52 checks across 7 sections — see exactly where your site stands for AI citation before spending a cent on optimization.
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Work through each section and check off what you already have in place. 52 checks, 7 sections. Your progress saves automatically — come back any time. When you're done, jump to our full AEO playbook for the rollout plan that turns these signals into citations — or use the free AEO Scan below to see what AI engines actually say about your brand today.
Want a printable version? Download the AEO Readiness Checklist PDF — same 12 core questions, formatted for printing or sharing with your team.
Download PDFThe infrastructure AI crawlers need to index, parse, and trust your content.
GPTBot, ClaudeBot, PerplexityBot, and Googlebot-Extended are explicitly allowed (or not blocked) in your robots.txt. Disallowing them is the #1 silent AEO killer — your content can't be cited if it can't be crawled.
LCP under 2.5s, FID under 100ms, CLS under 0.1 on key pages. Slow pages get crawled less frequently — outdated content gets cited less. Speed affects crawl freshness, which directly affects AEO.
All content renders fully on mobile — no truncation, broken layouts, or JS-dependent sections that fail without interaction. AI crawlers increasingly use mobile user agents; partial renders mean partial indexing.
Your homepage's opening paragraph names what you are, who you serve, and what problem you solve — clearly, without fluff. AI engines use this as the primary citation extract when asked "what is [your brand]?"
Your entire site is served over HTTPS with no mixed content warnings. AI systems and search engines treat insecure pages as lower-trust sources — HTTPS is a non-negotiable trust baseline.
You have a sitemap.xml that includes all key pages with accurate lastmod dates, submitted to Google Search Console. Outdated or missing sitemaps mean AI training data misses your newest, most authoritative content.
Every page has a self-referencing canonical tag pointing to its preferred URL. Duplicate content without canonicalization splits citation authority across multiple URLs, diluting your AEO signal.
Your primary content pages have no 404 internal links. Broken link chains signal a poorly maintained site — AI systems factor site health into citation confidence for domains they regularly crawl.
Schema.org markup tells AI engines exactly what your content represents — without it, they guess.
Your homepage has an Organization JSON-LD block with name, url, logo, description, and sameAs links to your social profiles. This is the entity anchor that connects all your other schema to a verified business identity.
Every page with FAQ-style Q&A content has FAQPage JSON-LD markup. AI engines extract FAQ answers directly from schema and cite them verbatim in responses. Unmarked FAQs are invisible to this extraction layer.
Each blog post and long-form guide has Article or BlogPosting JSON-LD with headline, author, datePublished, dateModified, and image. Authorship and freshness signals in schema help AI systems rank citation reliability.
Key product or feature pages use Product or SoftwareApplication schema with name, description, offers, and applicationCategory. When users ask AI "what tools do X?", products with schema surface ahead of those without.
Step-by-step guides and tutorial pages use HowTo JSON-LD with each step named and described. AI engines treat HowTo schema as directly extractable answer content for "how do I…" queries — a high-value citation format.
Content pages include BreadcrumbList JSON-LD that maps the page's position in your site hierarchy. Breadcrumb schema reinforces topical context — AI systems use it to understand content relationships across your site.
Your homepage includes a WebSite JSON-LD block with a SearchAction pointing to your site search. This establishes your domain as a navigable knowledge resource — a positive trust signal for AI engines evaluating source authority.
All JSON-LD passes Google's Rich Results Test and Schema.org validator with no critical errors. Invalid schema is silently ignored — you get none of the citation benefits while believing you're covered.
How your content is structured determines whether AI engines can extract and cite it cleanly.
You have stand-alone FAQ pages (not just buried accordions) that mirror the exact questions your buyers type into AI engines. Pages with FAQPage schema and clear Q&A structure get directly extracted into AI answers.
Your content answers questions conversationally — the way a knowledgeable colleague would explain them — without keyword stuffing or jargon. AI engines extract clean, citable sentences; dense or hedged prose gets paraphrased or skipped.
Your content pages are focused: each one answers a single, well-defined question as its primary purpose. Topic sprawl — a single page trying to cover five different queries — dilutes citation signal and confuses AI extraction.
You have dedicated "X vs Y" or "[your brand] vs [competitor]" pages. When buyers ask AI "which tool is better — X or Y?", having a comparison page with clear structured arguments makes your perspective directly citable.
Your content uses H2/H3 headers to signal topic sections, bullet lists for parallel items, and tables for comparisons. AI engines extract structured content more reliably than prose paragraphs — formatting is a citation accelerant.
Your About page identifies the people behind the company by name, with roles and brief credentials. Named authors and teams are a key E-E-A-T signal — AI systems treat anonymous content as lower-authority by default.
Each product or feature page clearly states the problem it solves, how it solves it, and why it's better than the alternatives — in plain language. When AI answers "what does [product] do?", these three elements form the citation.
You have definitional pages for the core terminology in your market — written as clear, citable definitions (not marketing copy). AI systems pull from glossary-style content disproportionately for definitional queries about your space.
AI engines weight source authority. These signals tell them your content is worth citing.
Your domain has editorial backlinks from recognized industry publications, analyst reports, or respected blogs in your category. AI systems factor third-party link authority into citation decisions — zero inbound links = low-trust source.
Every blog post, guide, and long-form page shows a named author with a bio that includes their relevant expertise. Bylined content scores higher on E-E-A-T signals that AI systems use to evaluate citation reliability.
Your brand appears by name in external articles, reviews, or listicles that aren't directly controlled by you. AI training data includes these third-party mentions — being named externally tells AI systems your brand is a real, recognized entity.
Your site explicitly states what makes you different from at least three named alternatives — not just vague claims like "the best," but concrete differentiators. AI answers comparison queries by extracting stated differentiators from each brand's content.
Testimonials, case studies, or customer logos appear prominently on your site — with named customers and specific outcomes where possible. AI systems use social proof as a proxy for real-world adoption when evaluating citation worthiness.
Your domain name, brand name, and product name have stayed the same for at least a year across your website, social profiles, and external mentions. Name changes fragment entity recognition in AI training data — consistency builds brand identity.
You explicitly state the market category your product belongs to — using the same category name your buyers would use when asking AI. Products that don't name their category get lumped into vague "software" or "tool" buckets in AI responses.
Breadth and depth of coverage determines which queries AI engines can cite you for.
Your most important pages have been updated within the last 90 days and have accurate dateModified timestamps in their Article schema. AI systems trained on recent data weight fresh content — stale pages get cited less as information ages.
You've published new content on at least a monthly cadence for three or more months. Consistent publishing signals an active, maintained knowledge base — one-time content dumps don't build the freshness signal that AEO requires over time.
You publish in at least three formats: written guides, structured comparison tables, FAQ pages, and/or how-to content. AI systems pull from diverse content types — multi-format coverage increases citation surface across different query patterns.
Your most important category and topic pages are comprehensive — not shallow overviews. AI engines use topical depth as a quality signal; thin content on core topics gets skipped in favor of more thorough sources.
Related pages link to each other with descriptive anchor text — forming topical clusters. Internal link structure tells AI systems which pages are central to a topic, reinforcing citation authority for your pillar content.
You've mapped which queries competitors rank for that you don't yet cover, and have a plan to address them. AI citation is a zero-sum game on many queries — if a competitor has content on a topic and you don't, they get cited and you don't.
Experience, Expertise, Authority, and Trust (E-E-A-T) signals are embedded across your content: author credentials, first-hand experience claims, data sourced from your own research, and clear editorial standards. AI systems weight E-E-A-T when choosing which sources to trust.
Signals that go beyond traditional SEO — built specifically for how AI engines retrieve and cite content.
You have a plain-text file at yourdomain.com/llms.txt that tells AI crawlers what your product does, who it's for, and which pages are most authoritative. OpenAI and Anthropic have indicated they use this signal during training and retrieval.
Your brand name doesn't share a name with other companies, common words, or concepts in your space. Ambiguous brand names cause AI engines to conflate your content with unrelated entities — citation accuracy drops significantly.
Your pages answer the primary question in the opening paragraph — before any background, context, or preamble. AI engines extract the first complete answer they encounter; burying the answer after three paragraphs of context means it often gets missed.
Statistics, benchmarks, and factual claims link to primary sources — original studies, your own research, or authoritative reports. AI systems are more likely to cite sourced claims and flag or omit unsourced data, especially in domains where accuracy matters.
You use the exact same brand name spelling and capitalization everywhere — in page text, meta tags, schema markup, and external mentions. Inconsistent naming (e.g., "AIGrowthNav" vs "AI Growth Nav") fragments entity recognition across AI training data.
Pages with information that changes over time (pricing, statistics, best practices) include explicit date markers like "As of Q2 2026" in the content itself — not just in metadata. AI systems use these to assess freshness and avoid citing outdated information as current.
Your content makes direct, confident statements ("X does Y") rather than passive or hedged language ("it might be argued that X could potentially…"). Active, declarative prose is extracted verbatim by AI; hedged language gets paraphrased or softened into vagueness.
You can't improve what you don't measure. These are the tracking baselines every AEO program needs.
You've run an initial AEO audit and have a documented baseline score — so you can measure improvement over time. Optimization without a baseline is guesswork; you need a starting point to know if your changes are working.
You have a repeatable process for checking how often and how accurately your brand is cited in ChatGPT, Perplexity, Claude, and Google AI Overviews responses — at least monthly. Manual spot checks or automated scans both count.
You have a trigger that alerts you when citation rates fall below an acceptable threshold — so you can catch and address drops before they compound. Undetected AEO regression can silently erode your visibility for months before anyone notices.
GSC is set up for your domain, your sitemap is submitted, and someone reviews it at least monthly. GSC shows which queries drive impressions and clicks — this data is the closest proxy available for understanding where AI engines surface your content.
You have analytics segments or UTM conventions that identify visits from AI referrers (perplexity.ai, chat.openai.com, etc.). Without this segmentation, AI-sourced traffic gets lumped into "direct" and you can't measure the commercial impact of AEO.
You periodically check which queries your competitors are being cited for — not just which queries you appear in. Understanding citation gaps relative to competitors is how you prioritize which new content will have the highest AEO ROI.
You have a calendar reminder to re-run this checklist and your AEO scan every quarter. AI search evolves rapidly — what gets you cited today may not be sufficient in six months, and new signals emerge regularly as these systems are updated.
The checklist shows where you stand in theory. The free scan tells you what ChatGPT, Perplexity, Claude, and Google AI Overviews actually say about your brand — right now.