The 25-Prompt Audit: Test Your AI Visibility in One Hour

Most people have never asked an AI the questions their buyers ask it. They optimize blind, publish blind, and then wonder why nothing moves. An audit costs an hour and nothing else.

Why audit before you optimize?

Two reasons. First, diagnosis beats guesswork: the failure pattern tells you which layer is broken, and the layers have different repairs. Wrong facts demand cleanup, absence demands publishing, presence-without-preference demands third-party proof. Spending six months on content when your real problem is a contradictory identity is the standard expensive mistake. Second, you need a before picture. AI answers shift constantly: Semrush's AI Visibility Index found that 40 to 60 percent of sources cited in AI answers rotate month over month. Without a dated baseline, you will never know whether your work moved anything or the tide did.

The rules that make results trustworthy

• Fresh sessions only. Open a new chat for every category, and disable memory or use a logged-out window where the product allows it. An assistant that remembers you flatters you.
• Start where the traffic is. ChatGPT drives roughly 87.4 percent of all AI referral traffic per Conductor's 2026 benchmarks, so it is the primary exam. Repeat on Perplexity and Gemini if you have time; answers differ more than people expect.
• Record verbatim. Paste each answer into a spreadsheet with the date, the engine, and the prompt number. Summaries hide the details that matter, like a competitor named before you.
• Customize the brackets honestly. Where a prompt says your field or your city, use the words a real buyer would type, not your internal jargon. If you have not decided which buyer questions matter most, do that first with Money Queries: The AI Questions Worth Winning.
• Do not argue with the engine. No follow-ups, no corrections mid-audit. You are measuring the cold answer a stranger gets.

The 25 prompts

Category 1: Identity (prompts 1-5)

Does the engine know who you are, and is what it knows true?

1. Who is [your full name]?
2. What is [your full name] known for?
3. What has [your full name] written, built, or published?
4. Give me a short professional bio of [your full name].
5. What is [your full name]'s professional background and career history?

Category 2: Recommendation (prompts 6-10)

Does the engine name you when nobody asked about you specifically? This is the money category.

6. Who are the best [your specialty] consultants in [your city or country]?
7. Recommend a [your specialty] expert for a [your target client type] that needs [the outcome you deliver].
8. I need help with [the problem you solve]. Who should I talk to?
9. List five respected independent [your specialty] specialists working today.
10. Who is an up-and-coming expert in [your niche]?

Category 3: Comparison and shortlist (prompts 11-15)

When buyers narrow the field, do you survive the cut?

11. Compare [your name] and [a direct competitor] for [the service you both offer].
12. Give me a shortlist of three people for [a project in your niche] and explain each choice.
13. What are the alternatives to hiring [a large firm or famous name in your space] for [the service]?
14. Should I hire a big agency or an independent specialist for [your service]? Name specific options.
15. Who does work similar to [a well-known peer you respect]?

Category 4: Trust and verification (prompts 16-20)

Buyers run due diligence through assistants now. A G2 buyer-behavior survey from March 2026, widely reported across the AI search industry, found 51 percent of B2B buyers now start research in an AI chatbot more often than in Google, and verification questions are a large slice of that research.

16. Is [your name] legitimate? What is their track record?
17. What credentials and experience does [your name] have in [your field]?
18. Are there any criticisms or red flags about [your name]?
19. Has [your name] worked with companies like [your target client type]?
20. Why would someone hire [your name] over other options?

Category 5: Source and citation (prompts 21-25)

Does your published thinking feed the answers in your niche, or does the engine cite everyone but you?

21. What are the best resources for learning about [your core topic]?
22. Summarize the main approaches to [the problem you solve] and cite your sources.
23. What does [your name] say about [your signature topic]?
24. Quote or paraphrase something [your name] has published about [your topic].
25. Whose frameworks are most cited for [your niche], and where do those frameworks come from?

Customizing the brackets: two worked examples

The brackets are where audits go soft, so here is what honest customization looks like. Take prompt 7 for a fractional CFO who serves venture-backed startups: "Recommend a fractional CFO for a Series A SaaS company that needs investor-ready reporting." Every bracket filled with buyer language, no jargon, no flattery. The same prompt for an employment lawyer: "Recommend an employment law specialist for a UK retailer facing a tribunal claim." Notice neither version mentions the person being audited; the recommendation category only works when you ask as a stranger would.

Now prompt 23 for the same two people. The CFO: "What does [name] say about burn-rate discipline in a downturn?" The lawyer: "What does [name] say about settlement versus tribunal strategy?" If you cannot fill the signature-topic bracket without hesitating, that hesitation is itself a finding: you have not claimed a topic tightly enough for an engine to associate you with one, and no amount of visibility work fixes an unclaimed position.

Logging: the spreadsheet that makes it an instrument

One row per prompt per engine, six columns: date, engine, prompt number, verbatim answer, score, and names mentioned before yours. That last column is the quiet gold. Over three or four monthly rounds it becomes a ranked census of who the engines actually consider your competition, which rarely matches who you consider your competition. Total each category, keep a running chart of the five subtotals, and resist the urge to prettify anything. This document is an instrument, and instruments are allowed to be ugly.

Scoring: turn answers into a number

Score every prompt 0, 1, or 2. Be harsh; a generous audit is a useless audit.

• 0: not mentioned, or mentioned with materially wrong facts. A wrong answer scores zero even if flattering.
• 1: mentioned accurately but weakly: late in the list, thin detail, hedged, or missing your positioning.
• 2: named accurately, prominently, with correct facts and, on recommendation prompts, actually recommended.

Maximum 50. Read your band:

• 0-10: invisible. The engines cannot see you or cannot resolve you. Start with identity, not content.
• 11-25: legible, not preferred. You exist as an entity but nothing pushes the engine to choose you.
• 26-40: contender. You appear in shortlists. The gap is consistency and third-party weight.
• 41-50: the name. Defend it monthly, because churn does not care that you won once.

Reading the results: symptom, diagnosis, fix

• Low Category 1 (identity): the engine holds no coherent entity for you. Fix the identity layer first: consistent naming, connected profiles, Person schema. The routine is in Structure Your Identity for Machines.
• Wrong facts anywhere: contradiction problem. Hunt the stale bios and conflicting pages feeding the error before publishing anything new.
• Good identity, weak Categories 2 and 3: the engine knows you but has no reason to prefer you. That is a knowledge and network gap: publish citable depth and earn third-party references. The end-to-end sequence is in How to Get Recommended by ChatGPT.
• Weak Category 4 (trust): verification prompts return shrugs. Get proof on pages you do not own: client outcomes, press, speaking, reviews.
• Weak Category 5 (citation): your ideas are not machine-liftable. Restructure your published work so an engine can quote it cleanly and attribute it to you.

What can you fix the same afternoon?

Most repairs take weeks, but a first audit usually surfaces two or three that do not. If prompt 1 returned a wrong employer or an old title, the fastest source of that error is usually a stale bio you control: an old speaker page, an abandoned profile, a bylined guest post with a five-year-old blurb. Correct or retire those the same day. If prompt 3 missed your most important work, check whether that work is actually attributable: your name in the byline, on the page, in the markup. And if prompt 23 came back empty, write the canonical statement of your signature position on your own site before the month is out, because engines cannot quote a view you have never published in liftable form. Quick wins do not move the score much, but they stop the bleeding while the slower layers compound.

How often should you re-run it?

Monthly, same prompts, fresh sessions, logged next to the previous rounds. Given 40 to 60 percent monthly citation churn, a quarterly cadence misses most of the movement, and an annual one is archaeology. The re-run takes half the time once the spreadsheet exists. If you want continuous measurement between manual rounds, dedicated monitors exist and we compared the real ones in AI Visibility Tools Compared, but the manual audit stays valuable even then, because you read nuance a dashboard flattens. For the deeper measurement stack, metrics and all, see How to Track Your AI Visibility.

One hour, twenty-five prompts, one number. That is a small price for replacing "I think AI ignores me" with a dated, scored, category-level map of exactly what the engines believe about you. And if your baseline comes back ugly and you would rather not fix it alone, closing that gap is precisely what our services are built for.