"An AI engine optimization audit evaluates brand visibility, accuracy, and citations in AI-powered search engines. It highlights how a brand appears across ChatGPT, Gemini, Perplexity, and Bing Copilot, and identifies gaps in the facts, descriptions, and links these systems rely on. In contrast, a traditional SEO audit focuses on website rankings and technical health in classic search engines. AI search extracts information directly from content, public sources, and structured data."
"This shift changes how buyers discover brands and validate solutions. Growth-focused teams benefit from precise, consistent brand details in AI summaries, as these summaries influence early research, shortlists, and pipeline creation. This post gives teams a complete workflow for running an AI engine optimization audit, priority fixes, a practical checklist, and the HubSpot tools that support the process. Each section offers clear steps for testing visibility across AI engines, measuring accuracy, updating content, and publishing structured, AI-friendly pages at scale."
An AI engine optimization audit measures how AI-powered search engines represent a brand by evaluating visibility, factual accuracy, and citation quality across systems like ChatGPT, Gemini, Perplexity, and Bing Copilot. The audit identifies outdated facts, missing brand mentions, incorrect citations, and gaps caused by unstructured pages, unclear entities, and inconsistent context. AI search extracts information from page content, public sources, and structured data, changing buyer discovery and validation behaviors. Growth teams gain from consistent, precise brand details in AI summaries because those summaries influence early research, shortlists, and pipeline creation. The workflow includes testing visibility across engines, measuring accuracy, updating content, and publishing structured, AI-friendly pages at scale, with priority fixes and tools to support implementation.
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