AI Visibility Audit

Answer Engine Optimization (AEO) is the discipline of structuring web content so that AI-powered answer engines — including Google AI Overviews, ChatGPT Search, Perplexity, Microsoft Copilot, and Google Gemini — select that content as the cited source when they generate a direct answer for a user's query. Where traditional SEO optimizes to rank a page on a results list, AEO optimizes to be quoted inside the answer itself. Why it matters: As zero-click search consumes a larger share of all queries, being the cited source inside an AI-generated answer becomes far more valuable than ranking #10 on a traditional results page. AEO best practices include writing one-sentence factual definitions immediately under question-based H2 headings, publishing comprehensive FAQ sections with FAQPage schema, building strong Organization and Author schema, earning third-party citations from authoritative outlets, and maintaining a public llms.txt file. Brands that adopt AEO early are positioned to dominate AI citations as the AI search market matures.

AI search is the broad category of search experiences powered by artificial intelligence and large language models, where users receive synthesized, conversational answers instead of (or alongside) traditional lists of links. This includes Google AI Overviews, ChatGPT Search, Perplexity, Microsoft Copilot, and Gemini. Why it matters: AI search has shifted the SEO playing field. Ranking on page one of Google is no longer enough — brands must also be cited by AI models when users ask questions about their industry, products, or expertise. AI search systems prioritize sources with strong entity signals, consistent brand mentions across authoritative sites, structured data, and content that directly answers user intent. Optimizing for AI search means building digital authority through PR, earning media mentions, implementing schema markup, and creating content that AI models can easily understand, trust, and reference in their generated responses.

llms.txt is a proposed plain-text file placed at the root of a website (e.g. /llms.txt) that summarizes the site's purpose, lists its most important canonical URLs, and provides AI crawlers with a compact, structured map of what the site is authoritative on. It is the AI-engine analog to robots.txt and sitemap.xml, designed specifically to help large language models index, ground, and cite the right pages. Why it matters: As ChatGPT, Perplexity, Claude, Google AI Overviews, and Bing Copilot increasingly drive discovery, llms.txt is becoming a meaningful AEO and GEO infrastructure layer. A well-crafted llms.txt tells AI engines exactly which pillar guides, services, and authoritative resources to cite when answering questions in the brand's domain — reducing the risk of being misrepresented or omitted. Sites without llms.txt are not penalized, but sites with a clean, accurate llms.txt give themselves a structural advantage in AI citation outcomes. Smart Money Media's own llms.txt is publicly available at /llms.txt, and any site can generate a spec-compliant file in 30 seconds with our free llms.txt generator at /tools/llms-txt-generator.

Prompt visibility is the practice of measuring whether — and how — a brand appears when a representative set of AI prompts is run against the major AI search engines. It is the AI-era equivalent of rank tracking: instead of asking "where do I rank for [keyword]?", brands ask "do I get mentioned when a buyer asks ChatGPT [buyer question]?" Why it matters: Prompt visibility is the only metric that directly captures AEO and GEO performance, because traditional rank tracking misses every zero-click AI answer. Smart Money Media runs prompt-visibility scans across GPT-5, Claude, Gemini, and Perplexity so brands can see, prompt by prompt, where they win, where competitors win, and which prompts to attack next.

Cited-by-AI is the metric that tracks how often an AI engine (ChatGPT, Perplexity, Gemini, Copilot, Claude) names a brand or links to its content as a source inside a generated answer. Unlike traditional rankings, cited-by-AI is measured per prompt and per engine: a brand can be cited first in Perplexity for one query and absent from Gemini for the same query. Why it matters: As zero-click answers consume more of the buyer journey, cited-by-AI share replaces blue-link ranking as the truest measure of search visibility. Tracking it across a defined set of buyer prompts is the foundation of any serious GEO program and the headline metric of an AI visibility audit.

An AI search engine is an advanced search platform powered by artificial intelligence that fundamentally shifts the search experience from a list of links to conversational, synthesized answers. Unlike traditional search engines, these platforms (such as Google Gemini, Microsoft Copilot, Perplexity, and even integrated AI features like ChatGPT Search) generate comprehensive responses, often citing multiple sources, rather than merely pointing to web pages. Why it matters: This paradigm shift means that for a brand's information to be included or cited, its content must exhibit strong entity signals, demonstrate high authority and factual accuracy, and be structured in a way that AI models can easily process and trust. The goal is to be a primary 'ingredient' in these AI-generated answers, rather than just a link on a results page. For example, a user asking "What are the benefits of [Brand X's] new service?" expects a direct answer citing the brand's official statements or authoritative reviews, not just a list of links to articles about it.