AI Visibility Audit Deliverable: What an Audit Should Include
The artifact you actually hand the client. A section-by-section breakdown of an AI visibility audit — what each part shows, and why it earns its place in the deliverable.
An AI visibility audit deliverable should move from presence (where the domain is cited or mentioned today) to context (which competitors share those queries) to opportunity (the gap of queries it could be present on) and end with recommendations. Every section maps a finding to a client decision.
What an AI visibility audit is for
The audit is the first paid artifact most AI visibility engagements produce, and often the thing that wins the retainer. Its job is to turn an abstract worry — “are we showing up in AI answers?” — into a concrete, query-level picture the client can act on. A good audit is not a screenshot of a dashboard; it is a structured document where every finding leads to a decision.
You can generate the raw baseline for free with a Domain Check, then shape it into the deliverable below.
The sections of the deliverable
Each section answers a different question the client will ask. The right-hand column is the test: if a section does not produce client value, cut it.
| Section | What it shows | Client value |
|---|---|---|
| Executive summary | The headline state in plain language | A non-technical stakeholder can grasp it in 60 seconds |
| Presence baseline | Distinct queries the domain is cited / mentioned on | An honest starting line to measure against |
| Model coverage | Presence split across ChatGPT, Gemini, Grok | Shows which assistants reach their audience and which do not |
| Intent breakdown | Queries grouped by informational vs. commercial | Connects presence to where buying decisions happen |
| Competitive context | Competitors appearing on the same queries | Frames performance as relative, not absolute |
| Keyword gap | Queries competitors are cited on, client is not | The opportunity list that justifies the engagement |
| Risk notes | Queries recently lost or slipping | Surfaces problems before the client finds them |
| Recommendations | Prioritized next moves tied to real queries | Turns the audit into a plan, not just a diagnosis |
Section detail: the four that carry the audit
Presence baseline
Lead with the count and the list of distinct queries where the domain is already cited or mentioned. Show the actual queries. This is the most credible page in the document because it is verifiable — and it sets the reference point every later report compares back to.
Competitive context
For the highest-value queries, name the competitors that appear alongside or instead of the client. This is the section that reframes the conversation from “how are we doing” to “how do we beat them.” If you ran a competitive audit before the pitch, much of this is already done.
Keyword gap
The gap is the opportunity. Pull it from an AI keyword gap analysis: the queries competitors are cited on where the client is absent. This section is the argument for the entire engagement, so make it specific and prioritized.
Recommendations
Close with a short, ordered list of moves, each tied to a real query from the audit. Frame outcomes as presence and trend improvements over time — never as a guaranteed citation on a named query.
Delivery checklist
- Every number traces back to a real, nameable query — no invented scores.
- The executive summary is readable by someone who has never heard of GEO.
- Competitors are named on the queries where they actually appear.
- The gap list is prioritized, not just dumped.
- Recommendations are ordered and each maps to a query in the audit.
- No language guaranteeing AI rankings or specific citations anywhere.
From audit to engagement
The audit is designed to flow straight into onboarding. Once the client signs, the baseline and gap list become the first inputs to your 30-day onboarding plan, and the reporting sections become the template for your monthly reporting cadence. If you are evaluating what powers the audit, compare the tools.