AI Engine Optimization (AEO)

Definition

AI Engine Optimization (AEO) is the practice of optimizing content and online presence so that large language models (LLMs) mention, recommend, or cite your brand when users ask relevant questions through AI assistants like ChatGPT, Perplexity, or Claude.

In Depth

AEO emerged as a discipline in 2025-2026 as LLM-powered search tools captured significant user attention. Unlike traditional SEO, which optimizes for blue-link rankings, AEO targets the language model's generation step. LLMs form their responses from training data, retrieval-augmented generation (RAG) pipelines, and real-time search API calls. AEO practitioners work on all three: ensuring brand mentions appear in high-quality content that gets into training data, structuring content for easy RAG retrieval, and ranking for the search queries that LLMs generate internally when answering user questions. Measurement requires running the same prompt across multiple models repeatedly, because LLM responses are probabilistic. A single check tells you almost nothing; you need statistical sampling across models, prompt variations, and time to track visibility trends.

Example Usage

Platforms

AI Engine Optimization (AEO) is relevant across the following platforms, all accessible through Scavio's unified API:

• Google

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