AEO (Answer Engine Optimisation) targets citation in search engine AI features like Google AI Overviews and Bing Copilot. GEO (Generative Engine Optimisation) targets citation in standalone AI chatbots like ChatGPT, Perplexity, and Claude. Both disciplines share the same core content principles: answer-first writing, named source attribution, and strong E-E-A-T signals. The difference is where and how AI systems retrieve your content. Start with What is AEO? for the foundational context.
What AEO and GEO Share and Where They Differ
Both disciplines have overlapping foundations and platform-specific tactics. Understanding the boundary helps you allocate optimisation effort to the right surface.
AEO vs GEO: Overlap and Differences
Click each zone to explore what each discipline covers exclusively and what they share.
Detailed Comparison: AEO vs GEO
A direct comparison of both disciplines across the seven dimensions that matter most for strategy planning and resource allocation.
AEO vs GEO: Side-by-Side Comparison
| Dimension | AEO | GEO |
|---|---|---|
| Primary target | Google AI Overviews, Bing Copilot | ChatGPT, Perplexity, Claude, Gemini |
| Citation mechanism | Passage retrieval from indexed web pages | LLM training data, RAG pipelines, plugins |
| Organic ranking required | Yes - top 12 for Google AI Overviews | No - LLMs can cite non-indexed pages if referenced elsewhere |
| Schema importance | High (FAQ, HowTo, Article) | Low to moderate - LLMs do not read schema at inference |
| Freshness impact | Moderate - indexed content updated regularly | Limited by training cutoff; RAG varies by provider |
| Measurement | AI citation rate in Google Search Console + manual tracking | Brand mention rate in LLM responses (prompt-based auditing) |
| Key shared tactic | Answer-first writing and E-E-A-T | Answer-first writing and E-E-A-T |