The way customers find suppliers is changing. More product and service questions now begin in ChatGPT, and Google increasingly answers queries through AI Overviews above its traditional results. For business owners, the question is no longer simply whether you appear on page one. It is whether an AI tool names your business when a prospect asks for the kind of work you do.
AI search optimisation is the response to that shift. This article explains what it involves, what Google recommends, and the practical steps that make your brand more visible inside AI assistants.
AI search optimisation is the ongoing process of making your site more easily found, read and trusted by AI tools and search agents. The goal is straightforward: when a customer asks an AI assistant for a product, service or supplier, your brand is the one recommended, discovered and chosen. In a competitive market, that visibility carries real commercial weight.
There is one important reason why this matters more than ordinary rankings. AI assistants answer questions directly and often reference a source without linking to it. If the AI names your business, you earn the enquiry. If it names a competitor, the customer may never see your website at all.
Tools such as ChatGPT, Bing’s AI search and Google’s Search Generative Experience have transformed how people discover information online. They focus on answering questions directly rather than presenting a list of links, which changes what you are actually optimising for. Traditional SEO seeks a better position in a ranked list of results. AI search optimisation seeks to influence the answer itself, so the model draws on your content and recommends your brand.
There is another shift underneath that. Traditional keyword tracking becomes less relevant when there is no stable set of results to rank in. A strategy built entirely around individual keyword positions will not tell you whether ChatGPT recommends your business to a buyer.
Google has published its own guidance on optimising for the generative AI features in Search. Its advice is deliberately straightforward: the fundamentals of good SEO still apply. Google identifies four core principles for site owners:
Notice what is missing from that list. Google does not suggest trying to manipulate its AI features. Its models draw on the same index that powers ordinary search, so content that is crawlable, useful and well presented is the content best placed to appear in AI-generated summaries. The technical SEO advice in Google’s guide serves the same goal it always has: helping Google understand, trust and display your content.
When you optimise content for AI-driven search, you move beyond traditional keyword targeting and think about topics and intent. An AI model does not match a list of search terms. It interprets what the user wants and assembles an answer from content it considers relevant.
For most businesses that means publishing depth instead of chasing volume. Write the page a customer would find genuinely helpful, cover the practical questions that surround a buying decision, and the AI has several angles from which to cite you. Content built around intent earns far more AI visibility than thin pages written purely for keywords.
AI search tools rely heavily on page structure to judge relevance. Headers, tables and other structural elements help the model understand what a page is about and how its sections fit together. A page of continuous text gives an AI little to work with, while a page with clear headings, logical sections and comparison tables is far easier to interpret and cite.
This is where AI search optimisation combines technical SEO, structured content and credibility signals. Technical factors let the AI access your content. Structure lets it understand your content. Credibility lets it trust your content. All three work together to determine whether a model names your brand or someone else’s.
Credibility signals influence how AI interprets and cites your brand. When an assistant decides which business to recommend, it weighs the source as well as the facts. Information that is accurate, current and supported elsewhere on the web is much easier for a model to defend within an answer.
There is no shortcut here. Publish dated, accurate information. Keep the way your business is described consistent across your site and the wider web. Answer the questions customers genuinely ask. Over time, the collective picture of your brand becomes one an AI is comfortable recommending to a buyer.
Because AI-driven search results are less about fixed rankings, AI search optimisation needs new metrics to gauge success. Checking where a page sits for a keyword will tell you very little about whether ChatGPT mentions your brand inside its written answer.
Instead, run regular manual checks. Ask the AI tool the questions your customers ask and note which brands it names. Review which of your pages appear in Google AI Overviews for relevant queries. Track the enquiries that arrive without a traditional click path. The metric that ultimately matters is unchanged: how often AI answers send real customers your way.
The day-to-day work of AI search optimisation can be summarised in a short checklist:
Work through those items and you cover the core of AI search optimisation. None of them requires chasing an algorithm update. They ask you to do the fundamentals well, then keep an eye on how AI models use what you publish.
At Wicked Spider, we are an SEO and web design agency based in Greenock, working with established businesses across Scotland and the UK, many of them in construction and engineering supply chains. When we plan local SEO and content for clients, AI visibility is now part of the conversation from day one.
AI search optimisation is not a separate silo. It is the latest and most visible expression of the same goal we have always pursued: making sure that when a buyer asks who does what you do, your name is the answer they receive.
AI search optimisation is the ongoing process of making your website easier for AI tools and search agents to find, read and trust. The goal is to be the brand an AI assistant recommends when a customer asks about a product or service. It combines technical SEO, structured content and credibility signals to influence how AI interprets and cites your business.
Traditional SEO optimises for a position in a ranked list of search results. AI tools such as ChatGPT, Google AI Overviews and Bing’s AI search answer questions directly, and they may reference content without linking to it. AI search optimisation therefore focuses on topics and intent rather than individual keywords, and it demands credibility signals strong enough for the AI to cite your brand.
Keywords have not disappeared, but they are no longer the starting point. When optimising content for AI-driven search, you move beyond keyword targeting and think about topics and intent. Understanding the phrases customers use still helps you identify their real questions. The difference is that you now write to answer the whole topic, not to rank one page for one term.
Traditional keyword tracking becomes less relevant when there is no fixed set of results to monitor. Run regular manual checks instead. Ask ChatGPT the questions your customers would ask and note which brands it names. Review Google AI Overviews for the same queries and track whether you appear, disappear or get recommended alongside competitors over time.
