Start here: what AI search does with a business

A search engine ranks pages. An answer engine picks one business, or a short list, and states it as the answer. That difference is the starting point for AI visibility. Every guide gathered here works from it, rather than from a platform-versus-platform question or an industry playbook alone. Before deciding which comparison matters, or which industry move to make first, a business needs the foundation underneath both. That foundation is what Answer Engine Optimisation is, how an engine decides what to trust, and where the old SEO rules still hold.

Answer Engine Optimisation is not SEO with a new acronym stapled on. SEO earns a ranking position. AEO earns the sentence an AI model reads back to a user, and that can happen with or without a page ranking well in Google first. Google has published its own guidance on optimising for its AI, and it is worth reading directly rather than through a rewritten checklist. llms.txt gets debated as though it were a magic switch, when the actual evidence for it is thinner than the hype around it. The six guides in the first group below work through these definitions one at a time. They cover what AEO means, what Google itself says, and whether SEO is dead. The rest cover what zero-click search changes for a small business's leads, whether AI search only names big brands, and what llms.txt does.

Once the definitions are settled, the harder question is mechanical: what happens between someone typing a question and an AI engine naming a business. Google's own documentation describes query fan-out, where one question becomes a dozen smaller searches before an answer gets built. ChatGPT only browses the live web on a fraction of its answers, and that browsing is weighted heavily toward the first question in a conversation. A location survives that rewrite almost every time, even when everything else about the question gets stripped down. Perplexity, Gemini and Grok each read from different source pools, which is why the same business can appear in one and vanish from another. That whole pipeline is traced end to end across six guides in this second group. The set closes with a direct 20-query audit of where two major engines agree, and where their sourcing genuinely diverges.

Understanding the mechanics only matters once it turns into a first move. The third group holds six playbooks. One covers becoming an entity an AI model recognises by name. One is a 90-day plan for a brand-new business with no reviews yet. Two walk through the workflow behind getting mentioned by ChatGPT and getting cited by Perplexity. One works from Google's own AI Overviews checklist. The last covers what to do when an AI answer about a business already exists, and gets it wrong. Each one assumes zero prior AI-visibility work and ends at a concrete task, not a general principle.

Three fields already let an AI recommendation decide who gets called first, and the remaining nineteen guides apply that same foundation to each. The eleven dental guides are built to a UK, GDC-safe frame, with one exception: how-ai-overviews-rank-dental-practices-2026 carries no UK or NHS reference and uses US spelling throughout. The set explains why a strong Google ranking does not guarantee a ChatGPT mention, and how AI Overviews pick a dentist. It also covers what makes a schema markup or an FAQ page worth an AI model quoting it. The six trades guides cover roofers, plumbers and HVAC companies answering the same urgent, largely unplanned searches. They work through what a homeowner asks before hiring, and why AI search treats storm damage as a different job from a routine repair. Two guides close the set for regulated professional services. One is a Florida law firm ranking guide covering GEO, AEO and AI SEO together. The other is an accountants' guide to the questions a business owner puts to AI before choosing who to hire.

None of these 37 guides assumes prior familiarity with the acronyms. Each stands on its own.