TL;DR: What is generative AI search?
AI search is changing how people search and discover information. This type of search behaviour takes place within traditional search engines such as Google and Bing as well as native generative AI tools such as Chat GPT, Gemini, Perplexity and Claude.
The results in both the AI overview summaries in search engines and the direct results in the AI platforms both share the same characteristics:
- AI search tools generate direct conversational responses rather than lists of links
- They draw on large language models (LLMs) and often live web data
- AI is already embedded into traditional search engines such as Google, Bing DuckDuckGo, as well as AI-only platforms like Chat GPT or Claude.
- AI responses are deciding which brands to mention, recommend, or ignore. Which makes AI search both a marketing challenge and opportunity.
- Small businesses need to move beyond traditional SEO and understand this new search environment now and should take steps to optimise for AI search, known as Generative Engine Optimisation (GEO) or Answer Engine Optimisation (AEO).
What is AI search?
AI search is a way of finding information using technologies underpinned by large language models (LLMs) rather than a traditional search engine.
When you ask a question in an AI tool, the model generates a direct, conversational answer rather than pointing you to a list of website links (as most people have come to expect through classic search engines such as Google, Bing, DuckDuckGo and Yahoo etc.).
The platforms most people associate with AI include ChatGPT (from OpenAI), Claude (from Anthropic), Microsoft Copilot, Perplexity and Google’s Gemini, but AI search is now also baked into traditional search engines like Google, Bing and DuckDuckGo.
Each of the major AI platforms uses its own underlying models, which have been trained on vast amounts of text data from the internet. When you ask a question, the model draws on that training to construct an answer. Many of these tools also pull in live web data to supplement their response with up-to-date information.
The result is a conversational response that answers your question directly, rather than a signpost to a list of links – as you’d get with a traditional search engine results page (SERP).
How does AI search work?
At the core of every AI search tool is a large language model. Think of this as a system that has scraped an enormous amount of content from across the internet over many years and learned the patterns, relationships, and meaning within that content.
When you type a query or instruction (known as a prompt), the AI doesn’t look up a pre-written answer. It generates a response based on what it has learned, and in many cases, it also queries the live web to fill in recent information the model wasn’t trained on (live web access is what keeps AI answers current and relevant), to provide you with a response.
How is AI search different from Google?
Traditional search engines like Google work by crawling the web using bots that visit billions of pages, read their content, and build a vast index. When you search for something, Google uses algorithms to rank the most relevant pages from that index and serve them to you as a list of results.
That process has remained broadly the same for decades, even as the algorithms have become more sophisticated. The output has always been a search engine results page (SERP) with a ranked list of links and usually a mix of organic results (free and earned placements) and paid ads (sponsored placement). Overtime, new features have come and gone on the SERPs, such as YouTube video suggestions, the Google Map Pack with local results, featured snippets and much more. But in general, the list of blue links has remained there as a constant.
AI search flips that model. Instead of returning links for you to click through and read the content yourself, an AI search tool reads the sources on your behalf and synthesises the information into a single answer. You don’t need to choose which page to visit, or click a link, as the AI has already made that decision for you as to what’s important and what the best answer is.
The key differences are therefore:
- Output: Google returns links. AI search returns answers.
- Interaction: Google responds to keywords and semantic similarity. AI search understands natural language questions.
- Clicks: Google search relied on the user to click through to pages, generating traffic to those websites as a result. AI search often answers the question, often without any click taking place if the user is satisfied the AI has answered their query sufficiently.
- Ranking: Google ranks you by position. AI search either cites you or it doesn’t. AI doesn’t rank, but it does provide a selection of website which may have helped inform its answer. However, this isn’t a ranking and you can’t rank in order in AI search as the sources it cites might be different every time for the same query prompt. This is because it’s a probabablistic technology and generates responses based on probability distributions rather than deterministic sorting algorithms. Unlike traditional search engines (which assign a fixed relevance score to each page and display them in a static order), LLMs calculate the probability of the next token (e.g. a word or piece of text) based on patterns learned during training. So, when an AI constructs its answer, it’s sampling from these probabilities and slight variations in the sampling process or the inherent randomness in how it weighs competing sources can lead to different combinations of cited websites for exactly the same question prompt. Therefore, there isn’t a single “position” to occupy, or a list to rank in, as the model’s output is a dynamic synthesis of information that shifts with every generation, reflecting the statistical nature of its prediction rather than a rigid hierarchy of authority.
AI search is already inside Google and Bing
This new form of search is already happening inside of traditional search engines such as Google and Bing, not just within the dedicated AI tools themselves such as Chat GPT and Claude. Google, Bing, DuckDuckGo and more have integrated AI into their traditional search pages, which is why this affects every business whether or not their customers are using ChatGPT.
Google’s AI Overviews appear at the top of many search results pages, above the organic listings. For a growing number of queries, including local and commercial searches like “best accounting firm in Exeter”, Google now generates a short AI-written summary before the user sees a single organic link. However, sponsored paid results (ads) may appear above the AI overview first for some queries. This can differ based on things like whether it’s a commercial-intent keyword, or dependent on industry.
Microsoft Bing has integrated its Copilot AI in a similar way. Even DuckDuckGo now has a built-in AI search feature, called Search Assist.. Rather than experimental features, AI answers are becoming the default search experience.
Google has also introduced AI Mode as an optional feature for users to use. This is a version of search that replaces the traditional results page entirely with an AI conversation interface, similar to what you’d expect from the dedicated AI tools like Chat GPT. A prompt box and a conversation with natural language.
Google’s product lead signalled in September 2025 that AI Mode could become the default search experience, though Google subsequently clarified it would not replace traditional search as the default in the near term. AI Mode is currently available as an optional feature for users in the UK and US. If it does eventually become the default, the implications for search and website traffic would be significant.
What does this mean for website traffic?
Many businesses have noticed a sharp drop in organic traffic over the past two years. For some, this has been alarming. But traffic and business performance don’t always move in the same direction.
Some businesses are seeing enquiries and revenue hold steady or grow even as their traffic declines. The reason is that AI Overviews are answering questions and surfacing brand names at the top of the page. A potential customer might read an AI summary that mentions your business, close the tab, and then search for your brand directly a day later. That visit shows up in Google Search Console as a branded search, not as AI-driven traffic. The attribution is lost, but the awareness was generated via AI search even if it appears as direct traffic or a branded organic search.
Measuring the impact and performance of AI search is one of the trickiest parts of AI search for marketers. The tools to do this well are still developing. What is clear is that being recommended in AI answers is becoming as valuable as ranking on page one of Google, if not more so.
What about AI agents and the future of search?
To muddy the waters further, AI agents is a further development worth being aware of, even if it isn’t fully here yet.
An AI agent is a system that can take actions on your behalf, rather than simply answering questions. Google’s CEO described a theoretical near future where search works more like an AI agent manager. You’d tell it what you want, and it dispatches agents to find information, compare options, and even complete bookings or purchases for you.
If that becomes the norm, businesses will be optimising for machines as much as, if not more than for humans. They’ll be optimising for AI agents that are making decisions about which suppliers, services, or products to recommend or act on. The signals those agents trust will matter enormously.
It’s still early, but it underlines why the foundations you build now for AI search visibility are worth getting right. In April 2026, Google published guidance on its developer resource web.dev recommending that web developers treat AI agents as a distinct audience alongside human visitors with a few key technical optimisations to make a website agent-friendly.
Why small businesses need to pay attention now
You don’t need to be a technical SEO to start thinking about AI search or acting on it, but you do need to accept that it’s already affecting how you get found, whether or not you’ve noticed.
A useful starting point is to ask AI tools the same questions your potential customers are likely asking. Ask it to recommend providers in your category and location without mentioning your business. See whether you appear, how you’re described, and which competitors are being cited alongside you. Then search for your business by name in ChatGPT, Perplexity, or Google’s AI Mode and ask the AI to profile your business as a potential supplier.
AI is a bit like a mirror in that is really shows where your strengths and weaknesses are in terms of brand messaging, clarity, visibility and positioning. If the AI is praising a competitor for something you also do, but you’re not mentioned, that’s a signal about how clearly your website and wider online presence communicates what you offer. If you are mentioned, but the AI has represented you in a way that doesn’t align with how you see yourself, or if it’s got details wrong, that’s a sign you need to be clearer in your messaging about those points on your website and across the web – so there can’t be any room for confusion next time.
The good news is that many of the things that help with AI search are things you should be doing anyway: clear, well-structured content, consistent business information across the web, evidence of expertisen (testimonials, case studies, reviews etc.), and a clear fast-loading website that machines can read easily. None of that requires a big budget.
Where to start with AI search
If you’re new to this, here are four practical steps to get your bearings:
- Search for yourself. Ask ChatGPT, Claude, Perplexity, Duck.ai, and Google’s AI Overviews questions your customers would ask. See where you appear and how you’re described.
- Check your business listings. AI tools pull information from directories, maps, and third-party sites. Make sure your name, address, phone number, and business description are consistent and accurate across the web.
- Review your website structure. Is your content clearly organised with good use of headings (e.g. H2s, H3s etc.) that align with the type of questions your prospects might ask. Can someone (or an LLM) read a page and quickly understand what you do, who you help and what makes you credible? If not, that’s a priority.
- Stay curious and keep learning. This space is moving fast. The businesses that adapt early will have an advantage that could be hard to close later.
The rest of the articles in this AI search series will go deeper on each of these areas. A good next step is to read about how cleaning up online business directory listings can increase AI search visibility and citations, while also being an SEO good practice and therefore a win-win.
Google have also released guidance on optimising your website for generative AI features on Google Search and are calling it “still SEO” rather than GEO or AEO. Which will help you understnand how you can optimise for this new era of search.
Frequently asked questions about AI search
What is AI search in simple terms?
AI search is a way of finding information online using artificial intelligence (AI) to answer your questions, rather than a traditional search engine like Google, Bing or Duck Duck Go. Instead of returning a list of links, an AI search tool generates a direct answer to your question, written in plain natural language.
What is the difference between AI search and Google?
Google uses algorithms to rank and return a list of website links in response to a search query. AI search tools use large language models (LLMs) to generate a direct answer, often without requiring you to visit any website. Google is increasingly blending both approaches through its AI Overviews feature which is an AI answer section inside the traditional Google search results page.
Which platforms are AI search engines?
The main AI platforms include ChatGPT (OpenAI), Perplexity, Claude (Anthropic), Microsoft Copilot, and Google Gemini, all of which can be used for search-based queries as well as helping users conduct non-search-based AI tasks (e.g. writing code, rewriting a document, designing something etc). Google, Bing and DuckDuckGo have also integrated AI into their traditional search engine results pages (SERPs) through AI overviews respectively.
Does AI search affect small businesses?
Yes. AI tools are used to find and compare local businesses, services, and suppliers. If your business isn’t visible to these tools, you may be missing out on enquiries from potential customers who never reach your website.
Do I need to do anything differently to appear in AI search results?
Some things that help with AI search overlap with traditional SEO, such as clear website structure, consistent business information, and authoritative content. There are also specific approaches, like entity building, that can improve how AI tools understand and represent your business.
Is generative AI search just a trend or is it here to stay?
Generative AI search is already embedded in the most widely used search engines in the world. Google’s AI Overviews appear on billions of searches and AI Mode is ibeing used increasingly as people discover it. While the specific platforms and tools will change over time, the shift toward AI-generated answers is a permanent change to how people find information online and one that many people increasingly prefer.
About the author
Mike Smith is a Marketing Manager with 9 years of experience in B2B marketing, based in Kingsbridge, South Hams, Devon. marketingstuff.co.uk is his blog for solo marketers and small marketing teams at UK SMBs who want practical, plain-English marketing advice without the fluff. If you found this useful, explore the rest of the AI search series for more on how to get your business visible in the places your customers are actually searching.