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AI SEO, covering Generative Engine Optimisation (GEO) and Answer Engine Optimisation (AEO), optimises content to be cited by AI systems like ChatGPT, Gemini, and Perplexity, not just ranked in Google's traditional blue-link results. Traditional SEO targets ranked positions; AI SEO targets the AI-generated answer itself. The underlying signals overlap (E-E-A-T, structured data, topical authority), but the content architecture, entity strategy, and schema requirements differ. As AI-generated answers capture an increasing share of search sessions, brands that appear in those answers capture demand that never reaches traditional search results.

AI citation is earned through authoritative content architecture, structured data, and entity recognition, not a shortcut. LLMs cite sources they've indexed as authoritative on a topic, which means building deep topical coverage, implementing FAQPage schema correctly, strengthening E-E-A-T signals (author credentials, external citations, first-party data), and structuring answers the way AI systems retrieve and synthesise information. Pages with FAQPage schema achieve a 41% citation rate in Google AI Overviews compared to 15% without — the same pattern holds across other generative platforms.

Yes, and the two reinforce each other. AI search systems draw on the same authority signals Google's algorithm uses: backlinks, E-E-A-T, site architecture, and content depth. Strong traditional SEO is the foundation AI visibility is built on. AI SEO adds a layer of content architecture and structured data specifically designed for how LLMs retrieve and surface information, as it extends traditional SEO rather than replacing it. Brands that treat GEO as a separate discipline from SEO typically underperform on both.

AI search visibility is tracked across three dimensions: brand citation frequency in Google AI Overviews, brand presence in ChatGPT, Gemini, Claude, and Perplexity responses for target queries (tested systematically against defined query sets), and entity recognition, or how AI systems describe and associate your brand with relevant topics. We baseline all three at the start of an engagement and report monthly. Traditional ranking metrics are tracked alongside AI visibility, and the two are reported together, not separately, with data analytics connecting AI search citations to pipeline and revenue.

Traditional ranking improvements typically appear within 60–90 days. Google AI Overview citation improvements follow a similar timeline, as structured data and content changes are reflected in AI answers within 4–8 weeks for most sites. Building consistent citation in ChatGPT and Perplexity for competitive queries takes longer: 3–6 months of sustained content and authority work. The compounding effect, where AI systems increasingly associate your brand with a topic, builds meaningfully over 6–12 months. For Prolink, a Singapore consumer electronics brand, this type of content authority build reached 100K monthly organic visitors within six months.

Yes, starting from zero is common and not a disadvantage. Most brands we engage have no intentional GEO or AEO strategy in place; the gap is typically in structured data, content architecture, and E-E-A-T signals rather than domain authority. We begin with an AI Search Intelligence Audit that diagnoses exactly where AI visibility is absent and what the highest-leverage fixes are. For brands with strong traditional SEO foundations, AI search improvements often come faster than expected once the architecture is properly aligned.

AI SEO engagements typically run alongside a standard SEO retainer rather than replacing it because the technical and content work is complementary. For brands with mature SEO foundations looking to add GEO/AEO capability, we scope AI SEO as a programme extension. For brands starting from scratch, we design an integrated engagement covering both. We recommend a minimum three-month runway for the foundational architecture work to index and begin generating citation signals.