schema markup and clean metadata that make content easier for AI to parse.
3.Authority Signals Across the Web: Consistent mentions in credible sources that strengthen trust.
4.Consistent Presence in AI Channels: Accuracy and consistency across platforms and knowledge graphs.
5.Conversational Optimization: Q&A and natural-language formatting that match how people ask questions to AI.
Each of these pillars plays a specific role in how AI decides what to cite. Let’s look at them in more detail:
1. AI-Optimized Content
Content must be written in a way that AI can directly reuse. That means:
- Clear headings phrased as questions
- Concise, factual answers up front
- Supporting details and context afterward
- Bullet points and lists for easy extraction
Example: Instead of a marketing fluff headline, write “CRM software helps small businesses track customers, automate follow-ups, and integrate with email tools.” An AI can cite that sentence directly in its answer.
2. Structured Data and Metadata
Schema markup, meta descriptions, and clean site architecture help AI models disambiguate your content. FAQ schema, HowTo schema, and Product schema all increase the likelihood your page will be cited. According to Google’s documentation, structured results increase user engagement by up to 35% compared to plain listings, and for AI, structure is even more critical.
3. Authority Signals Across the Web
AIs rely on trust. While Wikipedia and government sources carry weight, a Superlines study of 1.5M citations found that 85–97% came from smaller sources: company blogs, product documentation, Q&A forums, and niche sites. This means being consistently mentioned across multiple ecosystems is often more important than a single big backlink.
4. Consistent Presence in AI Channels
Each assistant has its own preferences. Google AI Overviews leans on high-ranking web pages, while Alexa and Siri may pull from Wikipedia or knowledge graphs. GEO ensures your brand information is correct and consistent across all of these touchpoints, from directories and review sites to LinkedIn articles and press releases.
5. Conversational Optimization
AIs are trained on Q&A data from forums, FAQs, and natural conversations. Formatting content in that style with FAQs, direct definitions, or “Top 5” style lists increases the odds your brand is quoted. For example, a page that begins with “The best CRM for small businesses depends on budget, integrations, and ease of use” is more likely to be reused than a vague blog intro.
In essence, GEO is about making sure AI models “see” your content as authoritative and relevant when generating answers. It complements traditional SEO rather than replacing it. A successful digital strategy builds on SEO best practices and layers GEO frameworks on top, always with your target audience at the center. The goal is to provide clear answers and solutions to their problems, while optimizing with AI algorithms in mind. Before we dive into how, let’s look at how AI actually decides what to include in its answers, a process very different from Google’s ranking playbook.
What are the new ranking factors in AI Search?
AI assistants like ChatGPT, Gemini, and Perplexity do not rank pages 1 through 10. Instead, they select and synthesize information from multiple sources to generate a single answer. This means visibility depends less on exact keywords and backlinks, and more on clarity, authority, and structured signals that AI can easily reuse. Traditional SEO experts are familiar with ranking factors like keyword relevance, backlinks, domain authority, and engagement metrics. Google has even published guidance emphasizing content quality, technical health, and user experience. But when an AI composes an answer, the “ranking” process looks very different. Here are the key ways AI selection differs from Google’s traditional approach:
•Does ranking #1 still matter in AI Search?: As noted, an AI answer is synthesized from multiple sources. If Google search was a popularity contest to be the top result, AI Search is more like a research report, pulling bits of knowledge from many places. A site that might rank #5 on Google could still be the one quoted by an AI if it has the most succinct relevant info for a specific part of the answer. There’s less emphasis on one source dominating; instead, the AI cherry-picks facts and insights. Your goal is to provide the most relevant, quotable information for key queries so the AI includes it.
•Do keywords still matter for AI optimization?: AI models don’t look for exact keyword matches the way a search engine might. They “read” and understand content in context. This means the old trick of exact-match keywords repeated X times is far less effective (and could even be counterproductive if it makes your content read poorly). Generative AI understands natural language. For example, an article titled “How to Boost E-commerce Sales in 2025” might get picked up for a question about “increasing online store revenue” even if it doesn’t use that exact phrase, as long as the content clearly covers the concept. What counts is the depth and clarity of information, an AI will prefer a page that fully answers a question over one that just happens to contain the right keywords.
•How important is trust and authority in AI Search?: Extremely important. Just like Google relies on E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness), AI assistants prioritize content from credible, well-established sources. If your brand lacks visible authority signals, it is far less likely to be cited. Superlines’ research shows that over 75% of marketers believe online information quality has deteriorated because of spammy AI-generated content. This makes trust signals such as citations from reputable sources, consistent brand mentions, and high-quality publishing more important than ever.
Historically, AI models leaned heavily on Wikipedia, government sites, and other high-trust domains. As of September 2025, LLMs are increasingly conducting real-time web searches, which expands the range of sources they can pull from. This shift means fresh, well-structured content from authoritative sites now has a better chance of being surfaced in AI-generated answers, even if it is not from a traditional authority domain.
•Where do AI models pull information from?: Google mainly looks at the web (and some verticals like news, images, etc.) for ranking. AI models might draw from a wider array of data: social media chatter, databases, knowledge graphs, real-time information feeds, and so on. They might consider not just what your website says, but if your brand is mentioned frequently in certain contexts. For example, an AI summarizing “the best project management tools” might have seen many forum discussions or reviews praising a particular software, even if those didn’t all rank on Google and thus include it in an answer. In generative AI, being a well-known entity matters. SEO had already been moving in this direction (think of entity SEO or knowledge panels), but with AI it’s even more pronounced. If an AI has “heard” of your brand across many data points, it’s more likely to include it. In short, AI’s selection criteria extend beyond the web SEO signals to a more holistic view of what’s authoritative across the information ecosystem.
•Does structured data help with AI visibility?: We touched on this, but it’s worth reinforcing: content that is well-structured is easier for AI to use. If you have an article with a clear heading like “What is the average ROI of email marketing?” followed by a concise answer with a statistic, an AI can readily pull that snippet to answer a user question. Compare that to a wall of text buried in a PDF, an AI might ignore the latter. It’s not a “ranking factor” in the traditional sense, but it greatly influences whether your information makes it into the answer. In fact, Google’s AI Overview often highlights text from a page much like featured snippets do, meaning the same practices that got you featured snippets (direct, well-formulated answers on your pages) will help in AI answers. Bing’s AI chat cites sources with links, those links often come from content that was straightforward in answering the question. Bottom line: Make your content easy to parse. Use descriptive headings, bullet points, summaries, and FAQ sections. Think about the questions your audience might ask, and answer them directly in your content. For example, BrightEdge reports that AI Overviews now appear in over 11% of Google queries. While impressions have risen by ~49% year-over-year, click-through rates in those queries have dropped by ~30%. This shows how much user attention is shifting inside AI-generated answers and why clarity and structure are now critical ranking signals in GEO.
To illustrate these differences, think about how an AI might answer the query “What are the benefits of using a CRM for a small business?” Traditional SEO would focus on ranking an article titled “Top 10 Benefits of CRM for Small Business” and you’d fight to get that page to rank. An AI, on the other hand, might compile an answer like: “Using a CRM helps a small business by [benefit 1], [benefit 2], and [benefit 3]. According to HubSpot, businesses saw a 30% increase in sales after adopting a CRM , and a Salesforce report notes improved customer retention rates.” In that AI-generated answer, it might have pulled a stat from a HubSpot blog, a point from a Salesforce study, and perhaps a definition from Wikipedia, none of which might be the #1 Google result on their own, but each provided a key piece. Your strategy in this world is to provide those key pieces wherever you can (and to be one of those cited names).
The good news is many classic SEO best practices still apply. High-quality, relevant content remains essential. Technical SEO, ensuring your site can be crawled and that content loads fast, is still important (if an AI’s web browser can’t access your page or finds it too slow, you’re out). And user-focused content that addresses searcher intent is as valuable as ever. What’s changing is how that content is leveraged. We’re moving from an era of “optimize to rank for X” to “optimize to be included when an AI answers X.” It’s a subtle shift in thinking, but a profound shift in execution and tracking of the results.
How to be the source AIs cite
To be cited by AI assistants, your content needs to be direct, structured, and trustworthy so that models can confidently reuse it in their answers. Here are six strategies to make that happen:
1. Provide clear, direct answers AI can reuse
AI prefers concise statements that can be quoted without extra editing. Surface the answer at the top, then expand with supporting details. For example, if you run a tax advisory, don’t bury “The LLC tax filing deadline is April 15th in most cases” in paragraph 8, but instead put it upfront, then explain why. Original research or unique statistics are even stronger because AIs love citing numbers. If your annual report found “68% of consumers prefer chat support over phone,” that’s a quotable nugget.
2. Earn mentions on authoritative platforms
AI relies on signals of credibility across the web. Ensure your brand appears in trusted sources like Wikipedia, industry associations, or review sites. If you’re eligible, create a well-sourced Wikipedia page. For local businesses, reviews on Google Maps, Yelp, or TripAdvisor feed voice assistants directly. For B2B, being listed on G2 or Trustpilot helps. The wider the net of credible mentions, the more likely an AI will include you.
3. Format your content for easy quoting
Write in snippet-friendly ways so AI can lift content cleanly. Use definitions at the start of articles (“Generative Engine Optimization is the practice of…”), numbered lists (“5 ways to improve open rates”), and FAQs in natural language. Include descriptive alt text for charts or tables. The goal: make your content look like a ready-made answer key.
4. Use schema markup and clean structure
Schema markup and a clear HTML hierarchy make your content easier for AI to parse. Add FAQ, How-To, Product, or Article schema depending on your page. Keep one H1, logical sub-headers, and structured lists. For example, Product schema ensures an AI can confidently reuse your specs in its recommendation. Structured data isn’t just good SEO — it directly improves your chances of being quoted in AI results.
5. Measure your AI visibility continuously
You can’t improve what you don’t measure. Track how often your brand is cited across ChatGPT, Gemini, and Perplexity. Tools like Superlines automate this monitoring, showing not only where you appear but also what sources are driving it. The key is turning that data into action: updating weak content, targeting new sources, or filling gaps competitors are exploiting.
6. Prepare for voice and niche AI platforms
AI assistants go beyond text. Voice platforms like Alexa and Siri favor short, conversational answers, while niche AIs in travel, law, or healthcare pull from industry-specific databases. Optimizing for these means ensuring your listings and content are complete on vertical platforms (e.g., Booking.com for travel, G2 for software). Early adopters in these spaces gain the same outsized advantage SEO pioneers had in the 2000s.
What is the future of Search?
The future of search is hybrid: SEO + GEO. SEO preserves rankings, GEO secures citations inside AI answers. Brands that master both win full-funnel visibility. GEO also increases your chances of being included in Google AI Overviews and prepares you for Google’s broader shift toward an AI-first search experience.
SEO + GEO = complete digital visibility.
- SEO ensures technical health, quality content, and backlinks.
- GEO ensures your brand is included and cited by AI assistants across platforms like ChatGPT, Gemini, and Perplexity.
Gartner predicts that by 2028 many brands will see their organic search traffic drop by 50% or more as users shift toward generative AI-powered search. This makes adapting now urgent.
Here is how to future-proof your strategy today:
- Educate Your Team: Make sure SEO, content, and PR understand GEO and work together.
- Audit and Update Content: Refresh high-value content, add FAQs, answer new customer questions directly.
- Expand Analytics: Track both SEO metrics and new AI-driven visibility signals.
- Experiment with AI-Friendly Content: Publish authoritative reports or guides designed for AI citation.
- Stay Current: Follow updates from Google, Microsoft, and new AI players as best practices evolve.
Above all, maintain a user-first mindset. This was true for SEO and remains true for GEO. Companies that provide genuine value whether to a human reader or an AI summarizing content will lead in the AI era.
Get started with GEO today!
The companies that react to these changes now, will be the ones riding the wave of AI Search rather than getting swept beneath it. The ones that don’t…well, they might be left wondering why their traffic dried up while a nimble competitor made it as their primary growth channel. Don’t let that happen to you. SEO got a shiny new upgrade (much like Apple’s newest iOS update rolling out this fall). Time to download the update and keep moving forward.
If you want to explore your current visibility or exchange thoughts on this topic, feel free to contact us or connect with me on LinkedIn. I am always happy to discuss.
— Jere Meriluoto, CEO & Co-Founder of Superlines