AI Search Optimisation: The Complete Guide for UK Businesses
The way people find businesses online is changing. Alongside traditional Google searches, a growing number of consumers now ask AI assistants — ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews — for recommendations, comparisons, and advice. For UK businesses, this shift creates both an urgent challenge and a significant opportunity.
AI search optimisation is the practice of improving your content and online presence so that these AI-powered platforms are more likely to reference and recommend your brand. Unlike traditional SEO, where success means ranking on a results page, AI search optimisation is about earning a place inside the answer itself.
This guide covers everything UK businesses need to know: how AI search works, what each platform does differently, and the practical steps you can take to improve your visibility.
What Is AI Search Optimisation?
AI search optimisation is the process of structuring your content, building your authority, and managing your online reputation so that AI-powered search tools recommend your brand when users ask relevant questions.
When someone asks an AI assistant "What's the best accounting software for UK freelancers?" the AI generates a synthesised answer, often mentioning several brands by name. Unlike a Google results page, where ten links compete for attention, an AI answer typically references just two to five brands. Being one of those brands — or being absent entirely — has a direct impact on your visibility and revenue.
AI search optimisation encompasses several interconnected disciplines:
- Content optimisation: Structuring your content so AI systems can easily extract and reference it
- Authority building: Establishing your brand as a credible, expert source across the web
- Entity management: Ensuring AI systems accurately understand what your brand is and what it offers
- Reputation management: Influencing how AI platforms perceive and describe your brand
- Citation earning: Getting your content cited as a source in AI-generated answers
The Shift from Traditional Search to AI-Powered Answers
Traditional search engines present users with a list of links and let them decide which to click. AI-powered search fundamentally changes this dynamic by providing a direct answer. This matters for several reasons:
Fewer brands get visibility. A Google results page shows ten organic links, plus ads, local results, and featured snippets. An AI answer typically mentions two to five brands. The competition for visibility is far more intense.
The user may never visit your website. When an AI assistant provides a comprehensive answer, many users have no reason to click through to a source. Your brand's mention in the AI answer may be the only touchpoint.
AI answers carry implicit endorsement. When an AI assistant recommends your brand, it carries a level of implied authority. Users tend to trust AI recommendations in a way they do not trust a list of search results, because the AI has ostensibly evaluated options on their behalf.
The playing field is different. Brands that dominate traditional search through large advertising budgets or extensive backlink profiles do not automatically dominate AI search. Smaller businesses with strong authority in their niche can outperform larger competitors in AI recommendations.
How Each AI Platform Works Differently
One of the most important aspects of AI search optimisation is understanding that each platform operates differently. A strategy that works for one may not work for another.
ChatGPT (OpenAI)
ChatGPT uses a combination of its training data and real-time web browsing (when enabled) to generate answers. For recommendation queries, it draws heavily on:
- Its training data, which includes web content up to its knowledge cutoff
- Real-time web searches when browsing is active
- The overall consensus across authoritative sources
ChatGPT tends to favour brands with strong, consistent mentions across multiple high-authority sources. It is particularly influenced by review sites, industry publications, and well-structured product pages.
Claude (Anthropic)
Claude draws on its training data and, in certain configurations, web search results. Claude places a strong emphasis on nuance and accuracy, and tends to provide balanced recommendations rather than single definitive answers. Brands that appear in well-reasoned, balanced content — such as detailed comparison articles and expert analyses — tend to be referenced more frequently.
Perplexity
Perplexity operates primarily as a search tool, conducting real-time web searches for every query and synthesising the results with citations. This makes it the most search-dependent of the AI platforms. Content that ranks well in traditional search and provides clear, citable information tends to perform well in Perplexity. Perplexity also provides visible source citations, making it easier to track whether your content is being referenced.
Gemini (Google)
Gemini draws on Google's vast search index and knowledge graph. It benefits from many of the same signals as traditional Google search — domain authority, content quality, E-E-A-T signals — but synthesises information into conversational answers rather than ranked links. Brands with strong Google Search Console performance often find Gemini visibility follows naturally.
Google AI Overviews
Google AI Overviews appear directly within search results, pulling from indexed web content to generate summaries. They heavily favour content that already ranks in the top organic positions. For a deeper look at this specific platform, see our AI Overview Optimisation guide.
The Role of E-E-A-T in AI Recommendations
Google's E-E-A-T framework — Experience, Expertise, Authoritativeness, and Trustworthiness — has become the de facto standard for content quality across all AI platforms, not just Google.
AI models are trained on vast amounts of web content, and they learn to recognise the markers of authoritative, trustworthy information. Content that demonstrates genuine expertise, is published on authoritative domains, and is written by credible authors is more likely to be referenced in AI-generated answers.
Experience
AI platforms increasingly value first-hand experience. Content that shares real case studies, practical examples, and hands-on insights is favoured over generic, theoretical content. If you are writing about a topic, demonstrate that you have direct experience with it.
Expertise
Establish your credentials clearly. Author bylines with relevant qualifications, "About" pages that detail your team's expertise, and content that demonstrates deep knowledge of your subject all contribute to your perceived expertise.
Authoritativeness
Your overall domain authority matters. Being referenced by other authoritative sources, maintaining a strong backlink profile, and having a consistent presence across respected industry platforms all signal authoritativeness to AI systems.
Trustworthiness
Accuracy, transparency, and reliability build trust. Cite your sources, keep your content updated, maintain clear editorial standards, and ensure your website is technically sound and secure.
Step-by-Step: Optimising Your Content for AI
Step 1: Identify your target queries
Start by listing the questions your ideal customers ask when researching products or services like yours. Focus on:
- Recommendation queries: "What's the best [product/service] for [audience]?"
- Comparison queries: "Which [product] is better for [use case]?"
- How-to queries: "How do I [solve a problem your product addresses]?"
- Research queries: "What should I look for in a [product/service category]?"
Step 2: Audit your current AI visibility
Query each major AI platform with your target questions. Document:
- Whether your brand is mentioned
- How your brand is described (positively, neutrally, negatively)
- Which competitors are mentioned instead
- What sources the AI cites
This baseline tells you exactly where to focus your efforts.
Step 3: Create authoritative, well-structured content
For each target query, ensure you have content on your site that:
- Directly addresses the question in a clear, authoritative manner
- Uses headings that mirror natural query language
- Includes specific data, examples, and practical advice
- Is structured with clear hierarchies (H2, H3, lists, tables)
- Includes relevant schema markup
Step 4: Build external authority
Your on-site content alone is not enough. AI platforms weigh your brand's presence across the entire web. Invest in:
- PR and media coverage: Earn mentions in respected publications relevant to your industry
- Review platforms: Actively manage your presence on review sites, encouraging genuine reviews from satisfied customers
- Industry directories: Ensure you are listed in relevant professional and industry directories
- Guest contributions: Publish expert content on authoritative third-party sites
- Community presence: Participate meaningfully in forums, communities, and platforms where your audience gathers
Step 5: Maintain consistency across all platforms
Ensure your brand name, description, and key claims are consistent everywhere. Inconsistent information confuses AI models and reduces their confidence in recommending you. Audit your listings across social media, directories, review sites, and partner websites.
Step 6: Earn citations through original value
Publish content that gives AI platforms a reason to cite you specifically:
- Original research and survey data
- Proprietary benchmarks and industry reports
- Unique frameworks, methodologies, or tools
- Expert commentary on industry developments
Content that cannot be found elsewhere is the most reliable path to consistent AI citations.
Measuring Results: What Metrics Matter
Traditional SEO metrics do not capture AI search performance. The metrics that matter for AI search optimisation are:
- Mention rate: The percentage of relevant queries where your brand is mentioned by each AI platform
- Citation rate: How often your content is cited as a source in AI answers
- Share of voice: Your brand mentions relative to competitors for target queries
- Sentiment: Whether AI platforms describe your brand positively or negatively
- Platform coverage: Which of the five major AI platforms mention your brand, and which do not
- Recommendation position: Whether you are mentioned first, second, or further down in AI answers
Tracking these metrics manually is impractical across five platforms and dozens of queries. Track your AI search visibility with RivalScope, which monitors all five major AI platforms and provides the data you need to measure and improve your performance.
Common Mistakes to Avoid
Treating AI search the same as traditional SEO
AI search optimisation requires different tactics. Keyword stuffing, link schemes, and thin content that might still generate some traditional search traffic will not help you in AI answers.
Ignoring platforms beyond Google
Google AI Overviews are important, but ChatGPT, Claude, Perplexity, and Gemini each represent growing audiences. An effective strategy covers all five platforms.
Focusing only on your own website
AI platforms draw from the entire web. Your visibility depends as much on what others say about you as on what you say about yourself. External authority building is essential.
Neglecting brand consistency
Inconsistent brand information across the web confuses AI models. If your website says one thing and your directory listings say another, AI platforms lose confidence in recommending you.
Not measuring results
Without tracking your AI visibility, you are optimising blind. Regular measurement is the only way to know whether your efforts are working and where to adjust your strategy.
Getting Started
AI search optimisation is not a single project — it is an ongoing discipline that sits alongside your existing SEO and marketing efforts. Start with a clear baseline of your current AI visibility, prioritise the platforms and queries most important to your business, and systematically build the authority, content quality, and consistency that AI platforms reward.
The businesses that invest in AI search optimisation now will have a significant advantage as AI-powered discovery continues to grow. The ones that wait risk becoming invisible to an increasingly important audience.