--- title: "What are the latest AI features integrated into popular search engines?" description: "From Google's AI Overviews to DuckDuckGo's Search Assist, every major search engine is adding AI. Here's what each one offers and what it means for how people search." author: "Andrea Tendero" date: "2026-08-25T12:00:00.000Z" url: "https://freshjuice.dev/blog/ai-features-in-search-engines/" --- # What are the latest AI features integrated into popular search engines? August 25, 2026 • Written by [Andrea Tendero](https://freshjuice.dev/authors/atenlotrad/) AI this, AI that. It seems like this technology is the only valuable and useful thing that has been invented since the wheel, even though it has been out there for longer than people think. We know it’s a trend, and it shows in the way even search engines (which have actually been using AI for a very long time) are now marketing their new AI features as if they were gold. But what are these features? ## What AI features do top search engines use? We have already talked a little about [how Google is introducing AI into every tool they have](https://freshjuice.dev/blog/ai-is-overtaking-google/) (from their search engine to their Ads platform), but other popular search engines like Microsoft Bing (yes, more people than you think use this) are also integrating this technology into their systems. How? Well, each in their own way, but as you’ll see, they all have kind of similar features. ### Google The most used search engine in the world (more than [91.3% of the population](https://gs.statcounter.com/search-engine-market-share?utm_source=freshjuice.dev) have this as their preferred search tool) uses different AI features within the tool, with the most notable ones being AI Overviews and AI Mode. However, there are other features within the search tool that we should mention, like Multisearch, Circle to Search, and Google Lens integration, three visual and multimodal features that use AI in different ways. All these features use AI in different ways and are meant to improve how users search, synthesize web data, process images, and handle more complex questions directly within the search experience. Let’s take a look at each one to better understand what they are meant to be used for: - **AI Overviews:** Provides an AI-generated summary at the top of some search results, giving users a quick overview of the information they are looking for and links to explore the topic further. - **AI Mode:** Takes the conversational approach a step further, allowing users to ask more complex questions, ask follow-up questions, and explore a topic through a more conversational search experience. - **Multisearch:** Allows users to combine different types of searches, such as text and images, to ask more specific questions and find information that might be difficult to describe using words alone. Its newer capabilities also use generative AI to better understand more complex questions about images. - **Circle to Search:** Allows users to search for information about something they see on their screen by circling, highlighting, or tapping it, without having to leave the app they are using. While it is primarily a visual-search feature, Google has increasingly added AI-powered capabilities to it, including AI Overviews and more advanced image understanding. - **Google Lens Integration:** Uses image recognition and AI to understand what is shown in an image and provide relevant information, such as identifying objects, translating text, or finding similar products. It is essentially Google’s visual-search tool, with AI playing an increasingly important role in how it understands and processes images. ### Microsoft Bing Microsoft Bing also has AI integrated into its search experience, with Copilot being the main feature users will encounter. Copilot allows users to ask questions in a more conversational way and receive direct AI-generated answers instead of simply getting a traditional list of links. It can also use information from the web to provide up-to-date answers and citations. One of the most interesting things about [Bing’s AI integration](https://explore.microsoft.com/en-us/bing/features?ch=1&form=MT00SR&cs=2349671405&utm_source=freshjuice.dev) is that users can continue the conversation after receiving an answer, asking follow-up questions without having to start a completely new search (same as Google does). This makes the search experience feel more like a conversation with an AI assistant than a traditional search engine. Bing also offers Copilot Search, which is designed to combine traditional web search with AI-generated answers. It searches the web, brings together information from different sources, and provides citations so users can explore the sources behind the answer. So, while Bing still works as a traditional search engine, Microsoft has been adding AI features that make the experience more conversational and focused on generating answers rather than simply providing a page of search results, following the trend among search engines. ### Yahoo Yahoo has also joined the trend with Yahoo Scout, an AI-powered search experience that allows users to ask questions and receive AI-generated responses. Users can also ask follow-up questions to refine their search or continue exploring the same topic, making the experience more conversational than traditional Yahoo Search. The interesting thing about Yahoo Scout is that it can be accessed directly through Yahoo Search, meaning that users can choose between traditional search results and an AI-generated response depending on what they are looking for. ### Yandex Yandex has also integrated generative AI directly into its search engine through Yandex AI (called YandexGPT). The feature can analyze multiple sources across the web and generate a concise answer that appears above the traditional search results, with links to the sources used. Users can also ask follow-up questions and continue the conversation while keeping the context of their previous query with [Alice AI](https://en.wikipedia.org/wiki/Alice_AI_\(AI_model_family\)?utm_source=freshjuice.dev). In this sense, Yandex is following a very similar approach to Google and Bing, combining traditional search with generative AI answers and conversational follow-ups. ### DuckDuckGo DuckDuckGo has taken a slightly different approach to AI. Its search results include Search Assist, an optional feature that uses AI-powered natural language technology to generate short answers based on information found on the web. The answers include links to the sources used, so users can explore the information further. If users want to continue the conversation, they can move from the Search Assist result to [Duck.ai](https://duck.ai/?utm_source=freshjuice.dev), DuckDuckGo’s private AI chat service, where they can ask follow-up questions and interact with different AI models. So, unlike Google or Yandex, DuckDuckGo separates its AI-assisted search answers from its dedicated AI chat experience. As you have probably already noticed after reading about all the AI features that the most popular search engines have, they all have a similar system: AI-generated overviews or answers, the possibility of asking follow-up questions, and an AI tool specific to each company. Even though we should clarify that the exact implementation is different, the general idea is actually the same: search engines are moving away from simply providing a list of links and increasingly trying to give users a direct answer first, which can then be explored further through the use of their AI tools. ## Which search engines offer AI-based personalized results? Regarding the search engines listed in the article, not all of them offer AI-based personalized results. To provide a truly personalized answer, a search engine needs to have access to some type of information or signals about the person searching, such as their preferences, previous searches or activity, location, language, or account profile. All of the search engines we have mentioned are using AI-powered features, but using AI doesn’t automatically mean that the results are personalized. AI can generate an answer based on the information included in the current search, without knowing anything about the person behind the query. Think about it like using ChatGPT without logging in: you can still ask questions and get an AI-generated answer, but the tool doesn’t necessarily know your previous conversations, preferences, or personal context. The same idea applies to AI-powered search in search engines. If the search engine doesn’t have access to previous searches, patterns, preferences, or other relevant signals, it has much less information to personalize the answer specifically for you. Google, for example, can do this as users usually log their accounts in Chrome to get a more convenient experience when using it. However, it must be said that personalization doesn’t always mean that the search engine knows exactly who you are. Some results can be adapted based on contextual signals, such as your approximate location, language, device, or what you have searched for during the current session. This is different from having a detailed personal profile that allows the search engine to understand your long-term preferences. In other words, if you are on your phone searching for something for a long time, the AI can start to personalize your search as it is getting signals on how you ask the questions, you may have your location on, etc. This is where things get interesting, because the search engines we have discussed don’t all approach personalization in the same way. Google, for example, can use information associated with your Google Account and your Search activity to personalize parts of the search experience, depending on your settings. Bing can similarly use information associated with your Microsoft account and other signals to personalize its experience. Other search engines put more emphasis on privacy and therefore limit the amount of personal information they use for personalization. So, when we talk about AI-based personalized search, we should actually separate two things: AI-generated results and personalized AI-generated results. The first is becoming increasingly common across search engines, while the second depends on how much information the search engine has about you and what it is allowed to use. This also means that two people can search for exactly the same thing and potentially receive different results or AI-generated answers, not necessarily because the AI is “thinking” differently about them, but because the search engine may have different contextual or personalization signals available for each user. And this is likely to become even more important as search engines move towards conversational AI. The more users interact with these tools, ask follow-up questions, and provide information about what they are looking for, the more context the system can potentially use to make the search experience feel personalized. ## Are there search engines without AI features? All the most used search engines use AI in one way or another. Is there any search engine that doesn’t use AI out there? Well, probably not. Why? Because right now, as AI is a trend, we have the feeling that this is a new thing that has recently appeared and changed the game regarding how search platforms work, but this isn’t true. AI and machine learning have been used for a long time by search engines to understand queries, retrieve information, rank results, and improve the overall search experience. Google, for example, introduced [RankBrain back in 2015](https://es.wikipedia.org/wiki/RankBrain?utm_source=freshjuice.dev), and it has been using AI and machine learning in different parts of Search ever since. The difference comes when we see the type of AI used back then compared to the one being used today. In the past, AI was mostly working behind the scenes, helping search engines understand what users were looking for and decide which results were more relevant. It was already more complex than simple keyword matching, but users didn’t necessarily notice that AI was involved. It was there, but it wasn’t directly interacting with them. Now, things are quite different. Search engines are putting AI directly in front of users, generating summaries, answering more complex questions, understanding different types of inputs, and even allowing users to have a conversation with the search engine. This newer type of AI uses technologies such as natural language processing and generative models to understand context and generate direct answers, as if the tool were talking to you. However, even though the AI models used differ, the question isn’t really whether search engines use AI or not, because most of them have been doing so for years, as we have already mentioned. The interesting question is how visible that AI is to users and how much of the search experience it is now controlling. ## Conclusion Right now, all the major search engines are using complex AI tools that use natural language processing, machine learning, and generative models to provide answers within their search engines that aren’t just a list of links to websites. This can be an apparent improvement to the UX, as it’s more convenient for users to get a quick answer to what they have been searching for. This new way of providing results is quite similar across all the search engines, as they are giving users a quick, easy-to-understand answer that can be followed up with more questions and continued through their AI tools, whether it’s Gemini, Copilot, Alice AI, or another AI assistant. These are the main AI features search engines are implementing right now, and even though we might think AI implementation is a new thing, we have to remind ourselves that AI has been used in search engines for a long time. The difference is that, in the past, AI and machine learning mostly worked behind the scenes, helping search engines understand queries, rank results, and improve the search experience. Now, generative AI is much more visible, as it is directly interacting with users and generating answers. That’s why finding search engines that completely avoid the use of AI is quite difficult nowadays. The interesting thing to watch now isn’t whether search engines will use AI, but how much AI they will integrate into the search experience and how this will change the way we search for information. ## Related - [AI is overtaking Google: news that you should care about](https://freshjuice.dev/blog/ai-is-overtaking-google/) - [How to do SEO for Gemini](https://freshjuice.dev/blog/how-to-do-seo-for-gemini/) - [AI answer engine optimization: the future of SEO](https://freshjuice.dev/blog/ai-answer-engine-optimization-aeo-future-of-seo/) - [#AI](https://freshjuice.dev/tags/ai/), - [#AISearch](https://freshjuice.dev/tags/ai-search/), - [#SearchEngine](https://freshjuice.dev/tags/search-engine/), - [#Google](https://freshjuice.dev/tags/google/)