Why the biggest upheaval since the invention of the search engine is happening now – and what you need to do to stay visible
The way people search for information on the internet is changing fundamentally. What was considered immovable for over two decades – the ten blue links on the Google results page – is being replaced at breathtaking speed by a new reality: AI-powered search systems that provide answers directly instead of just pointing to websites. Google AI Overviews, ChatGPT Search, Claude, Perplexity, Microsoft Copilot and Gemini are changing the playing field for any business that wants to be visible online. The key question is no longer whether this change is coming – it’s already here. The question is: Is your website prepared for it?
This article gives you a comprehensive overview of the new landscape of AI-powered search, explains the technical and content requirements that your website needs to fulfill and provides concrete recommendations for practical action. Whether you run a small business, manage a marketing department or work as a web developer, here’s what to do now.
1 The new search landscape: what has changed
1.1 The rise of AI search assistants
The figures speak for themselves. ChatGPT now processes around 2.5 billion queries per day, with an estimated third of these being classic information searches. Google still processes around 16.4 billion search queries a day and therefore remains the dominant player, but the dynamics are clear: AI-supported search is growing rapidly. AI platforms such as ChatGPT and Perplexity already accounted for 5.6 percent of desktop search traffic in the US in mid-2025 – more than double the figure from just one year earlier. Among early adopters, AI tools even reached a 40 percent share of desktop visits, while Google and Bing dropped to around 61 percent.
At the same time, usage is increasing rapidly: around 34% of US adults have already used ChatGPT, and the figure is as high as 58% among the under-30s. Around 20 percent of Americans are considered heavy LLM users, using ChatGPT, Perplexity, Claude, Copilot, Gemini or DeepSeek more than ten times a month. And even though AI search traffic is still relatively small in terms of overall volume – on average, it currently accounts for just over one percent of total website traffic – the conversion rate is remarkably high.
1.2 Higher conversion rates through AI traffic
An analysis of twelve million website visits shows that AI traffic has four to five times higher conversion rates than Google traffic. The average conversion rate of AI visitors is 14.2 percent, compared to 2.8 percent for Google visitors. Of particular note: Claude users convert at the highest rate of 16.8 percent, followed by ChatGPT users at 14.2 percent and Perplexity users at 12.4 percent.
The reason for this conversion advantage lies in the change in user behavior: AI users have already done their research, compared alternatives and refined their requirements while talking to the AI assistant. By the time they click on your website, they are already much further along in the purchasing process. They know what they want – and they’re ready to act.
1.3 Google AI Overviews and the consequences for click traffic
But there is also a downside to this development. Google’s AI overviews are dramatically changing click behavior. Studies show that users click 47 percent less on search results with AI overviews – the click rate drops from 15 percent to just 8 percent. Even more remarkable: 26 percent of users end their browser session completely after receiving an AI-generated answer, compared to only 16 percent without AI overviews. So-called “zero-click search” – i.e. search queries where the user never visits a website – is thus taking on a whole new dimension.
1.4 A new triangle: users, AI and content
The most fundamental change concerns the relationship between users, content and search systems. In traditional search, users interacted directly with websites. The search engine was merely an intermediary that guided the user to the right page. In AI-supported search, the AI becomes both gatekeeper and referee. It has a direct relationship with the user and decides which content is cited, summarized or recommended – and which is not.
This means that your website is no longer just competing for a place in the search results. It is competing to be recognized by AI systems as a trustworthy, authoritative and relevant source. And that requires a fundamentally different approach.
2. generative engine optimization (GEO): The new SEO
2.1 What is GEO?
Generative Engine Optimization, or GEO for short, is the practice of designing and optimizing web content so that it is cited, referenced and recommended by AI-powered search systems. While traditional SEO focused on ranking in search engine results pages (SERPs), GEO aims to get your content to appear in AI-generated responses. Industry surveys show that the term “AI SEO” is becoming the umbrella term for this discipline, with “Generative Engine Optimization” also gaining traction.
The key difference: traditional SEO was about bringing users to your website. GEO is about ensuring that your content, your expertise and your brand are present in the responses of AI systems – regardless of whether the user ever visits your website directly.
2.2 How AI search systems select content
To optimize for AI systems, you need to understand how these systems work. Most modern AI search tools use a technology called Retrieval Augmented Generation (RAG). Put simply, it works like this: when a user asks a question, the system first searches for relevant documents in an extensive knowledge database or on the internet. These are then passed to the language model as context, which generates a coherent answer.
Google co-founder Sergey Brin describes the process of Google’s AI as follows: The AI first retrieves the thousand most relevant search results, then performs follow-up searches to refine and analyze the results, and finally generates a structured response from them. This process means that several factors determine whether your content is cited by an AI: the semantic relevance of your content to the query, the quality and authority of your website, the structure and machine readability of your content, and the timeliness and trustworthiness of the information provided.
2.3 The difference between AI search and traditional search
An analysis of over 41 million AI search results found that ChatGPT’s results overlap with traditional Google search results only 12 percent of the time. Even with Bing – the search engine that powers ChatGPT’s browsing functionality – the overlap is only 26 percent. This minimal overlap confirms an important finding: optimizing only for traditional search engines does not guarantee visibility in AI search results. Google AI Overviews and Google’s AI Mode also cite different sources, with only 13.7 percent of citations matching in both functions.
It is also worth noting that AI recommendations are highly inconsistent: The probability that ChatGPT or Google’s AI will deliver the same list of brands twice when asked a hundred times is less than one percent. This means that AI visibility is not a static state, but a dynamic process that requires continuous attention.
3. technical basics: how to make your website AI-compatible
3.1 Structured data and schema markup
Structured data is the key to helping AI systems not only read but also understand the content of your website. Schema markup – a standardized vocabulary that you insert into the HTML code of your website – allows search engines and AI systems to accurately capture the meaning of your content. While traditional SEO already utilized schema markup, it takes on a whole new meaning in the era of AI search. Industry surveys show that structured data and schema are the most commonly cited methods for optimizing for AI search.
The main schema types for AI optimization include different categories, each addressing different aspects of your online presence:
Organization Schema anchors your brand identity and gives AI systems the structured data to consistently recognize and reference your brand. This is where you define your company’s name, logo, address, contact details and social media profiles.
Article and BlogPosting schema clarify key content attributes such as publication date, author and topic. These signals reinforce the authority and timeliness of your content, which influences how AI systems consider your content in their responses.
FAQPage schema identifies individual question-answer pairs and makes it easy for AI systems to quote them in conversational answers. Structured question-answer content is particularly easy for AI systems to interpret.
Product and Service Schema provides detailed information about your offerings, including pricing, availability and reviews. When AI systems can access this data, the likelihood of your products or services being recommended in relevant responses increases.
LocalBusiness Schema is particularly important for local businesses. It tells AI systems that it is a physical business and provides location information, opening hours and contact details. Local-related queries trigger a web search on ChatGPT in 59% of all cases – a huge opportunity for local businesses.
Implementing schema markup requires precision: Incorrect markup can confuse AI systems and reduce rather than improve the visibility of your content. Use validation tools such as the Google Rich Results Test to ensure that your markup is implemented correctly.
3.2 The llms.txt file: The new robots.txt for AI
In the tradition of robots.txt and sitemap.xml, a new standard has been established: the llms.txt file. This text file, which is hosted in the root directory of your domain (i.e. at yourdomain.ch/llms.txt), is aimed specifically at AI crawlers and large language models.
The llms.txt file fulfills several functions: It lists your most important pages in priority order, contains brief descriptions of what each resource contains, links to canonical URLs and gives AI systems clues as to which parts of your website are particularly relevant and trustworthy. This allows retrieval systems to directly access the right pages instead of having to work their way through your entire website.
The practical implementation is relatively simple: create a text file, list your most important pages in order of priority (one URL per line or as a short curated list), add short annotations describing what each resource contains, use canonical URLs and keep the file up to date as your site structure changes.
For WordPress users, there are already plugins such as Rank Math Pro that simplify the creation and maintenance of an llms.txt file. Regardless of the CMS, the llms.txt file should be considered an integral part of your technical SEO strategy.
3.3 Technical website performance and crawlability
The technical foundations of a website remain crucial in the era of AI search. Make sure that AI crawlers can easily crawl your website. Review your robots.txt file and make sure it allows access for AI crawlers such as OAI-SearchBot (OpenAI/ChatGPT), Google-Extended (Gemini), anthropic-ai (Claude) and PerplexityBot. Regularly update your XML sitemaps to ensure that all relevant content can be found.
Page speed and user experience also play a role. A fast, responsive website with a seamless user experience increases the likelihood that your content will be included in AI search results. Engagement metrics such as dwell time and bounce rate signal to both traditional search engines and AI systems that your content offers added value.
Optimize images with compression and modern formats like WebP, make sure your website works properly on all devices, and ensure fast loading times. Google itself continues to emphasize the same basic recommendations: unique, valuable content for people, a great site experience, making sure crawlers can access your content, and managing visibility with preview settings.
3.4 HTML-first architecture
AI systems process content primarily as text. Websites that rely heavily on JavaScript rendering, single-page applications or dynamically loaded content run the risk of not being fully captured by AI crawlers. An HTML-first approach ensures that your most important content is available directly in the HTML source code without the need to execute JavaScript.
This does not mean that you have to do without modern web technologies. It does mean that you should ensure that the essential content of your pages is contained in the initial HTML document. Server-Side Rendering (SSR) or Static Site Generation (SSG) are proven approaches that are beneficial for both AI crawlers and general search engine optimization.
4. content optimization: What AI systems prefer
4.1 Clear structure and semantic organization
AI systems process content as tokens – small fragments of text – and rely on patterns and relationships to understand the meaning. They do not look at individual keywords, but at the overall flow, context and structure of the content. When a model is asked a question, it retrieves the most relevant sections of text, identifies the clearest passages and uses them to generate an answer. This is why structured, clear content is much more likely to be included in AI-generated answers than long, unstructured blocks of text.
Use a clear heading hierarchy (H1, H2, H3, H4) that structures the content logically. Use short, concise paragraphs and format key information so that it is easy to extract. Incorporate question-and-answer formats, as AI systems often replicate content that follows this pattern. Platforms such as Quora and Reddit, which have a clear question-and-answer structure, are particularly frequently used as sources by Google AI Overviews.
An interesting finding from the research: 44.2 percent of all AI citations come from the first 30 percent of a text, i.e. from the introduction. 31.1 percent come from the middle section and 24.7 percent from the last third. This means: place your most important statements, facts and key messages at the beginning of your content.
4.2 E-E-A-T: Experience, expertise, authority and trustworthiness
Google’s E-E-A-T concept (Experience, Expertise, Authoritativeness, Trustworthiness) is more important than ever in the AI era. AI systems derive trustworthiness from multiple signals and thus apply an equivalent of E-E-A-T to AI search.
Show your experience by enriching your content with personal experience reports, case studies and practical examples. Show that there are people with real experience behind your content.
You demonstrate expertise through in-depth, technically sound content. Superficial summaries are not enough. AI systems prefer content that deals with a topic comprehensively and with recognizable expertise.
You build authority by being perceived as a recognized source in your field. This is done through specialist publications, mentions in the media, backlinks from trustworthy sources and a consistent presence in your subject area.
You signal trustworthiness through transparency, correct sources, up-to-date information and a professional online presence. Particularly high standards of trust and authority apply to YMYL inquiries (Your Money or Your Life – topics relating to health, finance or security).
4.3 Topic clusters and depth of content
Instead of creating individual, isolated pages, you should create topic clusters (topic hubs). A topic cluster consists of a central pillar page that comprehensively covers an overarching topic and several detailed subpages that go into more depth on individual aspects. All pages are linked to each other and thus form a semantic network that helps AI systems to recognize your expertise in a specific topic area.
This approach is not new – it has been a best practice in content marketing for years. In the AI era, however, it is becoming even more important because AI systems are able to capture the thematic depth and breadth of a website and evaluate it as a signal of expertise.
4.4 Unique findings and original data
AI systems prefer content that offers unique insights, original data or new perspectives. Generic content that simply repeats existing information is less likely to be cited. Invest in your own studies, surveys, analyses and case studies. Publish industry reports based on your own data. Share expert opinions and practical experience that cannot be found elsewhere.
Original content has a double benefit: not only is it cited more often by AI systems, but it also attracts more backlinks and mentions, which in turn boosts your website’s authority.
4.5 Up-to-dateness and regular maintenance
AI-supported search systems prefer up-to-date content because users expect the most up-to-date and accurate information. Regularly updating your content is therefore not a one-off task, but a continuous process.
Update existing articles with new statistics, industry trends and case studies. Integrate current examples from practice. Adjust the publication or update date if you have made significant changes. Both search engines and AI systems often prioritize content that is marked as recently updated. Content freshness algorithms in AI systems increasingly favor regularly updated, actively maintained websites.
5. off-page factors: reputation and visibility beyond your own website
5.1 Brand mentions and citations
Brand mentions and citations on third-party sites play a central role in AI search. AI systems use various aggregators to form an overall picture of what searchers value most. If your brand is mentioned, cited and recommended on trusted platforms, AI systems are more likely to consider you in their responses.
Strive to get your facts and expertise into the trusted public sphere. This can mean contributing to Wikipedia (with neutrality and sourcing), ensuring journalists or analysts have accurate information about your company, and maintaining accurate information in knowledge panels such as the Google Business Profile.
5.2 Ratings and social proof
Online reviews not only influence human purchasing decisions, but also the way in which AI systems evaluate and recommend companies. AI models analyze reviews to assess the quality of products and services. A strong review base on platforms such as Google, Trustpilot or industry-specific portals signals to AI systems that your company is trustworthy.
Although social sentiment – the general mood in social media and online forums – is currently the least weighted factor in the recommendation algorithm of ChatGPT and similar systems, it can make all the difference in competitive markets. It is to be expected that the importance of social sentiment will continue to increase in future updates of AI algorithms.
5.3 Backlinks and digital authority
Even if the importance of backlinks is weighted differently in AI search than in traditional search, they remain an important signal of authority and trustworthiness. High-quality backlinks from recognized sources – trade publications, industry associations, universities, news media – strengthen the perception of your website as an authoritative source.
Invest in relationships with journalists, industry experts and trade publications. Create content that is so valuable that others will voluntarily link to and share it. Guest posts in recognized trade media can also help boost your visibility and authority.
6 Special challenges for different industries
6.1 Local companies
For local businesses – restaurants, craftsmen, doctors, lawyers, retailers – AI search offers particular opportunities and challenges. As already mentioned, requests with a local connection trigger a web search on ChatGPT in 59 percent of all cases. This means that local businesses have an above-average chance of appearing in AI responses – provided they are positioned correctly.
Maintain your Google Business Profile carefully and keep all information up to date. Implement LocalBusiness schema on your website. Make sure your NAP data (name, address, phone) is consistent across all platforms. Actively collect reviews and respond professionally to feedback. Create local content that connects your region and expertise.
6.2 E-commerce and online stores
AI optimization is particularly relevant for e-commerce companies, as ChatGPTs’ most common use cases are practical instructions (29 percent) and information searches (24 percent) – both areas in which product recommendations play a central role.
Implement a comprehensive product schema with prices, availability, ratings and detailed product descriptions. Create buying guides, comparison articles and FAQ pages that answer typical customer questions. Use Offer Schema to clearly communicate to AI systems what users can buy or book from you.
6.3 B2B companies and SaaS
B2B companies and SaaS providers should optimize their help documentation, feature pages and thought leadership content for AI visibility. AI systems are increasingly being used to research and compare B2B solutions. Detailed, well-structured product documentation, integration guides and technical resources form the foundation here.
6.4 Healthcare, finance and legal services (YMYL)
Industries that fall under Google’s YMYL (Your Money or Your Life) criteria are subject to particularly strict requirements. AI systems must rely on highly trustworthy sources for these topics. Make sure that your content is written or reviewed by qualified professionals, that author profiles include qualifications and experience, and that all facts are backed up with reputable sources.
7. monitoring and measurement: tracking AI visibility
7.1 New metrics for a new era
Measuring your AI visibility requires new tools and metrics. While you track rankings, organic traffic and click-through rates for traditional SEO, you also need to monitor the following aspects for AI search: How often is your brand mentioned in AI-generated responses? Which of your pages are cited as sources? How does your brand perform compared to competitors in AI responses? Which queries are causing AI systems to refer to your content?
7.2 Specialized tools
There are now specialized platforms that allow you to monitor your AI visibility. These tools automatically track brand mentions and website citations on platforms such as Google AI Overviews, ChatGPT, Perplexity, Gemini and Microsoft Copilot. They provide competitive analysis, show what content is being cited and make recommendations for optimization. Some of these platforms analyze more than 25 on-page factors to identify weaknesses in AI visibility and make concrete suggestions for improvement.
7.3 Integrated tracking
It’s crucial to track both traditional organic traffic and AI platform referrals to get a complete picture of your search visibility. Set up separate segments for AI traffic in your analytics tools. Identify referrers such as ChatGPT, Perplexity, Claude and Copilot. Compare conversion rates between traditional and AI traffic. Only those who measure can optimize.
8 Practical guide: Your AI readiness checklist
8.1 Technical measures
The following list gives you an overview of the technical measures you should take:
Check your robots.txt file and make sure that AI crawlers have access. Create an llms.txt file with your most important pages and resources. Implement comprehensive schema markup for organization, products, services, FAQs and articles. Validate your schema markup regularly with the Google Rich Results Test. Ensure that your most important content is available in HTML source code without the need for JavaScript. Optimize the loading speed of your website on all devices. Update your XML sitemaps regularly and ensure a clear URL structure. Implement HTTPS and ensure a secure, trustworthy website infrastructure.
8.2 Content-related measures
On the content side, you should consider the following points:
Structure your content clearly with heading hierarchies, paragraphs and question-and-answer formats. Place the most important information and key messages at the beginning of your texts. Create topic clusters with pillar pages and detailed subpages. Invest in original content with your own data, studies and expert opinions. Regularly update existing content with new facts and examples. Cover long-tail queries and conversational search terms. Use precise language and avoid ambiguity. Ensure that author profiles are provided with qualifications and experience.
8.3 Off-page measures
These steps are recommended for off-page optimization:
Maintain your Google Business Profile and other relevant directory listings. Build a strong review base on trusted platforms. Aim for mentions and citations in trade media and on authoritative websites. Maintain consistent NAP data across all platforms. Publish professional articles and guest posts in recognized media. Use PR measures to position your expertise in the public eye.
9 The future of AI search: What’s next?
9.1 Conversational and multimodal search
The future of search will be even more conversational. Users will no longer enter individual keywords, but will ask complex, multi-part questions and refine information in a dialog with AI systems. Voice and video search will become more important, which means that your content will also need to be accessible and optimized in these formats.
Multimodal AI systems that can process text, images, audio and video are becoming increasingly widespread. Websites that provide content in different formats and enrich it with structured data will have an advantage in this new landscape.
9.2 AI agents and automated transactions
Another emerging trend is the rise of AI agents – autonomous systems that not only search for information, but can also perform actions. AI agents can book flights, make appointments, order products or compare and commission services. Websites that are optimized for interaction with AI agents – through clear APIs, structured data and machine-readable transaction information – will enjoy a significant competitive advantage in this future.
9.3 Personalization and contextual search
AI systems will increasingly be able to provide personalized responses based on the user’s context. Location, previous interactions, personal preferences and the current context of the conversation will influence the results. For website operators, this means that content will have to be tailored even more precisely to different user segments and search intentions.
9.4 Ethics, transparency and control
The increasing power of AI systems as information brokers also raises questions of ethics and transparency. Who decides what information appears in AI responses? How can website operators ensure that their content is presented fairly and correctly? The llms.txt file is a first step towards standardized communication between website operators and AI systems, but it is to be expected that further standards and regulations will emerge in the coming years.
10 Strategic recommendations: How to proceed
10.1 Don’t panic, but don’t wait either
The most important message of this article is: AI search does not replace traditional search – it complements it. Google still processes many times more queries than AI platforms. Traditional search engine optimization remains the cornerstone of your digital visibility. At the same time, it would be negligent to ignore AI search. The companies that invest in optimizing for AI platforms today will achieve superior results tomorrow, while those that wait will find more competition for fewer opportunities.
10.2 The dual strategy
The most effective strategy is an integrated approach that serves both channels from the outset. The good news is that the technical overlap is significant. Much of what helps AI visibility also helps with Google. High-quality, well-structured content with schema markup, clear semantic organization and strong E-E-A-T performance serves both channels simultaneously.
This does not mean that you have to double your workload. It means optimizing the content you already create for both channels. Integrate AI optimization into your existing content workflow instead of treating it as a separate project.
10.3 Prioritization of measures
If you start today, I recommend the following prioritization:
Start immediately by implementing an llms.txt file and checking your robots.txt for AI crawlers. Next, implement comprehensive schema markup on your most important pages. Then, revise your key content for clear structure, question-and-answer formats and original insights. In parallel, build your off-page presence through mentions, reviews and authoritative backlinks. Finally, set up AI visibility monitoring to measure your progress and continuously optimize your strategy.
10.4 Investment in knowledge and expertise
The AI search landscape is changing rapidly. What works today may be outdated tomorrow. Invest in continuous training for your team, follow industry developments and experiment with new approaches. Regular technical audits, content reviews and monitoring new standards and best practices will keep your website competitive in the long term.
The AI revolution in search is not a distant vision of the future – it’s happening now. Every day you put off optimizing for AI search systems means missed opportunities for AI citations, reduced visibility in AI-generated responses, and a growing competitive disadvantage in the evolving search landscape.
The good news is that the basic principles of good web communication still apply. Clear structure, high-quality content, technical excellence and demonstrable expertise form the foundation – for both traditional and AI-powered search. What is changing is the way you implement and extend these basic principles.
Start today. Implement the technical foundations, optimize your content and systematically build your digital authority. The companies that act now will be the winners of the new search landscape. The question is not if, but how quickly you can implement these strategies.
Bibliography
Studies and research reports
Conductor (2025). AI Referral Traffic Study. Analysis of the share of AI referral traffic in total website traffic. Available at: https://www.conductor.com
Growth Memo (2026). Citation Distribution in LLM Responses. Analysis of the distribution of AI citations within text content (44.2 % from the first 30 % of the text). Available at: https://www.kevin-indig.com/growth-memo/
Nectiv (2025). ChatGPT Web Search Trigger Analysis. Analysis of over 8,500 ChatGPT prompts, of which around 31% trigger a web search; local queries trigger web searches in 59% of cases. Available at: https://www.nectiv.com
OpenAI & Harvard University (2025). ChatGPT Usage Patterns Study. Analysis of the most common use cases of ChatGPT: Practical Guidance (29%), Seeking Information (24%), Writing (24%). Published September 2025.
Pew Research Center (2025). AI Overviews and Click Behavior Study. Study showing that users click 47% less on Google results with AI overviews (8% click-through rate vs. 15% without AI overviews). Published October 2025, available at: https://www.pewresearch.org
Profound / Brighton SEO (2025). Analysis of 41 Million AI Search Results. Presentation by Josh Blyskal at Brighton SEO 2025 analyzing the overlap of ChatGPT results with Google SERP (12%) and Bing (26%). Available at: https://seomator.com/blog/ai-search-optimization-insights
SEOFOMO (2025). State of AI Search Optimization Survey, 2025 Edition. Industry survey in which structured data/schema was named as the most common method of optimization for AI search. Available at: https://www.seofomo.co
SparkToro (2025). AI Chatbot Usage Study. Survey showing that 20% of Americans are heavy LLM users who use AI tools more than 10 times per month, while 95% continue to use traditional search engines. Published August 2025. available at: https://sparktoro.com
SparkToro (2026). AI Recommendation Consistency Study. Study showing that the probability of ChatGPT or Google’s AI returning the same brand list twice for 100 queries is less than 1%. Published January 2026. available at: https://sparktoro.com
Platform and usage data
Ahrefs (2025). AI Overviews vs. AI Mode Citation Overlap. Analysis showing that only 13.7% of citations overlap between Google AI Overviews and AI Mode. Published December 2025. available at: https://ahrefs.com
DemandSage (2025). Google Search Statistics 2025. report on Google’s 5 billion+ users and estimated 16.4 billion daily searches. Published August 2025. available at: https://www.demandsage.com
Exploding Topics (2025). ChatGPT Statistics. Report on ChatGPT’s 800 million weekly users and 2.5 billion daily prompts. Published August 2025. available at: https://explodingtopics.com
HigherVisibility (2025). AI Adoption Rate Study. Survey showing an increase in the AI adoption rate from 14% (February 2025) to 29.2% (August 2025). Published August 2025. Available at: https://www.highervisibility.com
Semrush (2025a). ChatGPT Search Usage Growth. Analysis showing that ChatGPT usage for general information searches has grown from 4.1% to 12.5% in six months. Published August 2025. available at: https://www.semrush.com
Semrush (2025b). Google AI Mode Usage Growth. Report on the quadrupling of AI Mode usage from 0.25% to over 1% and 75 million users. Published September 2025. Available at: https://www.semrush.com
Conversion rates and traffic analysis
RankScience (2025). AI Search vs. Google: Real Traffic Data. Analysis of 12 million website visits showing that AI traffic has 4-5x higher conversion rates (Claude: 16.8%, ChatGPT: 14.2%, Perplexity: 12.4% vs. Google: 2.8%). Available at: https://www.rankscience.com/blog/ai-search-vs-google-traffic-data
Technical optimization and best practices
Analyt Solutions (2025). Schema Markup & LLMs.txt for AI SEO 2025. Guide to implementing schema markup and llms.txt files for AI search optimization. Available at: https://analytsolutions.com/blog/schema-markup-and-llms-txt-must-have-for-ai-visibility-in-2025/
First Page Sage (2025). SearchGPT Optimization: 2025 Guide. Comprehensive guide to optimization for ChatGPT Search, including the recommendation algorithm. Published December 2025. available at: https://firstpagesage.com/seo-blog/searchgpt-optimization-2025-guide/
GetBool.AI (2025). llms.txt: The Complete Guide to Making Your Website Visible to ChatGPT, Gemini, and AI Search Engines. Detailed guide to implementing llms.txt and HTML-first architecture. Available at: https://getbool.ai/guides/llms-txt-complete-guide.html
Google Search Central (2025). Top Ways to Ensure Your Content Performs Well in Google’s AI Experiences on Search. Google’s official guide to optimizing for AI search experiences. Available at: https://developers.google.com/search
Ice Nine Online (2025). Optimizing Websites for AI Large Language Models (LLMs). Practical guide to technical and content optimization for LLMs. Published August 2025. available at: https://icenineonline.com/blog/optimizing-websites-for-large-language-models-llms/
Schema.org (ongoing). Schema.org Vocabulary. Standardized vocabulary for structured data, supported by Google, Bing, Yahoo and Yandex. Available at: https://schema.org
SchemaApp (2025). Structured Data, Not Tokenization, is the Future of LLMs. Analysis of why structured data is critical to the future of AI search. Published May 2025. available at: https://www.schemaapp.com/schema-markup/why-structured-data-not-tokenization-is-the-future-of-llms/
Spherical Coder (2025). LLM Content Optimization Using Structured Data for AI Search. Content Optimization Guide for LLMs Using Structured Data. Published December 2025. available at: https://www.sphericalcoder.com/news/llm-content-optimization-using-structured-data-for-ai-search
Symphonic Digital (2025). SEO for AI Search: Best Practices for Google AIO & ChatGPT SEO. Strategies to optimize for Google AI Overviews and ChatGPT Search. Published July 2025. available at: https://www.symphonicdigital.com/blog/seo-for-ai-search
ViaMrkting (2025). LLM Optimization: How to Optimize Content for LLMs and AI Overviews (GEO). Comprehensive guide to on-page and off-page factors of LLM optimization. Published November 2025. available at: https://viamrkting.com/a-comprehensive-guide-to-llm-optimization-preparing-your-website-for-generative-ai-geo/
Walker Sands (2025). How Can Schema Markup Specifically Enhance LLM Visibility. Analyzing the role of schema markup for visibility in LLM-generated responses. Published November 2025. Available at: https://www.walkersands.com/about/blog/how-can-schema-markup-support-llm-visibility/
Wellows (2026). Schema & NLP Best Practices for AI Search Visibility (2026 Guide). Current best practices for schema markup and NLP optimization in AI search. Available at: https://wellows.com/blog/schema-and-nlp-best-practices-for-ai-search/
Monitoring tools and platforms
Frase.io (2025). Agentic SEO & GEO Platform. Platform for researching, creating and optimizing content for SEO and GEO. Available at: https://www.frase.io
Otterly.AI (2025). AI search monitoring tool. Platform for monitoring brand mentions and website citations on AI search platforms. Available at: https://otterly.ai
Position Digital (2025). 90+ AI SEO Statistics for 2025. Continuously updated compilation of AI SEO statistics and trends. Available at: https://www.position.digital/blog/ai-seo-statistics/
Strategic analyses and comments
Omnius (2025). How to Rank Your Website on ChatGPT and Get Cited in 2026. Strategies to improve ChatGPT visibility with a focus on content freshness and user experience. Published November 2025. available at: https://www.omnius.so/blog/how-to-rank-on-chatgpt
Optimize5 (2025). The Essential Schema and LLMS.txt Guide. Practical guide to integrating schema markup and llms.txt, especially for WordPress websites. Published October 2025. available at: https://optimize5.com/power-of-schema-and-llms-txt/
Oyova (2025). AI Search Optimization in 2025: Boost Visibility in ChatGPT. Cross-industry strategies for AI search optimization. Published August 2025. available at: https://www.oyova.com/blog/ai-search-optimization/
Quoleady (2025). Schema & Structured Data for LLM Visibility: What Actually Helps?. Evidence-based analysis of the effectiveness of schema markup for LLM visibility. Published August 2025. Available at: https://www.quoleady.com/schema-structured-data-for-llm-visibility/
Search Engine Land (2025). Optimizing for AI: How Search Engines Power ChatGPT, Gemini and More. Analysis of the technical workings of AI search systems and their implications for optimization. By Chris Silver Smith, published September 2025. Available at: https://searchengineland.com/optimizing-ai-search-engines-461892
SEOmator (2025). AI Search Optimization: Insights from 41M Results Across ChatGPT and Google. Summary of Brighton SEO 2025 findings on AI search results. Available at: https://seomator.com/blog/ai-search-optimization-insights
This article was written in February 2026. In view of the rapid developments in the field of AI-supported search, we recommend that you regularly check the strategies and statistics mentioned here to ensure that they are up to date.
