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A credible audit does not end with a visibility score. It provides the evidence behind the score and a prioritized implementation plan.
What an AI search audit should answer
- Which questions represent real customer, buyer, and stakeholder demand?
- On which AI platforms and markets can those questions be measured reliably?
- When is the brand mentioned, recommended, omitted, or described inaccurately?
- Which competitors occupy the answer positions the brand needs?
- Which official and external pages are cited?
- Does each important question have a complete website owner?
- Which actions can be retested without changing the measurement method?
If an audit cannot connect a finding to a prompt, response, URL, and owner, the recommendation will be difficult to verify.
The UnderAI audit method
1. Scope the business decisions
We begin with products, markets, audiences, competitors, and the decisions the audit must support. Brand awareness, product selection, procurement, technical evaluation, and reputation questions require different prompts and success rules.
2. Build a source-labeled Prompt Library
Prompts are collected from real market evidence where possible: search demand, sales questions, support issues, category language, competitor positioning, and observed AI-answer tasks. Generated candidates are labeled as generated. They do not become “market demand” merely because a model proposed them.
3. Freeze the measurement panel
The approved subset is fixed before baseline collection. The panel records exact wording, platform, market, language, date, repetition, and success status. This prevents a later prompt change from being mistaken for performance improvement.
4. Collect answer-level evidence
For each successful response, the audit preserves:
- full answer text;
- brand and competitor mentions;
- recommendation position;
- Sentiment;
- Citation URLs and domains;
- collection status, platform, and timestamp.
Platform failure, missing export, a successful response with no mention, and a successful response with no citation remain separate states.
5. Diagnose three kinds of gaps
| Gap | Evidence | Typical action |
|---|---|---|
| Answer gap | Competitor appears; target brand does not | Clarify positioning, proof, and use-case coverage |
| Official page gap | Competitor official page is cited; target owner is missing or weak | Create, consolidate, or rewrite the page owner |
| External source gap | Third-party source repeatedly supports the answer | Develop credible external evidence or source relationships |
6. Prioritize by demand, gap, and feasibility
The audit distinguishes “important” from “possible.” A high-demand topic with no page owner may be a rapid publication. A desired external citation from an inaccessible publisher is a strategic gap, not an immediate deliverable.
7. Define the retest
Each action receives a target prompt set, success metric, acceptance check, publication version, and earliest useful retest date. The goal is attributable learning, not a before-and-after chart built from incompatible conditions.
What you receive
An UnderAI AI Search Audit can include:
- business and competitor scope;
- source-labeled Prompt Library and approved baseline panel;
- collection manifest and missing-data report;
- Visibility, TOP3, Sentiment, and Citation evidence;
- competitor answer and source-gap analysis;
- question-to-page owner map;
- website content and technical priorities;
- external source priorities;
- implementation roadmap and retest plan.
The exact scope is agreed before collection. Public pricing is not listed; the engagement is scoped to the number of markets, platforms, prompts, products, and competitors.
Software plus reviewed diagnosis
UnderAI GEO Workspace supplies the ongoing measurement layer: workspaces, Tracking Projects, Prompt Groups, daily platform results, Answer Snapshots, Sentiment, and Citation evidence. The managed audit adds prompt research, human review, gap diagnosis, page ownership, and implementation priorities.
This separation matters. Software can organize repeatable observations; an audit must still decide whether the questions are representative, the data is usable, and the proposed action follows from the evidence.
Request an AI Search Audit or review UnderAI GEO Workspace.
Example: what an audit conclusion should look like
UnderAI’s July 2026 category baseline showed why an audit needs more than one composite visibility score. The complete denominator and Citation results are reported in the AI Citation Rate Benchmarks and Most Cited Domains study.
A weak audit would report only “UnderAI visibility is 0%.” A decision-ready audit would show:
| Finding | Evidence | Decision |
|---|---|---|
| Brand absence was confirmed only in successful answers | Entity matching and collection status were reviewed separately | Establish the brand and product answer assets before optimizing position |
| Other sources were active | Response-to-URL evidence showed where answers obtained support | Build exact official and external source-gap maps |
| Competitor sites supplied category evidence | Specific cited pages and evidence modules could be inspected | Compare the evidence those pages provide and assign an owner for the Gap |
| Two Google routes were unavailable | 96 planned units failed | Repair or replace the collection route; do not report zero Google visibility |
The output is useful because each conclusion names an evidence state and a next decision. It does not convert a dashboard observation into a vague request for more content.
Audit quality controls
Before accepting an audit, verify that every aggregate can be reconciled to an answer record and that current platform facts are sourced. Google’s Search documentation says AI Overview and AI Mode eligibility follows the same core indexing requirements as Search; there is no special AI markup that can substitute for accessible, helpful pages. See AI features and your website.
Frequently asked questions
How long should an AI search audit take?
It depends on markets, platforms, prompt volume, and review depth. The scope should be defined in observable units rather than a generic duration promise.
Can an audit guarantee better AI visibility?
No. It can identify defensible actions and establish a way to measure change. AI answers remain variable and are influenced by many sources outside one website.
Is an SEO audit enough?
An SEO audit remains important for crawlability, indexing, content quality, and authority. An AI search audit adds answer-level mentions, positions, Sentiment, citations, prompt coverage, and source adoption.
Should failed responses count as absence?
No. A failed or unavailable collection is missing evidence, not proof that the brand was absent.