AI Search vs Google Search: What Changed
Google has been the default discovery mechanism for the internet since the early 2000s. AI search engines are the first genuine alternative to emerge at scale, and they work fundamentally differently. Understanding the differences is essential for any brand that depends on organic discovery, because the strategies that work on Google do not transfer automatically to AI search.
How Google works
Google crawls the web, indexes pages, and ranks them according to hundreds of signals including content relevance, backlink authority, page experience, and E-E-A-T. When a user searches, Google returns a ranked list of results, typically ten to twenty links per page. The user sees the title and description of each result and chooses which to click. The model depends on the user engaging with results and visiting external sites. Google earns revenue from ads placed above and alongside organic results.
How AI search works
AI search engines (ChatGPT, Perplexity, Google AI Overviews, Claude) take a user's question and generate a direct answer. They may retrieve real-time content from the web, but the answer is synthesized rather than listed. The user sees one answer, not ten options. Citations, when included, appear as references rather than as the primary result. The user rarely needs to visit any linked page to get value from the response. This is a fundamentally different interaction model that changes the economics of organic discovery.
Traffic differences
Google search generates click-through traffic. A top-three organic ranking on a competitive keyword can drive thousands of visitors per month. AI search does not generate traffic in the same way. ChatGPT often does not include links at all. Perplexity includes a few citations but users frequently stay in the Perplexity interface. Google AI Overviews reduce click-through on traditional organic results. The value of AI citation is brand awareness and high-intent referrals rather than volume traffic. The user who does click through from a Perplexity citation has already received a recommendation.
What still matters in both environments
Several factors matter for both Google ranking and AI citation. High-quality, factually accurate content is valued by both. Fast, accessible sites with no security warnings perform better in both environments. E-E-A-T signals are explicitly part of Google's quality rater guidelines and implicitly valued by AI engines selecting trustworthy citations. Strong brand mentions across authoritative external sources benefit both. Building for one environment while keeping the other in mind is achievable without doubling the workload.
What to do differently for AI search
The Google-specific tactics that do not transfer to AI search include keyword density optimization, building links specifically for domain authority, and targeting featured snippets with specific formatting. The AI-specific additions that Google does not require include an llms.txt file, explicit AI crawler permissions in robots.txt, Organization and FAQPage JSON-LD schema, and entity consistency audits. A brand that has done thorough SEO work has a head start on AEO but still needs to complete the AI-specific layer.
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