LLM optimisation is the practice of structuring content so that large language models such as ChatGPT, Gemini, Claude and Perplexity retrieve and cite it when answering user questions. AEO (Answer Engine Optimisation) is the practice of formatting content to win direct answers in search engines and AI assistants, including featured snippets, voice search and AI Overviews. AI optimisation is the broadest umbrella term, containing both LLM optimisation and AEO as subsets.
LLM optimisation, AEO and AI optimisation are related but distinct practices, and confusing them leads to wasted effort. LLM optimisation is specifically about being cited by large language models; AEO is about winning structured answer formats in search; AI optimisation is the umbrella term that contains both. As of 2026, understanding the difference is no longer optional for any business serious about organic visibility.
Here is how each term breaks down in plain English:
- LLM optimisation: structuring content so ChatGPT, Gemini, Claude and Perplexity retrieve and quote it when answering questions.
- AEO (Answer Engine Optimisation): formatting content to win featured snippets, voice search results and AI Overviews; the term predates the current LLM wave.
- AI optimisation: the broadest term, covering any strategy that improves how AI systems interact with or surface your content.
- GEO (Generative Engine Optimisation): an academic term closely related to LLM optimisation and often used interchangeably with it.
- The hierarchy: AI optimisation sits at the top; LLM optimisation and AEO are specific subsets beneath it.
The practical difference matters because each approach targets a different surface. AEO has historically focused on Google's position-zero results and voice assistants, using Q&A formatting and schema markup. LLM optimisation goes further, prioritising entity clarity, citability and structured prose that language models can extract and attribute accurately. Google's AI Overviews, which appeared in an estimated 15 to 20 per cent of searches in live markets according to industry research from BrightEdge and Semrush, sit at the intersection of both disciplines.
Web SEM, a results-driven SEO company in Cape Town, applies all three frameworks as part of a unified, data-driven strategy. Winning citations from AI systems in 2026 requires more than keyword placement; it requires content that is unambiguous, authoritative and structured for extraction. If your content is not being surfaced by LLMs or earning AI Overview placements, the gap is almost always in how the content is written and marked up, not how much of it exists.