Reddit sued Perplexity AI earlier this year, and the court filings did something unusual: they exposed, under oath, exactly how AI search engines find, evaluate, and cite content. Not theory. Not speculation from an SEO vendor. Documented technical architecture.
If you run a practice website or publish clinical content online, three findings matter.
1. AI search engines do not crawl the internet. They read Google.
Reddit proved this directly. They created a test post that only Google could access, blocking every other crawler. Perplexity surfaced that content anyway. The only path was through Google's index.
This means your Google rankings aren't just about Google anymore. They're the entry point for ChatGPT, Perplexity, Google's own AI Overviews, and every AI assistant your patients are already using to research their options. If your practice doesn't appear on page one for relevant searches, AI will never find you to cite.
2. AI engines maintain lists of trusted sources by category.
The lawsuit revealed that Perplexity curates domain authority lists organized by topic. Medical content from established, well-linked sites gets preferential treatment. Content from thin or poorly connected sites gets filtered out.
For restorative reproductive medicine, this is both a challenge and an opportunity. The category is small enough that a well-built site with strong clinical content and links from recognized medical organizations can establish itself as a trusted source relatively quickly. But it requires deliberate work. A WordPress template with a few paragraphs about your services won't clear the threshold.
3. Freshness is weighted heavily.
Court documents confirmed a time decay system. Recently published or updated content scores higher than older content, even if the older content is technically better.
This is where most practice websites fall behind without realizing it. A site that was built three years ago and hasn't been touched since is actively losing visibility in AI search, not just stagnating. AI systems interpret silence as irrelevance. Regular content updates, even modest ones, signal that a source is actively maintained and current.
What this does not change
The fundamentals still apply. Your site needs to load fast, be mobile-friendly, and contain real clinical depth, not marketing filler. Structured data (FAQ schema, medical practice schema) still helps AI systems extract and cite your content cleanly. And the quality of your backlinks still matters more than the quantity.
What the lawsuit does is remove ambiguity. AI search visibility isn't a separate discipline from search engine optimization. It's downstream of it. The practices that are investing in their web presence now are the ones that will be cited when patients ask AI "What is NaProTechnology?" or "Who treats endometriosis without hormonal suppression near me?"
The ones that aren't investing will wonder why they're invisible.
Two additional signals worth knowing
Beyond the lawsuit itself, earlier technical leaks from a Perplexity engineer revealed two more ranking factors that have since been corroborated by the court filings.
Semantic similarity scoring. Perplexity chunks your content into vector embeddings and computes how closely your page matches the intent behind a query. This means your content needs to directly answer the questions people are asking, not just mention the right keywords. Pages built around clear questions with specific, substantive answers perform better than pages that mention a topic generally.
Engagement tracking. Perplexity monitors whether content gets clicked and engaged with shortly after appearing in results. Content that earns early engagement gets shown more. Content that doesn't gets deprioritized. This matters most when you publish something new. Sharing it immediately through your existing channels (email, social, patient communities) creates the early signal that keeps it visible.
Frequently asked questions
How do AI search engines like Perplexity get their answers?
AI search engines primarily retrieve content from Google's index rather than crawling the web independently. They apply additional filters including trusted source lists, freshness signals, and semantic relevance scoring before selecting which content to include in a generated answer.
What did the Reddit v. Perplexity lawsuit reveal about AI search?
Court filings showed Perplexity accesses Google search results programmatically, uses curated allowlists of high-authority sources, and ranks retrieved content by recency and semantic match to the query -- mirroring Google's own ranking signals rather than replacing them.
What is a trusted source list in AI search?
AI search engines maintain internal lists of domains they treat as authoritative. Sites with strong Google authority, consistent publication history, and verifiable credentials are more likely to appear on these lists. NaPro and RRM specialty sites can qualify through structured content and credential markup.
How does content freshness affect AI search inclusion?
AI systems weight recently published or updated content more heavily when answering time-sensitive queries. A page last modified 18 months ago competes poorly against a page updated in the last 60-90 days, even on the same topic.
Does Google rank still matter if AI search is replacing traditional search?
Yes. Because AI search engines source from Google's index, Google ranking remains the primary prerequisite for AI search visibility. A page Google has not indexed cannot be retrieved by Perplexity, ChatGPT Search, or similar tools.