$ ~/ym8 --define aeo
AEO (AI Engine Optimisation)
definition
AI Engine Optimisation (AEO) is the discipline of ensuring your brand is accurately represented, frequently mentioned, and favourably positioned in AI-generated responses across all major answer engines. While SEO focuses on ranking in search engine results pages, AEO focuses on appearing in AI-synthesised answers.
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 synthesises 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 optimised for AEO, whether intentionally or not.
AEO differs from SEO in several key ways: it requires multi-engine optimisation (not just Google), the "ranking" is binary (mentioned or not) rather than positional, content quality matters more than keyword density, and structured AI-readable files (llms.txt, llm-profile.json) become as important as traditional on-page SEO elements.
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 AI engine visibility to maintain a complete digital presence.
examples
- Implementing llms.txt and structured data to improve AI engine comprehension of a brand
- Running a monthly Share of Model report across 8 AI engines to track competitive position
- Restructuring website content with answer-first formatting for better AI citation rates
faq
Is AEO replacing SEO?
No, AEO complements SEO rather than replacing it. Traditional SEO remains important for search engine visibility, while AEO adds the layer of AI engine visibility. Many AEO tactics (structured data, quality content, authority building) also benefit SEO, making the two disciplines synergistic.
When should a brand start investing in AEO?
Now. AI engines are already influencing purchase decisions, and early movers in AEO will establish visibility advantages that are difficult for latecomers to overcome. The foundational elements of AEO (llms.txt, AI crawler access, structured data) can be implemented quickly with minimal cost.
Related Terms
Technical AEO
Technical 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
AI 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
Share 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
AI 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).
Related Engines
Monitor Your AI Visibility
See how your brand appears with the default core pair. Start with ChatGPT and Claude by default. Expand monitoring only when the workflow needs it.