# How SEO Farms Are Gaming AI Search Engines > AI search tools rely heavily on obscure blogs and synthetic web pages to generate software recommendations. - Title: How SEO Farms Are Gaming AI Search Engines · Trellner Research - Summary: AI search tools rely heavily on obscure blogs and synthetic web pages to generate software recommendations. AI search recommendations are vulnerable to… - Keywords: seo, perplexity, tech, technology, startups, Farms, Gaming, Search, Engines, Trellner Research - Source: Trellner Research — https://trellner.com/reports/manufactured-sources-behind-ai-recommendations - Read time: 1 min - Topics: ai, seo, perplexity, tech, technology, startups ## How AI picks software recommendations When asked for top software products across 380 categories, Perplexity relied heavily on obscure, low-traffic websites to supply evidence. > Of the 7,534 citations that came back, 59.8% point at domains ranked worse than #100,000 in the Tranco top-1M list ## The rise of obscure sources Over 23% of citations used to ground AI answers came from websites outside the top million most popular domains. Wikipedia was cited just three times. > Wikipedia, for comparison, was cited three times in 7,534. ## Marketing blogs beating industry leaders A software vendor's content marketing blog became the third most-cited domain overall, outranking established research giants like Gartner. > Its blog was nonetheless cited 194 times across 96 of our 380 categories — a quarter of them — placing it third overall and ahead of Gartner. ## Synthetic content on a massive scale Three connected websites published over 215,000 automated software comparison pages in under three years to flood search indexes. > They and a third site under apparently common control have published 215,128 machine-generated best pages between them ## Built for bots instead of humans These automated networks titled their homepages 'Facts & Grounding Page' to directly target the machine retrieval steps used by AI engines. > Grounding is not a term buyers use. It is the name of the step in which a retrieval system fetches documents to condition an answer on. ## Contradictions and fake bylines The synthetic sites cited fictional experts and contained unrendered template code. They gave contradictory rankings for identical software queries. > All three carry an unrendered template variable in the byline line, reading 'Within the next 26 days' on two of them ## Bad links and gambling redirects Over one percent of vendor links supplied by the AI were completely unreachable. Other links redirected users to online gambling portals. ## A shared engine under the hood Perplexity's standard and pro models returned identical citations in 289 categories, revealing they rely on the exact same underlying retrieval system. > so the Perplexity tiers share a retrieval layer and should be read as one search stack sampled twice. ## A new era of AI optimization Spammers are moving beyond traditional human-focused search optimization to target the hidden machine retrieval pipelines powering modern AI. > What we measured is which documents the evidence base is made of. ## Key takeaway AI search recommendations are vulnerable to manipulation by synthetic content networks explicitly designed for machine retrieval.