What an AI search audit should deliver

An AI search audit should leave you with an explanation you can trace, priority fixes someone has implemented, and a handoff you can use afterward. Ask how the assessment becomes a decision, which repairs are included, and what proves each repair is complete. A score alone won’t answer those questions.

JAC’s AI Audit is a one-time engagement. It includes a documented assessment, competitor and customer intelligence brief, agreed priority fixes, recorded walkthrough, and playbook. This article explains how to inspect that work and decide whether an audit fits, rather than treating every visibility concern as a reason to start monthly work.

What decision should the assessment support?

Name the question before collecting answers. You might need to understand an inaccurate integration claim, an absent product mention, or a priority page that search systems haven’t reached. The assessment should preserve those distinctions and identify what is still unknown.

A product-facts record gives the checks a reference. It can include the intended buyer, supported workflow, integrations, setup requirements, and limitations, with a current source or responsible fact owner. Private facts need separate permission before being submitted to an outside service.

The answer record should retain the question, platform and surface, date, visible settings, evidence, and run status. Search answers can contain incomplete or incorrect citations, so inspect the linked source and the claim it supposedly supports.

A missing mention, missing owned citation, and incorrect description call for different follow-up checks. Diagnosing why ChatGPT misses a SaaS product explains that separation before you choose a repair.

What belongs in the intelligence brief?

The brief should help choose work. For customer intelligence, ask what evidence supports the buyer questions and objections, when it was gathered, and what permission governs its use. Available sales notes or product questions can be useful; invented buyer quotes can’t fill gaps.

For competitors, compare the same buying questions and inspect the pages or sources that appear. Record differences in access or sampling. Don’t rank a company from completed checks for one product and failed requests for another.

Separate observation from explanation. A competitor appearing in an answer is an observation. Claiming that its FAQ format caused that appearance needs evidence beyond the answer itself. A useful brief can recommend inspecting the cited page without pretending the cause is known.

Google warns against special AI markup and pages for every query variation. That guidance applies to Google Search. It supports checking ordinary eligibility and useful coverage there, not selling a universal shortcut to every platform’s answers.

The brief should finish with a prioritized issue, the evidence behind it, and a reason for the proposed work. If the facts or access don’t support a defensible repair yet, that limitation belongs in the handoff.

What turns an issue into a fix?

A repair needs a changed object, a scope boundary, and a completion check. The following is a constructed teaching example, not a client observation or result.

Suppose a fictional handoff product supports CSV imports and requires someone to assign the delivery owner. An inspected answer claims it automatically syncs every CRM. The verified fact sheet contradicts that claim, and the existing integration page doesn’t explain the limitation clearly.

A scoped repair could update that page with the supported import method and owner-assignment step. The completion check would confirm the text matches the product documentation, its links work, and the intended public URL displays correctly. Repeating the original question provides a separate outcome observation.

An issue record could contain:

• Evidence. Saved answer, linked sources, and the checked product facts.
• Included work. The agreed integration-page clarification.
• Excluded work. Building a native CRM connection or rewriting every page.
• Dependency. Verified facts and access to edit the existing page.
• Completion. Published text, links, and page behavior pass the agreed checks.
• Repeated observation. The same question, recorded settings, and later answer or failure.

The page repair can be complete while the outside answer remains inaccurate. Keep both states visible. The AI audit workbook lets you practice this issue-to-repair method yourself.

Which access and inputs are required?

Required access depends on the agreed work. A page change needs editing access and verified facts. An indexing investigation may need a property owner to supply inspection evidence. A hosting repair may need the person who controls robots rules or the firewall.

Search and training permissions are separate. OpenAI’s crawler documentation distinguishes the relevant agents. An assessment should respect the business’s intended policy rather than quietly enabling every bot or weakening security controls.

Confirm readiness before kickoff. Agree the priority issues, included repairs, inputs, access, and acceptance checks. Identify what can’t be completed within the scope. A repair list assembled after the deadline starts is a weaker buying agreement than one both sides can inspect before work begins.

If an agreed repair becomes blocked afterward, it stays incomplete. JAC’s deadline doesn’t pause or reset automatically. A changed scope or deadline requires your agreement, so an access problem can’t silently become an accepted exception.

How do you judge the handoff?

Trace each issue to its evidence and repair. Open the changed URLs, inspect the completion checks, and watch the recorded walkthrough. The retained playbook should explain how to repeat the assessment and what a new issue would require.

An assessment score summarizes the checks used. It isn’t market share, a validated growth measure, or a forecast. Repeated assessment checks, shipped repairs, and outside observations need separate records, including completed-check denominators and unavailable data.

Native reports also have boundaries. Bing’s AI Performance citation counts don’t show rank or individual-answer placement. Keep those aggregates separate from inspected answers, visits, booked calls, held calls, and qualified conversations.

JAC’s delivery promise is under two weeks from confirmed kickoff, once scope, required inputs, and access are ready. The kickoff and deadline are agreed in writing. The complete agreed handoff must arrive before 14 calendar days have elapsed, including the assessment, intelligence brief, implemented fixes, completion checks, repeated assessment checks, walkthrough, and playbook. If it misses that deadline, no audit fee is owed, and paid audit fees are returned. This is a delivery promise, not a ranking, citation, or sales guarantee.

Does the audit require monthly continuation?

No. The assessment, implemented fixes, brief, recorded walkthrough, and playbook stand on their own. Jared handles the research, writing, and implementation, with a shared Slack channel for progress, questions, and context.

The AI search overview describes the research, page work, and technical foundation. Recurring work is a separate decision. If you already know you need ongoing page improvements, technical work, and monthly reporting, AI Search & SEO can start directly. You don’t need to buy the audit first. The AI purchasing test provides a way to examine the task and acceptance evidence before choosing either service.

Choose one buying question and one priority URL, then decide whether you need a bounded assessment with fixes or recurring work. The AI Audit service page contains the current price and terms. Book a call to agree what needs checking, what can be repaired, and what the handoff must contain.