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If you’re here, you’ve probably noticed something: AI is changing how people find information online. Let’s understand what’s actually happening under the hood.

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How People Search Has Changed

Traditional Google Search:
  • User types keywords: “CRM software” (2-3 words)
  • Google shows 10 blue links
  • User clicks one
  • You track the visit
AI Search:
  • User asks: “What’s the best CRM for a 10-person remote marketing team that integrates with Slack?”
  • AI reads multiple sources
  • Creates one synthesized answer
  • Maybe mentions you, maybe doesn’t
  • You might never know
People don’t type keywords anymore. They have conversations. They provide context. They expect personalized answers.

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How AI Search Actually Works (RAG)

AI search uses Retrieval Augmented Generation (RAG) to provide answers. Here’s what happens step by step: 1. Question Analysis
  • AI understands what you’re really asking
  • Identifies key entities, intent, and context
  • Expands the question to capture related concepts
2. Document Retrieval
  • Searches pre-built web indexes (not the live web!)
  • Uses vector search to find semantically similar content
  • Retrieves relevant passages from multiple sources
3. Content Evaluation
  • Judges quality, relevance, and authority of sources
  • Filters out low-quality or outdated information
  • Prioritizes trusted domains and recent content
4. Answer Generation
  • Synthesizes information from selected sources
  • Creates coherent response in natural language
  • Decides whether to include citations (usually doesn’t)
5. Learning
  • Improves from user feedback and interactions (remember the thumbs up/down buttons next to ChatGPT answers?)
  • Adjusts ranking and selection algorithms
  • Updates understanding of what makes good answers
Think of it like a DJ mixing tracks - AI pulls content from different sites and mixes it into one answer. But most of the time, it forgets to credit the original artists.

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Where AI Gets Its Information

Critical insight: AI doesn’t crawl the live web. Each platform uses different pre-built indexes:
PlatformIndex Source
ChatGPTBing + proprietary
PerplexityGoogle’s index
ClaudeOwn crawled data
Google AI OverviewsGoogle’s index
GeminiGoogle’s index
This means your brand new content won’t appear immediately - it needs to be indexed first by the underlying search engine.

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Google’s Query Fan-Out Method

Google AI Overviews and the upcoming AI Mode do something unique - they expand one query into many. When someone searches “best CRM software,” Google AI generates 20+ related searches behind the scenes:
  • CRM pricing comparison
  • CRM features for small teams
  • CRM integration capabilities
  • CRM user reviews
  • CRM setup complexity
  • CRM customer support quality
Your content ranking #50 for the main term might rank #2 for “CRM API capabilities” and get included. This is why comprehensive content wins - you need to match the entire query universe, not just one keyword. Based on leaked Claude documentation, AI has 4 search modes:
  1. Never Search - Uses pre-trained knowledge (you can’t influence this)
  2. Offer Search - Varies by model (unpredictable)
  3. Single Search - Most common, handles 80% of queries (your main opportunity)
  4. Research Mode - Complex queries needing 2-20 searches (growing opportunity)
Focus your efforts on Single Search and Research Mode - these are where you can actually make an impact.

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Key Differences from Traditional SEO

AspectTraditional SEOAI Search (GEO)
User InputKeywords (2-3 words)Prompts (15-25 words)
GoalRank in top 10Get mentioned at all
Competition10 spots on page 1Unlimited mentions possible
TrafficDirect clicksBrand awareness → searches
UpdatesMonthly algorithm changesDaily volatility
Trust SignalsBacklinksThird-party mentions
Now that you understand how AI search works differently, let’s learn the new vocabulary you’ll need to navigate this world - from prompts to citations and everything in between.
What’s Next