To run an AI visibility audit, work through six steps: baseline your current visibility across platforms, benchmark against competitors, check your technical readiness, review your content, review your off-site and entity signals, and prioritize the findings into an action plan. The audit combines a measurement of where you stand now with an assessment of the readiness factors that determine where you can get to, producing a ranked list of what to fix first.
In short
- An audit measures your current visibility and assesses the readiness factors behind it.
- Six steps: baseline, competitor benchmark, technical check, content review, off-site review, prioritize.
- The output is a ranked action plan, not just a score.
- Fix foundational technical issues first, since content and authority work depends on them.
What does an AI visibility audit cover?
An AI visibility audit covers two things: how visible you are in AI answers right now, and how ready your site and presence are to be surfaced and cited. The first is the symptom, the second is the cause, and a good audit connects them.
This dual focus is what makes an audit actionable rather than just descriptive. Measuring your current visibility, your presence, share of voice, rank, sentiment, and citations, tells you where you stand, but on its own it does not tell you what to do. Assessing the readiness factors, your crawlability, content, and off-site authority, explains why your visibility is what it is and what to change to improve it. An audit that does both produces a clear path from problem to action, which is why it is a sensible early step in the overall sequence set out in the AI visibility how-to playbook. The six steps below move from measuring the symptom to diagnosing the causes to prioritizing the fixes. This is the practical companion to the conceptual treatment in how to run an AEO audit and the measurement reasoning in how to measure AI visibility.
How do you baseline visibility and benchmark competitors?
You baseline visibility by running a representative set of customer questions across the AI platforms and recording your presence, and you benchmark competitors by doing the same for them on the same questions. These first two steps establish where you stand, both absolutely and relative to rivals.
Work through them in order. For the baseline, assemble a set of questions a customer would ask in your category, ask them across the platforms that matter to you, and record for each whether you appear, how prominently, how you are described, and which of your pages or sources are cited, which gives you your starting visibility score, share of voice, average rank, and sentiment. Choosing those questions well is the same skill as building a prompt set, covered in how to build a tracked prompt set. For the competitor benchmark, run the same questions noting which competitors appear, how prominently, and which sources are cited when they win, which reveals where rivals are beating you and what is behind it, the gap-analysis logic covered in how to do an AI citation gap analysis and how to benchmark against competitors in AI search. Together these two steps tell you not just whether you are visible but where your biggest competitive gaps are.
How do you check technical readiness and content?
You check technical readiness by confirming AI systems can actually access and read your content, and you review content by assessing whether your pages are structured and evidenced in the way AI tends to favor. These steps diagnose the on-site causes behind your visibility.
The technical check comes first because it is foundational. Confirm that AI crawlers can access your site and are not blocked, that your important content renders without requiring client-side JavaScript, and that the basics like sitemaps and indexability are sound, the issues covered in how AI crawlers work and how to fix JavaScript rendering for AI, and verifiable in your logs as covered in how to set up AI crawler tracking in your server logs. A page AI cannot read cannot be cited, so any failure here outranks everything else. The content review then assesses whether your priority pages answer questions directly, are clearly structured with descriptive headings, include evidence like statistics and citations, and are current, the qualities covered in AEO and GEO. Reviewing your most important pages against these criteria shows where content improvements will help, which feeds directly into your action plan.
How do you review off-site signals and prioritize?
You review off-site signals by assessing your presence and reputation across the web, and you prioritize by ranking all the findings by impact and dependency into a sequenced action plan. These final steps turn the audit from a diagnosis into a plan.
The off-site review looks beyond your own site, since much of AI visibility is won there. Assess how your brand is mentioned across the web, whether your entity information on knowledge bases like Wikipedia and Wikidata is accurate, your presence on the review platforms relevant to your category, and whether you appear in the third-party sources AI cites for your prompts, the work covered in GEO, how Wikipedia and Wikidata presence affect AI visibility, and what is a citation source analysis. Finally, prioritize: gather every finding and rank it by impact and dependency, putting foundational technical fixes first, then the highest-value content and competitive gaps, then the off-site authority work that compounds over time. This sequencing reflects the rough impact hierarchy, technical as a gate, content as the measurable lever, off-site authority as the highest ceiling, that guides where to start. The result is a ranked action plan you can execute, which is the real output of an audit, far more useful than a single score.