Understanding how AI-powered search works and why your traditional SEO foundation has never been more important.
A question is echoing through every digital marketing conference, Slack channel, and strategy meeting these days: Is traditional SEO dead in the age of AI? With ChatGPT, Perplexity, and Google’s AI Overviews reshaping how people find information, it’s a legitimate concern that keeps many of us awake at night.
Here’s what the data reveals, and it may surprise you.
Recent research from Search Engine Journal, combined with a comprehensive analysis by ZipTie’s co-founder, Tomek Rudzki, based on 25,000 user queries, delivers a clear answer: No, SEO isn’t dead. It’s evolving rapidly and remains critically important.
But here’s the nuance that matters: the relationship between traditional rankings and AI-powered results is more intertwined than most people realise.
Think about this for a moment. When ZipTie analysed how AI systems select their sources, they found something remarkable: websites ranking first in Google have a 25% chance of being cited in AI search responses. Even more telling, the higher your position in the traditional top 10, the more likely you are to appear in ChatGPT, Perplexity, and Google AI Overviews.
This isn’t speculation—it’s based on concrete user data across thousands of queries. If you want to show up in AI-powered results, you first need to perform well in traditional SEO. The AI revolution hasn’t replaced the foundation; it’s built upon it.
To understand why traditional SEO still matters, you need to grasp how AI search systems operate. They typically follow a three-stage process that reveals why your current SEO efforts are more valuable than ever:
First comes Pre-selection. The AI system identifies the most relevant content for a user query, typically content that already ranks highly in Google’s traditional results. This is your entry ticket to the AI game.
Next is Content Extraction. From these pre-selected sources, the system pulls specific information that directly answers the user’s question. This is where your content structure and clarity become crucial.
Finally, AI Synthesis takes over. Large language models like Gemini transform this extracted information into coherent, comprehensive answers. Your content doesn’t just need to rank; it needs to be synthesizable.
Google’s leaked internal communications confirm what many of us suspected: content from top-ranking pages improves the accuracy of AI outputs. This makes traditional SEO not just relevant but critical for AI visibility.
You might wonder: if top rankings are so important, why do AI results sometimes include sources that don’t rank in the first 10? Two primary reasons reveal opportunities for strategic SEO.
Personalisation and Caching mean search results can vary by user, creating windows of opportunity for well-optimized content to surface in AI responses even without top-10 rankings.
More importantly, Query Fan-Out represents a fundamental shift in how search works. AI doesn’t just process your main query—it runs multiple sub-queries in the background. When someone searches for “difference between SEO and SEM,” the system simultaneously seeks answers to related questions like “what is SEO?” and “what is PPC?”
Content that ranks strongly for these sub-queries can appear in AI responses even if it doesn’t dominate the main search term. This creates new strategic opportunities for SEO professionals who understand this dynamic.
Traditional SEO aimed to create the “best page” about a topic—comprehensive, authoritative, covering everything. AI search wants the “best answer”—concise, direct, and immediately useful.
This shift demands a fundamental change in how we approach content creation. Instead of building massive, all-encompassing pages, we need modular, question-focused content that addresses specific user intents with precision.
The content that wins in both traditional SEO and AI responses shares common characteristics: it directly addresses user intent, provides clear value, and can be easily understood and synthesised by both humans and machines.
Based on 15 years of watching search evolve and the latest data on AI integration, here’s what you need to do differently:
Don’t abandon SEO fundamentals. Traditional rankings remain the foundation. Every AI system I’ve analyzed draws heavily from content that already performs well in conventional search results.
Modularise your content strategy. Instead of creating massive pillar pages, develop focused, question-specific content pieces. Each piece should provide a complete answer to a specific query while linking to related topics.
Play the sub-query game. Research keyword variations and related questions your audience asks. Optimize for the query fan-out effect by creating content that ranks for multiple related searches.
Write with clarity and directness. Eliminate unnecessary complexity. AI systems favor content that’s easily extractable and synthesizable.
Monitor your AI citations. Track which pages get cited by AI systems and analyse the patterns. This data will inform your future content strategy.
Shift your mindset. Focus on providing the best answer to user questions rather than just achieving top rankings. The two goals align more than you might think.
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