What is AEO? The complete guide to Answer Engine Optimisation

For over two decades, the playbook for online visibility was straightforward: optimise your website for Google, climb the rankings, and watch the traffic flow. That era isn't over, but it's no longer the whole story. A new category of search — powered by large language models — is fundamentally changing how people find information, compare products, and choose which brands to trust. The discipline emerging around this shift is called Answer Engine Optimisation, or AEO.

AEO is the practice of structuring your online presence so that AI-powered search engines — tools like Perplexity, ChatGPT, Google's AI Overviews, and Microsoft Copilot — accurately understand, reference, and recommend your brand when users ask questions in your domain. Unlike traditional SEO, where success means appearing as a blue link on a results page, AEO success means being woven directly into the answer itself.

The distinction matters more than it might seem. When someone asks Perplexity "What's the best project management tool for remote teams?" they don't get ten blue links. They get a synthesised answer that names specific brands, explains their strengths, and often provides a direct recommendation. If your product isn't mentioned in that answer, you're invisible — regardless of where you rank on Google. Early data suggests that AI-generated answers have dramatically lower click-through to source websites, meaning the citation within the answer is becoming the primary form of brand exposure.

So what determines whether an AI search engine cites your brand? The models draw from a broad range of signals: the quality and depth of your content, the presence of structured data markup, external mentions and reviews across authoritative sources, E-E-A-T signals (Experience, Expertise, Authoritativeness, Trustworthiness), and how well your content is formatted for extraction. AI models are particularly good at identifying content that directly answers specific questions, uses clear definitions, and provides structured comparisons.

The relationship between traditional SEO and AEO is complementary rather than competitive. Strong SEO foundations — quality content, technical health, authoritative backlinks — feed directly into AEO performance. But AEO adds new layers: ensuring your content is structured in ways that LLMs can parse, that your brand appears in the third-party sources these models draw from, and that your schema markup gives AI crawlers the context they need. Think of SEO as optimising for the index and AEO as optimising for the synthesis layer that sits on top of it.

Measuring AEO performance has been one of the biggest challenges for businesses. Unlike Google Search Console, there's no dashboard from Perplexity or ChatGPT telling you when your brand was mentioned. This is precisely the problem that Casa's AEO tool was built to solve — it systematically queries AI search engines with the questions your customers are asking and reports back on whether your brand appears, how prominently it's featured, and what your competitors' AI visibility looks like. It turns an opaque new channel into something you can actually monitor, measure, and improve.

The businesses that start investing in AEO now will have a significant first-mover advantage. AI search adoption is accelerating rapidly, and the brands that establish strong AI visibility today will be the ones these models learn to reference consistently. Waiting until AI search is the dominant paradigm means playing catch-up against competitors who've already built that presence. The fundamentals aren't complicated — they start with understanding where you stand today and making systematic improvements from there.