How AI search works

Large language models (LLMs) like GPT-4 are trained on vast amounts of text data. They learn patterns in language and facts about the world from this training.

When you ask ChatGPT a question, it generates a response based on patterns learned during training – not by searching the web in real-time.

Newer systems like ChatGPT with Browse, Perplexity, and Google AI Overviews combine LLMs with real-time web search to provide current information with citations.^[1]

This combination – called retrieval-augmented generation (RAG) – is the foundation of modern AI search. The LLM generates fluent text while the retrieval system grounds responses in real, current sources.^[1]

AI tools look for authoritative sources. Government sites (.gov), educational institutions (.edu), and established medical organizations carry weight.

Content structure matters. Well-organized content with clear headings, lists, and explicit answers to questions is easier for AI to parse and cite.^[2]

Recency affects selection. For time-sensitive topics, AI tools prefer recent content over outdated information.

Consistency across sources builds confidence. If multiple authoritative sources say the same thing about your practice, AI is more likely to surface that information.

Structured data plays a growing role. Schema.org markup helps AI tools understand entities on your page – who you are, what services you offer, and where you're located – making it easier to match your content to relevant queries.

Google AI Overviews (formerly SGE) appear at the top of some search results, providing an AI-generated summary with source links.^[3]

These overviews synthesize information from multiple web pages, citing sources alongside the generated text.

Being cited in AI Overviews requires ranking well AND having content that's easily extractable and quotable.^[3]

For healthcare queries, Google is particularly careful about AI Overview content due to the potential for harm.

The shift from link-based search to AI-synthesized answers has direct implications for patient acquisition. When a patient asks ChatGPT "best dermatologist in Austin for mole removal," the response is drawn from whatever structured, authoritative information the system can find.

Practices with comprehensive, well-structured content and clear entity signals are more likely to appear in these AI-generated responses. Practices with thin, generic websites are increasingly invisible.

The key difference from traditional SEO is that AI tools don't just rank your page – they extract and synthesize your content into an answer. Your information needs to be both authoritative enough to be selected and structured enough to be accurately represented.

This means investing in schema markup, consistent business information across platforms, and detailed condition-specific content isn't optional – it's the baseline for AI visibility.