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- Brand discoverability: AI systems cannot reliably reach the information they need about the brand.<\/li>\n
- Brand clarity: AI systems access the information but produce inaccurate or inconsistent descriptions of the brand.<\/li>\n
- Brand authority: AI systems describe the brand accurately but rarely rank it in comparisons or shortlists.<\/li>\n
- Brand trust: AI systems consider the brand but rarely recommend it, or recommend it with the same reservations every time.<\/li>\n<\/ul>\n
The guide calls the planning behind this an AI search strategy, also known as an AI SEO strategy. Agentic search optimization, or ASO, builds on SEO to cover how AI systems retrieve, describe, and recommend a brand. The guide notes several tactics that are not a strategy on their own: writing in a special style for chatbots, adding an llms.txt file, implementing schema markup, checking a handful of prompts once, or creating hundreds of pages around variations of the same prompt. Each belongs in a strategy only when it addresses a problem you have already diagnosed.<\/p>\n
Layer 1: can AI systems find your content?<\/h2>\n
Brand discoverability is how reliably AI systems can find and retrieve your content. Clarity, authority, and trust all operate on information that has already been retrieved, so this is the layer to rule out first. Start with the technical baseline: priority pages should be crawlable and indexable, and the AI search crawlers you want should not be blocked by accident through robots.txt, a CDN, a firewall, a WAF, or bot-management rules. Important information should be available as readable text, JavaScript rendering should not hide key content or links, and canonicalization should signal the preferred version of duplicate pages.<\/p>\n
To qualify as a supporting link in Google’s AI Overviews or AI Mode, the guide says a page must be indexed and eligible to appear in Google Search with a snippet, and Google states that no additional technical requirements or special schema.org markup apply. For ChatGPT Search, OpenAI says publishers should allow OAI-SearchBot to reach the content they want included in summaries and snippets. Structured data still helps machines interpret a page when it accurately reflects what is visible, and the guide treats it as supporting infrastructure rather than a proven way to earn AI citations. Whether an AI agent can actually reach and read a site is what an AI agent readiness check looks at, and SEOScanPro’s AI Agent Readiness<\/a> does this.<\/p>\n
Layer 2: does AI describe your brand correctly?<\/h2>\n
Brand clarity is how accurately AI systems understand and describe your brand. A brand whose content is fully accessible can still be described inaccurately, because AI systems build their description from many sources collectively. A brand described inconsistently across the web gets described inconsistently in AI answers. Geertrui Laleman, Senior AI Search Optimization Manager at Semrush, said in the guide that AI answers used to present the company as a traditional SEO tool with bolted-on AI features, that the mentions were there but described the wrong company, and that the fix came from changing how it was described on the third-party pages that LLMs cite rather than from publishing more on its own site.<\/p>\n
Start with a verified source of truth for current positioning, product facts, pricing, and terminology. Align owned pages first, then find the important third-party sources that still carry outdated or conflicting information. AI systems can also encounter many individually accurate facts and still assemble a fragmented picture when those facts do not resolve into a clear hierarchy of what the company is, who it serves, and what it should be known for. The goal is to make the core facts consistent enough that different sources reinforce one another.<\/p>\n
To audit how you are described, the guide points to Semrush’s AI Visibility Toolkit, which shows how ChatGPT, Google AI Mode, Perplexity, and Gemini describe a brand, with a Perception report and a Key Sentiment Drivers section. Pull out the descriptions that make a factual or positioning claim and compare them against your source of truth in a simple ledger of approved fact, what AI says, assessment, where to investigate, and next action. A mismatch tells you what to review and correct, whether that means updating owned content, requesting a correction from an affiliate or publisher, or aligning internal language. For tracking across multiple markets, languages, or product lines, the guide mentions Enterprise AIO for more granular tracking by market and language. How a business appears to AI search, and what its listing looks like to the engines people ask, is what BizScoreAI<\/a> scores.<\/p>\n
Layer 3: does your brand look qualified to be included?<\/h2>\n
Brand authority is whether AI systems find enough relevant evidence to include your brand when comparing products, providers, or solutions. That evidence can come from your own site, review platforms, publishers, forums, comparison pages, and documentation. A brand can be named in an AI answer while the citation points somewhere else entirely, such as a G2 review page or a Reddit thread. Start with information gain: evidence or insight your organization can contribute that adds something new and is hard for others to reproduce, such as proprietary data or research, firsthand tests, expert experience, original frameworks, detailed primary documentation, or useful synthesis a reader would otherwise have to piece together.<\/p>\n
A Semrush content optimization study compared AI-cited pages with pages ranking in Google’s top 20 for related keywords. Cited pages scored higher on clear summarization by 32.83%, E-E-A-T signals by 30.64%, Q&A formatting by 25.45%, section structure by 22.91%, and structured data by 21.60%. In that study, structured data means lists, tables, and Q&A pairs in the visible text, not schema markup. State a finding clearly, attribute the evidence, and use headings, lists, tables, or Q&A formatting when they make the information easier to interpret. To find the sources shaping your category, the guide points to the Sources tab in Prompt Tracking and its Sources by Category view, which shows the kinds of domains AI systems draw from across tracked prompts.<\/p>\n
Layer 4: will AI confidently recommend you?<\/h2>\n
Brand trust is whether AI systems recommend your brand once they consider it, or recommend it with recurring caveats. The guide ties this layer to sentiment, review quality, cross-source corroboration, transparent claims, and reputation consistency, work that usually sits with brand, PR, reputation, and customer experience teams. The four layers are meant for triage rather than four parallel checklists, and they are diagnostic layers, not universal AI ranking factors or a fixed sequence that every system follows.<\/p>\n
What to do now<\/h2>\n
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- Rule out access first: check that your priority pages are crawlable and indexable and that no AI search crawler is blocked through robots.txt, your CDN, firewall, WAF, or bot-management rules.<\/li>\n
- Build a verified source of truth for positioning, product facts, pricing, and terminology, then align your owned pages to it.<\/li>\n
- Compare how AI systems describe your brand against that source of truth, and correct the stale third-party pages that carry outdated claims.<\/li>\n
- Find questions where you hold evidence a competitor cannot reproduce, and structure that evidence with clear findings, headings, lists, tables, or Q&A formatting.<\/li>\n
- Decide which layer a problem sits in before picking a fix, since discoverability, clarity, authority, and trust each need a different one.<\/li>\n<\/ol>\n
FAQ<\/h2>\n
What are the four layers of an AI search strategy?<\/h3>\n
Brand discoverability, brand clarity, brand authority, and brand trust. Discoverability is whether AI systems can access your content, clarity is whether they describe it correctly, authority is whether they find evidence to include you, and trust is whether they recommend you.<\/p>\n
Why does the same AI prompt return different answers?<\/h3>\n
Each AI platform draws on different sources and weighs them differently, so the same prompt can come back with a different answer the next day.<\/p>\n
Can a brand be mentioned in an AI answer but cited somewhere else?<\/h3>\n
Yes. A brand can be named in an AI answer while the citation points somewhere else entirely, such as a G2 review page or a Reddit thread.<\/p>\n
Related coverage<\/h2>\n
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