Traditional SEO is built around getting ranked on Google's blue links. AI search optimisation -covering AEO and GEO - is built around getting cited, summarised, and recommended by AI systems like ChatGPT, Perplexity, and Google AI Overviews. The underlying principles overlap: authority, credibility, content depth. But the execution is different. AI models don't just rank pages - they interpret brands. Optimising for AI search means ensuring your brand is clearly defined as an entity, your content is structured for AI parsing, and your authority signals come from the sources LLMs actually trust.

An entity is how AI systems and knowledge graphs identify and categorise your brand -distinct from other brands, clearly associated with a category, and backed by credible signals across the web. When your brand entity is weak or ambiguous,AI models either ignore you or describe you inaccurately in generated answers. Entity optimisation involves clarifying your brand's positioning across structured data, third-party citations, author credentials, and content that consistently signals what you do and who you serve. It's the foundation of AI search visibility.

Timelines for AI search visibility are harder to predict than traditional SEO - and anyone who gives you a precise number should be questioned on it. Different platforms operate very differently: Perplexity uses real-time web data, ChatGPT's knowledge has training cutoffs and Google AI Overviews blend both. What we do know is that the underlying work - entity clarity, third-party citations, structured data, topical authority - compounds over time and creates durable visibility across all of them. The brands that are consistently cited in AI-generated answers today didn't get there through a campaign. They got there through sustained, systematic signal-building. That's what we build - and it's a medium to long-term investment, not a quick-win channel.