AI Spam

AI spam is content created with AI, or aimed at AI systems, primarily to manipulate search rankings or AI-generated answers rather than to help people. It includes mass-produced pages with little original value, fake reviews and comparison sites, auto-generated location or product pages, and scraped or reworded content made with AI content generation tools. Newer tactics target language models directly, such as hidden instructions in page code and networks of sites built to seed narratives into AI answers.

Google's main policy against it is scaled content abuse, introduced in March 2024: generating many pages 'for the primary purpose of manipulating search rankings and not helping users', whether AI, humans or both produce them. Its listed examples include using generative AI to create many pages without adding value, scraping and synonymizing content, and stitching together text from other pages (Google spam policies). On May 15, 2026, Google updated the policies to say that attempts to manipulate generative AI responses in Search, such as AI Overviews and AI Mode, also count as spam. Its guide for AI features, published the same day, added that creating pages for every query or fan-out variation mainly to influence AI answers violates the scaled content policy. Google has run several spam updates in 2026, the most recent from September 24 to October 8.

Spam aimed at language models is a newer problem. In February 2025 the American Sunlight Project described what it called LLM grooming: flooding the web with content so that AI systems absorb or retrieve it. A NewsGuard audit in March 2025 found that 10 leading chatbots repeated false narratives from the Pravda network, which published about 3.6 million articles in 2024, in 33% of tested responses (NewsGuard). Hidden instructions are another tactic. A 2026 analysis of 1.2 billion URLs found 15,300 validated prompt injection instances on 11,700 pages, about 70% of them in parts of the page users never see, such as comments and metadata (arXiv). Most targeted crawlers rather than search, and models rarely obeyed them, but a subset aimed at reputation manipulation in AI search and summaries.

AI spam affects legitimate brands in two ways. It can crowd out or contradict accurate information: if spam pages are the most available source on a niche question, an AI answer may repeat them, which is an AI brand safety issue. And tactics that look like shortcuts, such as mass-producing pages for every prompt variation, buying fake mentions or hiding instructions for AI crawlers, can get a site demoted. Google's May 2026 guide notes that seeking inauthentic mentions is unlikely to help because its AI features depend on the same systems that block spam.

To stay on the right side, keep human review and original information in any AI-assisted publishing, prune thin auto-generated pages that weaken your content quality signals, avoid hidden text of any kind, and disclose sponsored placements. If AI answers repeat false claims about your brand, publish a clear, well-sourced correction on your own site and through credible third parties, and keep tracking the prompts where the claim appears. Our post on fact-checking what AI says about your brand covers that process. AI hallucination is a separate cause of false answers, but the remedy overlaps.