Ask ChatGPT, Gemini, or Perplexity to explain your business. Not your website. Your business.
The responses can be surprisingly good. They often identify what a company does, who it serves, where it operates, and what differentiates it from competitors, drawing on websites, reviews, press mentions, social profiles, and other public information.
They’re also revealing. Sometimes AI can explain a business exactly as the owner would. Other times, it produces a generic description that could apply to dozens of competitors. It may understand what a company does but struggle to explain why someone should choose it, or identify expertise without enough evidence to support it.
If AI systems are developing an understanding of organizations, how do we know what they actually understand about ours?
Auditing how AI understands your business
While patents don’t tell us exactly how Google Search works, they can provide valuable insight into the kinds of problems Google is trying to solve.
Google’s “Data extraction using LLMs” patent explores how SEO is evolving from helping search engines understand webpages to helping AI systems understand entities. One idea described in the patent was the ability to synthesize a “deep, holistic characterization” of an entity using information gathered from websites and other public sources.
Whether that patent is used in production isn’t the point. AI-powered search experiences are already moving beyond document retrieval. They’re:
- Summarizing organizations.
- Comparing products.
- Recommending businesses.
- Answering questions that require a broader understanding than any single webpage can provide.
Before an AI system can recommend a plumber, explain a software platform, compare two law firms, or suggest a translation service, it first needs to develop an understanding of the organizations involved.
That raises a practical challenge for you.
Historically, we’ve audited the assets that contribute to search visibility. We audit technical SEO, content, backlinks, structured data, Google Business Profiles, citations, and reviews. Each of those audits tells us something important about a specific aspect of search performance. What they don’t tell us is whether those assets collectively create a clear, consistent, and evidence-backed understanding of the business itself.
That’s the next layer to audit. I’ve been experimenting with a framework I’m calling an AI entity footprint audit. Instead of evaluating individual marketing assets in isolation, you evaluate the collective understanding they create. Rather than auditing rankings or technical SEO, it attempts to answer a different question:
- If an AI system had to explain this business to a prospective customer today, how confidently could it do it?
The rest of this article explores the thinking behind that framework, the questions you should begin asking, and how you can perform your own AI…
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