{"id":4588,"date":"2025-05-30T08:37:31","date_gmt":"2025-05-30T08:37:31","guid":{"rendered":"https:\/\/blogs.nuformsocial.com\/?p=4588"},"modified":"2025-07-31T08:07:44","modified_gmt":"2025-07-31T08:07:44","slug":"ai-is-changing-search-but-seo-still-drives-results-groundbreaking-study-insights","status":"publish","type":"post","link":"https:\/\/www.nuformsocial.com\/blog\/ai-is-changing-search-but-seo-still-drives-results-groundbreaking-study-insights\/","title":{"rendered":"AI Is Changing Search\u2014But SEO Still Drives Results, Says Groundbreaking Study"},"content":{"rendered":"\t\t
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AI Is Changing Search\u2014But SEO Still Drives Results, Says Groundbreaking Study<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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SEO in the Age of AI<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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In the rapidly evolving world of digital search, artificial intelligence is reshaping how users discover information. Tools like <\/span>ChatGPT<\/b>, <\/span>Perplexity AI<\/b>, and <\/span>Google\u2019s AI Overviews<\/a><\/b> are being integrated into everyday search behavior, offering direct, conversational answers instead of traditional lists of blue links. This shift has sparked a growing belief among marketers and content creators that <\/span>AI is rendering traditional SEO obsolete<\/b>.<\/span><\/p>

But new research by <\/span>Tomasz Rudzki<\/b>, co-founder of ZipTie, challenges this assumption. Analyzing <\/span>25,000 real-world user searches<\/b>, his study reveals a compelling truth: <\/span>SEO is far from dead<\/b>. In fact, your <\/span>Google ranking still plays a major role<\/b> in whether your content appears in AI-generated search results.<\/span><\/p>

The key insight? AI-powered search engines still rely on the top-ranking results from Google to source their answers. For businesses and marketers, this means SEO remains a critical tool for maintaining visibility\u2014even in the age of AI.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Research Overview: 25,000 Searches Analyzed<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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The person behind this eye-opening research is <\/span>Tomasz Rudzki<\/b><\/a>, co-founder of <\/span>ZipTie<\/b>, a company known for its data-driven insights into SEO and search engine behavior. With growing speculation about the role of SEO in an AI-dominated future, Rudzki set out to examine the real impact of traditional rankings on AI search visibility.<\/span><\/p>

To do this, he analyzed <\/span>25,000 actual user searches<\/b> across three leading AI platforms: <\/span>ChatGPT<\/b>, <\/span>Perplexity<\/b>, and <\/span>Google\u2019s AI Overviews<\/b>. The objective was clear\u2014determine whether websites that rank highly on Google are still being featured in AI-generated answers.<\/span><\/p>

The findings were striking: <\/span>websites that ranked #1 on Google appeared in AI-generated responses 25% of the time<\/b>. This correlation between top search engine positions and AI visibility offers powerful evidence that traditional SEO continues to influence AI-driven results.<\/span><\/p>

Why does this matter? As AI becomes more embedded in the search experience, many marketers have questioned whether optimizing for Google still holds value. This study proves that <\/span>high Google rankings are not just relevant\u2014they’re essential<\/b>. AI doesn\u2019t ignore SEO; it builds on it. For anyone serious about digital visibility, this data is a clear call to action: <\/span>don\u2019t abandon SEO\u2014evolve with it<\/b>.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Why Top Rankings Still Matter<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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One of the most important findings from Tomasz Rudzki\u2019s research is the strong correlation between <\/span>top Google rankings<\/b> and <\/span>AI search visibility<\/b><\/a>. In a world where AI is increasingly relied upon to generate search responses, many assumed that traditional SEO signals had lost their relevance. However, the data tells a different story.<\/span><\/p>

Rudzki explains, <\/span>\u201cThe higher you rank in Google\u2019s top 10, the more likely you are to appear in AI search results across platforms. This isn\u2019t speculation \u2013 it\u2019s based on real queries from real users.\u201d<\/span><\/i> This insight confirms that <\/span>AI platforms aren\u2019t starting from scratch<\/b>\u2014they\u2019re using the existing infrastructure of search engines, especially Google, to determine which content to trust and present.<\/span><\/p>

AI systems like ChatGPT, Perplexity, and Google\u2019s AI Overviews still rely heavily on the <\/span>authority, relevance, and quality indicators<\/b> that SEO professionals have been optimizing for years. They extract and synthesize information from top-performing content, not random sources.<\/span><\/p>

While AI search may look new on the surface, it <\/span>rests on the foundation laid by traditional SEO<\/b>. High-ranking pages remain highly influential. So, for brands and marketers, the goal isn\u2019t just to adapt to AI\u2014it\u2019s to ensure their SEO efforts continue feeding into it.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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How AI Search Engines Select Sources<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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AI search engines don\u2019t magically generate answers from thin air\u2014they follow a systematic process to select and synthesize information from the web. Understanding this process is crucial for anyone looking to maintain visibility in AI-generated search results. Based on the research and documentation revealed during Google\u2019s antitrust trial, here\u2019s a clear step-by-step breakdown:<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Step 1: Pre-selection \u2013 Prioritizing Top-Ranking Documents<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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The first step AI systems take is to <\/span>identify the most relevant and authoritative content<\/b>. This process strongly favors web pages that already rank highly on Google. Sites with strong <\/span>E-E-A-T signals (Experience, Expertise, Authoritativeness, and Trustworthiness)<\/a><\/b> and solid <\/span>domain authority<\/b> are more likely to be selected during this initial filtering stage.<\/span><\/p>

AI systems are designed to mimic user trust\u2014and users trust what ranks well. So, if your content ranks in the top 10, it\u2019s already at an advantage in being shortlisted by AI tools.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Step 2: Content Extraction \u2013 Finding the Best Answers<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Once potential sources are selected, the AI doesn\u2019t read entire pages\u2014it looks for <\/span>specific, relevant passages<\/b> that directly address the user’s query. This means <\/span>clear, concise, and well-structured content<\/b> is far more likely to be used.<\/span><\/p>

Content that answers questions in a focused way\u2014using subheadings, lists, or FAQs\u2014helps AI systems extract meaningful responses more efficiently.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Step 3: AI Synthesis \u2013 Generating a Final Response<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Finally, the AI takes the selected passages and <\/span>synthesizes them into a coherent, natural-sounding answer<\/b>. In Google\u2019s case, this step is handled by its powerful <\/span>Gemini model<\/b>. Content quality and contextual relevance play a major role in this phase.<\/span><\/p>

According to internal Google documentation from the antitrust trial, <\/span>\u201cUsing top-ranking content improves the accuracy of AI-generated answers.\u201d<\/span><\/i> This proves that <\/span>SEO is not only still relevant\u2014it\u2019s foundational<\/b> to how AI search engines function today.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Understanding the Query Fan-Out Effect<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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One of the most fascinating elements of how AI search engines operate is a behind-the-scenes process known as the <\/span>Query Fan-Out Effect<\/b>. Instead of relying on a single query to generate an answer, AI systems quietly run <\/span>multiple related sub-queries<\/b> to better understand the user\u2019s intent and provide a more accurate, context-rich response.<\/span><\/p>

For example, if a user searches for <\/span>\u201cSEO vs SEM<\/a>,\u201d<\/b> the AI might automatically run several additional queries, such as:<\/span><\/p>