How to Run an AI Visibility Audit: A Step-by-Step Framework for Any Brand

Most brands have no idea what AI says about them. This guide walks you through a complete AI visibility audit — the exact framework we use at Aethon AI to help brands understand their current position and build a strategy to improve it.

They’ve spent years optimizing for Google, building paid media campaigns, and managing their social presence — but they’ve never once checked how ChatGPT, Gemini, or Perplexity describes their business.

That blind spot is costing them customers. Right now, someone is asking AI for a recommendation in your category. What comes back in that conversation determines where their money goes. If you don’t know what AI says about you, you can’t fix what’s broken or build on what’s working.

Step 1: Identify Your Core Conversational Queries

Before you open any AI platform, you need to understand how your customers actually talk to AI. This is fundamentally different from keyword research. You’re not looking for search terms — you’re looking for real-life scenarios.

Start by thinking about the situations that lead someone to your business. Not the moment they search for you, but the moments before that. A plumber’s customers don’t start with “emergency plumber.” They start with “our pipes burst and there’s water everywhere — what do we do?” A financial advisor’s clients don’t start with “wealth management near me.” They start with “I’m about to retire and I have no idea if I have enough.”

Include competitor-adjacent queries too. If someone asks AI “is [competitor] good for [use case]?” does your brand come up as an alternative? These competitive moments reveal whether AI sees you as a viable option in your market.

Step 2: Test Across Multiple AI Platforms

A common mistake is auditing only ChatGPT. While it’s the most popular AI assistant, your customers use multiple platforms. A thorough audit should cover ChatGPT, Google Gemini, Perplexity, Claude, Microsoft Copilot, and Meta AI at minimum.

For each of your 15 to 20 conversational prompts, run the same query across every platform. Record whether your brand is mentioned, where it appears in the response, how it’s described, what competitors are mentioned, and whether the information about you is accurate.

You’ll quickly notice that different platforms tell different stories about your brand. You might be prominently featured in Perplexity’s responses (which pulls from real-time web data) but completely absent from ChatGPT (which relies more on training data). These discrepancies reveal exactly where your strengths and weaknesses are.

Pay special attention to the specific language AI uses to describe you. Does it get your value proposition right? Does it mention the right products or services? Does it position you accurately against competitors? Inaccurate AI descriptions are often more damaging than being absent entirely, because they create wrong impressions that are hard to correct once a customer has heard them.

Step 3: Map Your Competitive AI Landscape

Your audit results will reveal which competitors AI prefers over you — and why. This competitive intelligence is some of the most valuable data you can collect.

For every query where a competitor gets recommended instead of you, ask why. Look at their web presence. What content are they publishing that you’re not? Which publications mention them? What review platforms feature them prominently? What’s their overall digital footprint compared to yours?

Often, the brands AI recommends aren’t the biggest or the best-known. They’re the ones with the most comprehensive, helpful, and well-distributed content around the specific topics AI is being asked about. A smaller competitor with deep expertise content in a specific niche can outrank a market leader that only has surface-level marketing pages.

Document every competitor that appears in AI responses to your queries. Note which platforms mention them, what position they hold in the recommendation, and how they’re described. This competitive map becomes the foundation of your AI visibility strategy — because you now know exactly who you need to outperform and on which topics.

Step 4: Assess Your Content Authority Gaps

Now compare your audit results against your existing content. For every conversational query where your brand doesn’t appear, ask yourself: do you have content that directly addresses this topic? Not tangentially. Not in a product page footnote. Real, comprehensive content that would establish you as an authority on this specific subject.

Most brands discover significant gaps. They might have a great “about us” page and some product descriptions, but they lack the deep topical content that AI models need to form a strong impression of their expertise. A law firm might have practice area pages but no in-depth guides about the situations that drive clients to need a lawyer. A SaaS company might have feature lists but nothing about the real-world problems their software solves.

Prioritize gaps based on business impact. Which conversations lead to the highest-value customers? Which topics have the least competition? Where do you have genuine expertise that you haven’t yet translated into content? Focus there first.

Step 5: Evaluate Your Third-Party Signal Strength

AI models don’t just look at your own website. They weigh what others say about you — and this third-party validation is often the deciding factor in whether you get recommended.

Audit your external presence across several dimensions. Review platforms like Google Business, G2, Capterra, Trustpilot, and industry-specific sites are where AI models often pull recommendation data. Count your reviews, assess your ratings, and read the actual review content. AI models parse this language to understand your strengths and weaknesses.

Media mentions and press coverage tell AI that your brand is recognized by credible sources. Search for your brand name across news outlets, industry publications, and trade media. How often are you mentioned? In what context? Are you quoted as an expert, or merely listed as a participant?

Industry directories, association memberships, and certifications add credibility signals. Being listed in relevant professional directories tells AI that your brand has been vetted by your industry’s gatekeepers.

Backlinks from authoritative websites still matter. While AI visibility isn’t just SEO, the web of references pointing to your brand gives AI models a signal of how trusted and interconnected you are within your field.

The brands that AI recommends most confidently tend to have strong signals across all of these dimensions. If you’re strong on content but weak on reviews, or strong on media mentions but thin on industry validation, those gaps will limit your AI visibility.

Step 6: Build Your Action Plan

Your audit gives you a clear picture. Now you need to turn that picture into an action plan with specific priorities, timelines, and ownership.

In the first 30 days, focus on quick wins. Fix any inaccurate information AI has about you by updating your website, business listings, and review profiles. Ensure your core value proposition is clearly and consistently stated across every platform where AI might pull information. If your brand name, services, or positioning is inconsistent between your website, LinkedIn, Google Business, and other profiles, harmonize them immediately.

Over the next 60 days, start closing your content authority gaps. Begin with the highest-impact topics from your content gap matrix. Create comprehensive, genuinely helpful content for each one. Don’t write 500-word blog posts — create definitive resources that cover each topic thoroughly. Think 2,000 to 3,000 words minimum for pillar content, with supporting pieces that go deep on subtopics.

From 90 days onward, focus on building third-party signals. Pursue media coverage, guest contributions, speaking engagements, and strategic partnerships that generate mentions and references from credible sources. Encourage satisfied customers to leave detailed reviews. Build relationships with industry publications.

Throughout all of this, re-run your AI visibility audit monthly. Track changes over time. Note which actions produce improvements and which don’t. This iterative approach ensures you’re investing in what actually works rather than guessing.