Definition
What is AEO (AI Engine Optimisation)?
AI Engine Optimisation (AEO) is the discipline of ensuring your brand is accurately represented, frequently mentioned, and favorably positioned in AI-generated responses across major answer engines. While SEO focuses on ranking in search engine results pages, AEO focuses on appearing in AI-synthesized answers.
The term needs disambiguation. Outside marketing, AEO often means Authorized Economic Operator in customs and trade. That ambiguity is why good AEO pages explain the marketing meaning immediately and pair it with related terms such as AI visibility, answer engines, citations, and comparison pages.
AEO encompasses three core pillars: Technical AEO (infrastructure for AI discovery), Content AEO (creating content that AI engines extract and cite), and Strategic AEO (competitive positioning and measurement). Each pillar addresses a different aspect of how AI engines discover, process, and present brand information.
The emergence of AEO reflects a fundamental shift in how consumers discover products and services. When a user asks ChatGPT "what is the best project management tool for remote teams," the AI engine synthesizes an answer from its training data and real-time search. There is no results page to rank on. The brands that appear in this response have optimized for AEO, whether intentionally or not.
AEO differs from SEO in several key ways: it requires multi-engine optimization, the "ranking" is binary (mentioned or not) rather than positional, content quality matters more than keyword density, and supporting assets such as glossary entries, comparison pages, and AI-readable files become more important than most teams expect.
Why it matters
As AI engines capture an increasing share of product research and discovery, brands that ignore AEO become invisible to a growing segment of potential customers. AEO is not a replacement for SEO but an essential complement. Brands need both traditional search visibility and answer-engine visibility to maintain a complete digital presence.
Real-world examples
- 1
Implementing llms.txt and structured data to improve AI engine comprehension of a brand
- 2
Running a monthly Share of Model report across 8 AI engines to track competitive position
- 3
Restructuring website content with answer-first formatting for better AI citation rates
Frequently asked questions about AEO (AI Engine Optimisation)
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Explore related concepts
Technical AEO
technicalTechnical AEO encompasses the infrastructure and technical configurations that help AI engines discover, crawl, parse, and cite your content. It includes AI-specific crawl policies, structured data implementation, llms.txt files, site architecture optimisation, and content formatting for AI consumption.
AI Visibility
strategyAI Visibility refers to the extent to which a brand is present, accurately represented, and favourably positioned across AI engine responses. It is the aggregate measure of how discoverable your brand is when users ask AI engines questions relevant to your products or services.
Share of Model
metricShare of Model (SoM) measures how frequently a brand is mentioned or recommended by AI engines in response to relevant queries. It is the AI-era equivalent of Share of Voice, quantifying your brand's presence across ChatGPT, Perplexity, Gemini, Claude, and other answer engines.
AI Search Optimization
strategyAI Search Optimization is the broad practice of optimising digital content and brand presence to perform well across all AI-powered search interfaces, including conversational AI (ChatGPT, Claude), AI-native search (Perplexity), and AI-enhanced traditional search (AI Overviews, AI Mode).
Start with the pages and proof that AI can actually use
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