AI Search and Your Business: How Bing Copilot, ChatGPT, and Google AI Overview Use Your Website

AI search tools are changing the commercial relationship between businesses and search engines. Instead of presenting a list of ten links, these tools generate a written answer — drawing from multiple websites, synthesising the information, and presenting it as if it were their own. When your business is cited in that answer, it carries a credibility that a standard search listing cannot match.

The key tools to understand are Google AI Overview, Microsoft Copilot (powered by Bing), ChatGPT, and Perplexity. Each draws from web content differently, but all of them share one characteristic: they cite sources they consider authoritative, well-structured, and factually reliable. Businesses that meet those criteria get cited. Businesses that do not are invisible in AI-generated answers.

This has real commercial consequences. A user who asks Copilot "which accountant should I use in Leeds?" and receives a specific recommendation with your business name in the answer is far closer to becoming a customer than someone who sees you in position eight on a standard search results page.

For the full context on Bing's role in AI search and how it connects to your alternative search strategy, see the Bing Places and alternative search hub.

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How AI Search Tools Source Their Answers

Understanding how these tools work helps you understand what to optimise.

Large language models (LLMs) — the technology behind ChatGPT, Copilot, and Google's AI systems — are trained on vast amounts of text. But for search applications, they also browse the live web or draw from an indexed database. When a user asks a question, the system retrieves relevant content from multiple sources, synthesises it, and generates a response.

The key decision is which sources to draw from. That decision is shaped by:

• Traditional search rankings — content that already ranks well in Google or Bing is more likely to be retrieved and cited
• Structured data — machine-readable markup that gives AI systems explicit, reliable information about your business and content
• Content clarity — text that is specific, factual, and well-organised is easier for AI systems to parse accurately
• Authority signals — indicators that your business and website are credible: author credentials, citations, consistent business information, reviews

AI systems are not making qualitative judgements the way a human editor would. They are pattern-matching against signals of reliability and relevance. Understanding those signals is the starting point for AI search optimisation.

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The Major AI Search Platforms

Platform	Powered By	How It Sources Content
Google AI Overview	Google index	Live web retrieval from Google's index
Microsoft Copilot	Bing index	Live web retrieval from Bing's index
ChatGPT (Browse)	Bing + web crawl	Bing index plus direct web browsing
Perplexity	Own index + Bing	Web retrieval with direct citations
Apple Intelligence	Google + Siri	Primarily Google index

Two observations stand out from this table.

First, Bing's index powers multiple AI tools simultaneously — Copilot, ChatGPT's browse mode, and Perplexity all draw from Bing. This means being well-indexed on Bing has a multiplier effect that simply claiming a Bing Places listing does not fully capture. Your entire website needs to be Bing-indexable and Bing-credible.

Second, Google AI Overview draws from Google's index, which you are likely already working to influence through your standard SEO activity. AI Overview optimisation is less about doing something new and more about ensuring your existing content meets a higher standard of structure and clarity.

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What the Shift from Links to Summaries Means for Traffic

The honest commercial reality of AI search is that it is reducing click-through rates for informational queries. If a user asks "what is the best email marketing platform for a small business?" and Google AI Overview provides a complete answer with four recommendations, many users will get what they need without clicking through to any website.

This is disruptive for businesses that depend on informational content to attract and convert visitors. However, the picture is more nuanced for transactional queries — searches where the user intends to buy, book, or hire.

When a user searches "accountant in Bristol taking new clients" or "commercial cleaning quote Manchester", they need to take an action. AI search tools cannot book an appointment or provide a tailored quote. They can suggest businesses, but the user still needs to click through and convert. For these queries, appearing in AI-generated suggestions is a first step, not a complete answer.

The implication: optimise your informational content to be citable in AI answers (increasing brand authority), while optimising your transactional pages to remain visible in traditional search results (driving direct conversions). These are complementary, not competing, goals.

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Structured Data: The Most Direct Lever You Have

Structured data is the single most actionable step you can take to improve your AI search visibility. It gives AI systems machine-readable, unambiguous information about your business and content — information they can use directly in generated answers without having to interpret your natural language copy.

The most relevant schema types for AI search citability are:

Organisation schema — confirms your business identity: name, address, phone number, website, social profiles, description, founding date. This is the foundation. AI systems use Organisation schema to verify that a website represents a legitimate, identifiable business. See Organisation schema markup for implementation guidance.

FAQ schema — provides question-and-answer pairs in a structured format that AI systems can extract directly. A well-implemented FAQ schema is, in effect, pre-formatted content for AI-generated answers. See FAQ schema markup guide for how to implement this.

Article schema — marks up blog posts and guides with author information, publication date, and topic. AI systems use this to assess content recency and authority.

LocalBusiness schema — combines location, hours, services, and reviews into a structured profile relevant for local queries. Particularly important for businesses serving a specific geographic area.

Product and Service schema — provides structured information about what you offer, including pricing where relevant. AI systems can surface this directly when users ask service-comparison questions.

For a full introduction to structured data and how to implement it without technical knowledge, structured data for business websites covers the essentials. Schema markup for small businesses goes into practical implementation detail.

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E-E-A-T: The Authority Framework AI Systems Respond To

Google introduced the E-E-A-T framework — Experience, Expertise, Authoritativeness, Trustworthiness — as a way of assessing content quality. AI systems, which draw heavily from Google's and Bing's evaluations of content, effectively use E-E-A-T signals to determine which sources are worth citing.

Experience — does the content demonstrate first-hand knowledge? Author bios that reference real credentials, case studies from actual clients, and specific examples all signal genuine experience.

Expertise — is the author credible on the subject? Professional qualifications, industry credentials, and consistent publishing on a topic build expertise signals over time.

Authoritativeness — does the wider web treat this source as authoritative? Backlinks from reputable sites, citations in other articles, and reviews from verified customers all contribute.

Trustworthiness — is the information accurate, sourced, and transparent? Clear authorship, accurate contact information, consistent NAP data, and a professional website all signal trustworthiness.

Improving your E-E-A-T is not a quick fix — it is built over months through consistent content, genuine credentials, and a credible web presence. But it is the underlying framework that determines whether AI systems consider your content worth referencing.

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Practical Steps to Improve AI Search Visibility

1. Implement structured data across your website. Start with Organisation schema on your homepage, Article schema on blog posts, FAQ schema on any page with questions and answers, and LocalBusiness schema if you serve a geographic area. Validate your implementation using Google's Rich Results Test.

2. Add FAQ sections to your key pages. Write questions the way your customers actually phrase them. Answer each question in two to four sentences — specific, factual, and complete. This format is directly parseable by AI systems.

3. Write clear, definitional introductions to every page. AI systems extract definitions and explanations. Pages that begin with a crisp one-to-two sentence definition of their topic are more likely to be cited than pages that open with vague marketing copy.

4. Ensure your business information is consistent everywhere. Your name, address, phone number, and website should be identical on your website, Google Business Profile, Bing Places, and any other directory. AI systems cross-reference these signals to verify business identity.

5. Build author credentials into your content. Add author bios to blog posts and guides. Include relevant professional credentials. Link to the author's other published work. AI systems use authorship signals to assess content authority.

6. Earn backlinks from credible sources. Coverage in industry publications, local press, and reputable directories increases the authority signals that AI systems respond to. This is a slower process, but it compounds.

7. Keep content current. AI systems deprioritise outdated content. Articles with recent publication or modification dates, and content that references current events or data, are more likely to be retrieved and cited.

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What Not to Do

A few practices that are counterproductive for AI search visibility:

• Do not keyword-stuff. AI systems are trained to identify and avoid spammy content. Dense keyword repetition signals low quality.
• Do not use generic, non-specific content. AI systems are looking for specific, citable facts — not vague value propositions.
• Do not block AI crawlers carelessly. Some businesses have updated their robots.txt to block AI crawlers. This prevents citation in AI-generated answers. Only block AI crawlers if you have a specific commercial reason to do so.
• Do not neglect traditional SEO. AI systems are more likely to cite sources that already rank well in traditional search. Your Google and Bing visibility is the foundation; AI search citability is built on top of it.

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Frequently Asked Questions

What is AI search? AI search refers to search experiences where an AI generates a direct answer rather than showing a list of links. Google AI Overview summarises answers at the top of search results. Microsoft Copilot generates conversational answers powered by Bing. ChatGPT and Perplexity browse the web and synthesise responses. All of these systems draw from website content and structured data.

How do AI search tools decide which websites to cite? AI systems favour content that is clearly structured, factually accurate, well-sourced, and marked up with structured data. Content with clear definitions, FAQ schema, Organisation schema, and authoritative E-E-A-T signals is more likely to be parsed, understood, and cited. Being well-ranked in traditional search also increases citation likelihood.

Will AI search replace traditional Google results? Not entirely — at least not in the near term. AI-generated answers appear alongside traditional results. For transactional queries (buying products, hiring services), users still click through to websites. AI search is most disruptive for informational queries where a direct answer satisfies the user. Businesses should optimise for both.

How do I optimise my website for AI search? Focus on structured data (Organisation, Product, FAQ, Article schema), clear and factual content with explicit definitions, consistent NAP information across the web, and strong E-E-A-T signals (author bios, credentials, citations). Content that directly answers questions in a structured format is easiest for AI systems to parse and cite.

Does structured data help with AI search? Yes. Structured data gives AI systems machine-readable information about your business, products, and content. FAQ schema provides ready-made question-answer pairs. Organisation schema confirms your business identity. Product schema provides pricing and availability. AI systems use this structured data to generate accurate, attributed answers.

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If you want a professional assessment of how your website performs for AI search — including structured data implementation, E-E-A-T signals, and content structure — view our SEO services or contact us to discuss your situation.