New study reveals that traditional SEO still drives visibility in AI-generated search results across ChatGPT, Perplexity, and Google.
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A new study analyzing over 25,000 real user queries reveals that websites ranked #1 on Google are featured in AI search results 25% of the time. Despite increasing reliance on generative AI to answer search queries, this data suggests that traditional SEO practices still play a vital role in determining what information surfaces in tools like ChatGPT, Google’s AI Overviews, and Perplexity.
The research, led by Tomasz Rudzki, co-founder of ZipTie, uncovers how closely AI platforms rely on Google’s top-ranked content. The results provide clear evidence that achieving top positions in traditional search results significantly increases a website’s likelihood of appearing in AI-generated summaries.
Top Google rankings still influence AI visibility
According to Rudzki, there is a direct correlation between Google search rankings and the visibility of content in AI search platforms. Pages that rank first on Google have a one-in-four chance of being featured in AI-generated results. While this doesn't guarantee inclusion, it confirms that search engines powered by AI rely heavily on conventional ranking systems to determine which pages to draw information from.
“The higher you rank in Google’s top 10, the more likely you are to appear in AI search results across platforms,” Rudzki explained. “This isn’t speculation – it’s based on real queries from real users.”
This finding holds true across major AI platforms, including Google’s AI Overviews, ChatGPT, and Perplexity. It confirms that these systems don't discard traditional search data, but instead build upon it when compiling answers.
How AI systems pull data from traditional rankings
Rudzki’s study builds on knowledge shared during Google’s antitrust trial, particularly regarding how AI search functions. The process typically follows three core steps:
1. Pre-selection based on traditional rankings
AI systems begin by identifying high-quality documents that best match the user’s query. Preference is typically given to pages with higher Google rankings, underlining the importance of ranking in the top 10.
2. Extracting precise content
Once top documents are identified, the AI extracts relevant parts of the content. The focus is on information that directly answers the searcher's question, often pulling paragraphs or specific sentences instead of entire articles.
3. Synthesizing a single answer
Finally, tools like Google's Gemini model compile the extracted content into a clear, coherent response. This synthesis process blends data from multiple sources, which is why the accuracy and clarity of a website’s information are so critical.
Internal Google documentation from the antitrust case supports the idea that AI performs better when it relies on top-ranked traditional search results. That connection explains why SEO still impacts visibility in AI search answers.
Understanding the “query fan-out” effect
Another factor influencing which pages appear in AI search results is something called the "query fan-out" method. This refers to the way AI systems expand a single user query into multiple related searches, allowing them to gather broader context.
For example, if someone searches “SEO vs SEM,” an AI might also perform additional searches like:
- “What is SEO?”
- “What is PPC?”
- “SEO explained in simple terms”
If your page is optimized for any of these related searches, even if it doesn’t rank for the original phrase, it may still appear in the AI's final answer.
This approach gives a wider range of content a chance to surface in AI responses—but only if it addresses the specific sub-queries that AI tools generate.
Why marketers must rethink their content strategy
This shift in how search works requires a new mindset from digital marketers. Historically, SEO content aimed to be the best and most comprehensive page on a given topic. But today’s AI-powered search prefers content that gives the best direct answer to a specific question.
That distinction is crucial. A long guide on iPhone 15 might rank #1 on Google, but if it doesn’t have a concise answer to “How long does the iPhone 15 battery last?” it may be ignored by AI summaries.
Marketers must adapt by producing content that directly addresses user intent, in a clear and concise format. Instead of focusing purely on keyword density or comprehensive guides, attention should shift toward producing content with specific answers.
What digital marketers should do next
Based on this research, digital marketers and SEO professionals should consider several actionable steps:
- Continue traditional SEO efforts. Top 10 rankings still significantly increase chances of being featured in AI results. Abandoning SEO would be a strategic mistake.
- Optimize for specific queries. Break down content into sections that address individual user questions, rather than writing only lengthy all-in-one guides.
- Target variations of your main topic. Use subheadings and structured content to rank for related phrases that AI systems might fan out to.
- Write with clarity and purpose. AI favors clear, factual responses. Avoid keyword stuffing and focus on user comprehension.
- Monitor both traditional and AI performance. Tools that track visibility across platforms will become increasingly valuable.
Industry-wide implications of AI search trends
This study arrives at a time when the use of generative AI in search continues to expand rapidly. With Google, Microsoft, OpenAI, and others investing in AI-first search experiences, marketers need reliable strategies to stay visible.
The fact that only 25% of top-ranked Google results are used in AI answers means there’s still significant competition—and opportunity. The remaining 75% of content is being left behind, suggesting that many top-ranking sites are not delivering content in a way that satisfies AI tools.
This creates a new metric of success: Are your answers AI-ready?
Tomasz Rudzki summed it up well:
“Instead of asking ‘How do I rank higher?’ start asking ‘How do I better serve users who have specific questions?’ That mindset shift is the key to thriving in the AI search era.”
Final thoughts
While AI-powered search engines are transforming how users find information, traditional SEO is far from obsolete. Instead, it forms the foundation upon which AI systems select, extract, and synthesize content. For marketers, this means evolving—not abandoning—your SEO practices.
By focusing on clear, helpful answers and strategically addressing related queries, you can enhance your content’s visibility across both classic and AI-driven search platforms. As the digital landscape shifts, the marketers who adapt their strategies to this hybrid model of AI and traditional SEO will be the ones who remain competitive.
