What is an AEO audit?

Answer engine optimization focuses on helping AI systems understand your brand, associate it with the correct category, and extract information from your content when responding to user questions.

The goal is straightforward: Identify where AI systems fail to recognize your brand, then correct the structural signals that influence how those systems interpret and recommend companies.

What does an AEO audit evaluate?

When AI assistants generate answers about a category, they rely on a set of signals that help them understand which companies belong in that space and which sources are credible enough to reference.

An AEO audit examines whether those signals exist across your website and the broader web presence around your brand. 

Several factors influence whether AI systems recognize and recommend a company:

• Entity clarity

AI systems must be able to identify your company as a distinct organization and understand what it does. If the model can’t clearly interpret your brand or its role in the market, it becomes difficult for it to reference the company in generated answers.

• Category authority

Your brand needs to be consistently associated with the correct solution space. AI assistants frequently respond to questions such as “Who are the leading companies in [category]?” or “What platforms solve [problem]?” Clear category association improves the likelihood that your company appears in those responses.

• Answer ready content structure

AI assistants prioritize information that can be extracted quickly. Pages that present direct explanations, structured headings, and clear answers to common questions are easier for models to interpret and summarize.

• Citation and trust signals

AI systems rely on references across the web to evaluate credibility. Backlinks from reputable sources, industry coverage, and expert commentary reinforce authority and strengthen the likelihood that a brand will be referenced.

• Competitive presence in AI responses

An audit also reviews which competitors appear most frequently in AI answers and examines why their content is selected.

Together, these signals determine whether your brand becomes part of the AI model’s understanding of the category.

Step 1: Check brand visibility across platforms

Start by observing how AI assistants describe your category today. The goal in this step is simple: determine whether your brand appears in AI generated answers at all.

Run discovery prompts across major assistants such as ChatGPT, Claude, Gemini, and Perplexity. Focus on prompts that simulate how buyers begin their research.

Examples include:

• “What companies specialize in [category]?”
• “What platforms help companies with [problem]?”
• “What solutions are used for [specific use case]?”

Then review the responses and document what appears.

Pay attention to patterns such as:

• Is your brand mentioned?
• Are your website pages cited?
• Does the model provide recommendation lists?
• Do your competitors feature instead of you?

Looking across multiple assistants often reveals consistent patterns. If the same competitors appear in several answers while your company doesn’t, that’s an early signal that AI systems do not yet associate your brand strongly with the category.

Step 2: Test category association

Once you understand whether your brand appears in answers, the next step is to examine how AI systems classify your company.

Instead of asking category discovery questions, ask prompts that focus directly on your brand.

Examples include:

• “What does [Company Name] do?”
• “What category does [Company Name] belong to?”
• “What problems does [Company Name] solve?”

These prompts reveal how clearly AI systems understand your company.

Evaluate the responses carefully:

• Does the assistant recognize your company?
• Does it describe the business accurately?
• Does it place the company in the correct category?

When models misclassify a company or struggle to describe it clearly, the issue usually stems from inconsistent positioning across the web.

AI assistants learn from many sources. If those sources describe a company differently, the model develops a fragmented understanding of the brand and becomes less confident including it in category answers.

Step 3: Evaluate topic authority

AI assistants lean heavily on educational content when generating answers. If you're not producing it, they'll pull from whoever is — which is usually your competitors.

Look at creating: 

• Strategy content

Resources that explain how your company approaches a problem or category. 

• Educational explanations

Clear articles that define concepts, terminology, or processes. 

• Comparison content

Pages comparing tools, vendors, or approaches. 

• Industry insights

Research, commentary, or analysis that demonstrates expertise. 

When these resources exist, AI systems gain more material to learn from and cite. When they’re missing, the mode will rely on competitor content instead. 

Step 4: Review content structure for answer extraction

Content structure plays a major role in whether AI systems extract information from a page. 

So, during your audit, make sure to review whether key pages include: 

• Direct answers to common buyer questions
• Clear headings that describe the topic of each section
• Concise explanations that summarize key ideas

AI models scan for information they can interpret and summarize quickly. Pages that bury explanations in long narrative introductions are harder to extract from. 

Pages structured around questions and explanations tend to perform better because they mirror the format of the prompts users enter into AI tools. 

Step 5: Evaluate citation and authority signals

Because AI systems also rely on signals outside of your website, it’s good to review the broader ecosystem of references that are connected to your brand during the audit. 

Important signals to look out for include: 

• Backlinks from credible sources
• Mentions in industry publications
• Quotes from executives or subject matter experts
• Research reports or original data

These signals help reinforce authority within your brand’s category and increase the likelihood that AI assistants will encounter your brand while synthesizing information across sources. 

Step 6: Analyze competitors that appear in AI answers

When you see competitors show up frequently in AI answers, that’s telling you something. Not just who your competition is, but which signals AI systems trust most when deciding who belongs in a category.

Start by identifying which companies appear most frequently across AI assistants, then examine the pages and sources they reference.

Look for these patterns: 

• educational content explaining the category
• structured guides and frameworks
• strong industry citations
• clear positioning language describing the solution

These signals help AI systems infer the category, its functionality, and which companies belong to it.

It’s also useful to pay attention to how the AI describes those companies. The wording used in the response often reflects the language that appears most consistently across the web.

When multiple sources describe a company in similar terms, the model develops a clearer understanding of that brand’s role in the category. That clarity increases the likelihood that the company appears in recommendation lists or category explanations.

Studying this positioning can help explain why certain competitors appear consistently in AI-generated answers and what signals may be missing from your own presence across the web.

Step 7: Identify structural weaknesses

After reviewing visibility, category recognition, authority signals, and competitor positioning, the final step is identifying the structural gaps.

Common issues include:

• Unclear category positioning
  The company’s role in the market is not described consistently across its website or external sources.
• Weak topical depth
  The site lacks educational resources explaining the category or problem space.
• Inconsistent brand descriptions across the web
  Different sources describe the company in conflicting ways.
• Limited authoritative resources
  There are few credible references that AI systems can cite.

These weaknesses often explain why AI assistants overlook a brand even when it performs well in traditional search.

Diagnosing the AI visibility gap

AI assistants are becoming a new interface for research and discovery. When buyers ask questions about categories, tools, or solutions, the generated answer often shapes the shortlist of companies they consider.

An AEO audit helps companies understand where their visibility breaks down. It shows whether AI systems recognize the brand, whether they associate it with the right category, and whether they have reliable content to reference when answering questions.

Once those signals become visible, the path forward becomes clearer. Strengthening category clarity, expanding authoritative content, and improving structural signals all increase the chances that AI systems can interpret and recommend your brand.

As AI-generated answers play a larger role in how buyers research solutions, companies that understand these signals will have a meaningful advantage.

If you want to understand how your brand currently appears in AI answers, we can help. We analyze how models like ChatGPT, Claude, Gemini, and Perplexity interpret your company, your category, and your competitors, then translate those findings into clear actions that improve visibility.

Read more about AEO from the Edgar Allan Blog.

Get Answer Engine Ready

AEO For Sentiment Analysis: How AI Understands Your Brand

AEO & AI in Action The New Playbook for Website Growth

What AI Search Actually Rewards: Expertise, POV, and Saying Something Real

Content Strategy for AEO: Why Prompt Visibility Comes First

Machines Are Reading Your Website (And They’re Probably Getting Your Brand All Wrong)

Machines Are Reading Your Website (And They’re Probably Getting Your Brand All Wrong) Part 2