AI readiness refers to a website's ability to be properly indexed and cited by AI search engines (ChatGPT, Perplexity, Google AI Overviews, etc.). Key criteria include HTML structure, title hierarchy, metadata, the presence of llms.txt, and accessibility. Improving your AI readiness helps you be discovered by conversational assistants.
An AI SEO audit evaluates your site's readiness for AI-based search engines. It checks H1-H6 title hierarchy, meta tags, llms.txt, robots.txt, and sitemap.xml. A complete audit provides a score and actionable recommendations to optimize your visibility in AI answers.
The llms.txt file is a standard inspired by robots.txt, designed for AI crawlers. It lets generative search engines discover your content usage rules and improve source citation. Place llms.txt at your domain root (e.g. example.com/llms.txt) to signal your willingness to be indexed.
Visibility in AI search engines depends on content quality, metadata, and technical structure. Generated answers from ChatGPT or Perplexity rely on well-structured, accessible sites. Optimizing for AI complements traditional SEO and prepares your brand for the conversational search era.
LLM marketing recommendations use positioning data (SOV, mentions, sentiment) from analysis reports to prioritize concrete actions. They cover content, source authority, perception, and competitive differentiation. These recommendations help align your strategy with your actual visibility in AI answers.
The robots.txt file governs crawler access to your site. AI search engines like ChatGPT and Perplexity generally respect these directives. To be indexed by conversational assistants, avoid blocking AI user-agents in robots.txt and ensure your important pages are accessible.
A well-structured sitemap.xml facilitates page discovery by AI crawlers. List your priority URLs with metadata (lastmod, priority) to help generative search engines better understand and index your site.
Meta tags (title, description, og:*) are essential for AI readiness. AI search engines use them to summarize and cite your content. Clear, relevant metadata improves the quality of citations in generated answers.
Web accessibility (semantic structure, ARIA attributes, contrasts) facilitates content parsing by AI crawlers. An accessible site is more easily understood and cited by generative search engines.
AI crawlers (GPTBot, Google-Extended, Perplexitybot, etc.) explore the web to feed language models. Optimizing your site for these crawlers via llms.txt, clear structure, and quality content improves your visibility.
ChatGPT Search cites web sources in its answers. To appear in these citations, your site must have an exploitable structure, correct metadata, and relevant content. AI readiness increases your chances of being cited.
Perplexity relies on web sources to generate answers. Good HTML structure, hierarchical headings, and an llms.txt file help Perplexity discover and cite your content correctly.
Google AI Overviews integrates site excerpts into search results. AI optimization complements traditional SEO: structure, E-E-A-T, useful content, and technical signals favour appearance in overviews.
A semantic HTML structure (header, main, article, section, nav) helps AI crawlers understand the hierarchy and meaning of your content. Semantic tags improve the quality of generated citations and summaries.
A correct heading hierarchy (one H1 per page, logical H2-H6) facilitates content understanding by AI search engines. Headings structure information and enable assistants to summarize and cite your pages accurately.