AI Is Changing Search—But SEO Still Drives Results, Says Groundbreaking Study
SEO in the Age of AI
In the rapidly evolving world of digital search, artificial intelligence is reshaping how users discover information. Tools like ChatGPT, Perplexity AI, and Google’s AI Overviews 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 AI is rendering traditional SEO obsolete.
But new research by Tomasz Rudzki, co-founder of ZipTie, challenges this assumption. Analyzing 25,000 real-world user searches, his study reveals a compelling truth: SEO is far from dead. In fact, your Google ranking still plays a major role in whether your content appears in AI-generated search results.
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—even in the age of AI.
Research Overview: 25,000 Searches Analyzed
The person behind this eye-opening research is Tomasz Rudzki, co-founder of ZipTie, 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.
To do this, he analyzed 25,000 actual user searches across three leading AI platforms: ChatGPT, Perplexity, and Google’s AI Overviews. The objective was clear—determine whether websites that rank highly on Google are still being featured in AI-generated answers.
The findings were striking: websites that ranked #1 on Google appeared in AI-generated responses 25% of the time. This correlation between top search engine positions and AI visibility offers powerful evidence that traditional SEO continues to influence AI-driven results.
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 high Google rankings are not just relevant—they’re essential. AI doesn’t ignore SEO; it builds on it. For anyone serious about digital visibility, this data is a clear call to action: don’t abandon SEO—evolve with it.
Why Top Rankings Still Matter
One of the most important findings from Tomasz Rudzki’s research is the strong correlation between top Google rankings and AI search visibility. 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.
Rudzki explains, “The higher you rank in Google’s top 10, the more likely you are to appear in AI search results across platforms. This isn’t speculation – it’s based on real queries from real users.” This insight confirms that AI platforms aren’t starting from scratch—they’re using the existing infrastructure of search engines, especially Google, to determine which content to trust and present.
AI systems like ChatGPT, Perplexity, and Google’s AI Overviews still rely heavily on the authority, relevance, and quality indicators that SEO professionals have been optimizing for years. They extract and synthesize information from top-performing content, not random sources.
While AI search may look new on the surface, it rests on the foundation laid by traditional SEO. High-ranking pages remain highly influential. So, for brands and marketers, the goal isn’t just to adapt to AI—it’s to ensure their SEO efforts continue feeding into it.
How AI Search Engines Select Sources
AI search engines don’t magically generate answers from thin air—they 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’s antitrust trial, here’s a clear step-by-step breakdown:
Step 1: Pre-selection – Prioritizing Top-Ranking Documents
The first step AI systems take is to identify the most relevant and authoritative content. This process strongly favors web pages that already rank highly on Google. Sites with strong E-E-A-T signals (Experience, Expertise, Authoritativeness, and Trustworthiness) and solid domain authority are more likely to be selected during this initial filtering stage.
AI systems are designed to mimic user trust—and users trust what ranks well. So, if your content ranks in the top 10, it’s already at an advantage in being shortlisted by AI tools.
Step 2: Content Extraction – Finding the Best Answers
Once potential sources are selected, the AI doesn’t read entire pages—it looks for specific, relevant passages that directly address the user’s query. This means clear, concise, and well-structured content is far more likely to be used.
Content that answers questions in a focused way—using subheadings, lists, or FAQs—helps AI systems extract meaningful responses more efficiently.
Step 3: AI Synthesis – Generating a Final Response
Finally, the AI takes the selected passages and synthesizes them into a coherent, natural-sounding answer. In Google’s case, this step is handled by its powerful Gemini model. Content quality and contextual relevance play a major role in this phase.
According to internal Google documentation from the antitrust trial, “Using top-ranking content improves the accuracy of AI-generated answers.” This proves that SEO is not only still relevant—it’s foundational to how AI search engines function today.
Understanding the Query Fan-Out Effect
One of the most fascinating elements of how AI search engines operate is a behind-the-scenes process known as the Query Fan-Out Effect. Instead of relying on a single query to generate an answer, AI systems quietly run multiple related sub-queries to better understand the user’s intent and provide a more accurate, context-rich response.
For example, if a user searches for “SEO vs SEM,” the AI might automatically run several additional queries, such as:
- “What is SEO?”
- “How does SEM work?”
- “Difference between paid ads and organic traffic”
- “SEO advantages for long-term traffic”
These related searches help the AI collect content from various angles before synthesizing a final answer.
There are two major outcomes of this process:
1. Personalization:
Search results can vary based on a user’s location, search history, or behavior. This means even high-ranking pages may not appear consistently for every user.
2. Query Fan-Out:
This is the more impactful factor. Even if your page doesn’t rank for the main query, it can still be pulled into AI-generated results if it ranks well for any of the related sub-queries. This gives marketers a valuable strategy: don’t just optimize for one keyword—optimize for a cluster of related questions and terms.
Implication:
To boost visibility in AI search, your content must cover related angles and subtopics thoroughly. By optimizing for a broader query set, you increase your chances of being selected during the AI’s fan-out phase—even if you’re not #1 for the original search term.
From “Best Page” to “Best Answer”: A Strategic Shift
In traditional SEO, the goal was clear: create the “best page”—a long, comprehensive guide covering every possible angle of a topic. While this approach worked well for ranking in Google’s top 10, it’s becoming less effective in the era of AI-driven search.
Today’s AI search engines prioritize the “best answer” over the longest article. They’re not looking for entire pages—they’re scanning for precise, relevant responses that match the user’s intent. This requires a significant strategic shift in how content is planned, written, and structured.
For example, instead of publishing a 3,000-word guide titled “Complete Guide to the iPhone 15,” it’s more effective to create a specific section—or even a standalone page—that answers a focused question, such as:
“What is the iPhone 15’s battery life?”
This is where content modularization becomes critical. By breaking your content into smaller, answerable units, you allow AI systems to easily extract relevant snippets for a wide range of search queries. Use clear headings, FAQs, bullet points, and concise explanations to increase the likelihood that your content will be selected during the AI’s content extraction and synthesis stages.
This shift doesn’t mean abandoning depth—but it does mean delivering value in smaller, sharper packages. To stay competitive, marketers must adapt their strategy from building pages that impress Google bots to crafting content that directly answers user questions in ways AI can easily understand and use.
SEO + AI = New Content Best Practices
As AI reshapes search, digital marketers must evolve their strategies to stay ahead. The good news? Traditional SEO remains vital—but it needs to be combined with new, AI-friendly tactics for maximum impact. Here are some actionable best practices to consider:
Keep SEO Alive:
Don’t abandon your efforts to rank in Google’s top 10. Tomasz Rudzki’s research proves that high rankings still heavily influence AI search results. SEO remains the foundation for AI visibility.
Keep SEO Alive:
Don’t abandon your efforts to rank in Google’s top 10. Tomasz Rudzki’s research proves that high rankings still heavily influence AI search results. SEO remains the foundation for AI visibility.
Target Search Variants:
Optimize not just for your main keywords but also for related phrases, semantic keywords, and different search intents. AI often runs multiple related queries (the “query fan-out” effect), so capturing this breadth expands your reach.
Clear Language Wins:
Avoid keyword stuffing or overly complex sentences. AI systems favor clear, simple, and direct language that quickly answers user questions. Prioritize readability and straightforward explanations.
Answer Intent Directly:
Include short summaries, bullet points, or “answer boxes” within your content. These help AI identify and extract relevant information faster, increasing your chances of being featured in AI responses.
Monitor AI Performance:
In addition to traditional SEO metrics, track your visibility in AI-powered search tools using specialized analytics. Understanding how your content performs in AI results allows you to refine strategies over time.
By blending traditional SEO with these AI-focused practices, marketers can ensure their content remains competitive and highly visible in today’s evolving search landscape.
Implications for Digital Marketing Teams
The rise of AI in search has fundamentally changed how digital marketing teams approach visibility—but it hasn’t replaced SEO. Instead, SEO and AI are now deeply intertwined. AI search engines amplify the reach of well-optimized content by using traditional SEO signals to identify trustworthy, relevant sources.
For marketers, this means prioritizing real user questions and delivering clear, actionable value has never been more important. Rather than targeting broad keywords alone, teams must focus on query clusters—groups of related searches—and micro-intent, which involves understanding the specific needs behind each query.
This approach helps content rank not only in traditional search results but also increases the likelihood of being featured in AI-generated answers. The shift calls for a more nuanced content strategy that balances depth with precision, ensuring that every piece serves a clear purpose and answers targeted questions effectively.
In short, digital marketing teams that embrace this synergy between SEO and AI will be best positioned to capture growing audiences across both conventional and AI-powered search platforms. The future belongs to those who adapt quickly and focus on user-centric content optimized for both humans and AI.
Competitive Advantage: Only 25% Make It—What About the Other 75%?
Tomasz Rudzki’s research revealed a surprising statistic: only 25% of content ranked #1 on Google actually appears in AI-generated responses. This means a staggering 75% of top-ranked content misses out on valuable AI visibility.
This gap highlights an important truth—ranking high is necessary but not sufficient. AI values not only authority but also relevance, clarity, and specificity. Content that fails to deliver precise answers or isn’t formatted for easy extraction risks being overlooked.
For digital marketers, this presents a golden opportunity. By combining traditional SEO tactics with AI-friendly content formatting—such as concise answers, clear headings, and targeted subtopics—brands can differentiate themselves.
The key to gaining a competitive edge lies in mastering this balance: maintaining strong rankings while delivering content that AI can confidently and quickly use. Those who adapt will capture the 75% of AI visibility others are missing.
The Future of SEO in an AI-Driven World
SEO is not disappearing—it’s evolving to meet the demands of an AI-driven search landscape. AI search engines continue to rely on trusted, authoritative content, and SEO remains the primary way to establish that trust online.
Moving forward, greater emphasis will be placed on structured data, schema markup, and crafting direct answers that AI can easily interpret and present. Niche authority and expertise will also become critical, as AI seeks the most reliable sources for specific topics.
The future belongs to marketers who adopt hybrid strategies, blending traditional SEO best practices with AI-focused techniques. This means optimizing for organic rankings while also designing content specifically for AI extraction and synthesis.
Ultimately, SEO will continue to play a vital role—just in a smarter, more targeted way that enhances visibility across both human and AI-powered search results.
Expert Takeaway & Final Thoughts
Tomasz Rudzki’s key insight sums it up perfectly: “Stop asking how to rank, start asking how to help.” This mindset shift is essential for marketers navigating the evolving search landscape.
Instead of chasing algorithm updates, success now depends on aligning content closely with user intent, providing clear, precise answers that genuinely serve the audience’s needs. This approach reaffirms SEO’s relevance—not as a static checklist, but as a dynamic strategy focused on clarity, relevance, and intent.
As AI continues to shape search, marketers must rethink their content strategies to thrive. Prioritize creating focused, well-structured content that answers real questions, and optimize for both traditional rankings and AI visibility.
In doing so, brands will not only maintain their search presence but also gain a competitive edge in the new era—where SEO and AI work hand in hand to deliver the best possible user experience.
Now is the time to audit your content strategy—ensure it meets both traditional SEO and AI-driven search demands. Use tools like Google Search Console and AI visibility trackers to monitor performance. Have questions or insights? Share your thoughts in the comments below—let’s keep the conversation going!
