What Is an AI Search Engine?

A user enters a query in the search bar, and a traditional search engine compares it against the data in its index to retrieve data that matches that query. This is often referred to as keyword search, or sometimes lexical search.

A search engine that leverages artificial intelligence (AI), sometimes also referred to as an AI search engine or AI powered search, retrieves data a little differently. It still compares a query against indexed data, but it doesn’t just look for exact matches. Often, the search result it returns is further refined by semantic search to uncover the users intent or contextual similarity to layer on additional information to that query, like who’s asking or what actions they took along with entering that query.

AI in search engines often means employing both keyword/lexical techniques along with semantic or vector search to achieve this precision in search results, resulting in hybrid search. These search techniques create a foundation for machine learning, like natural language processing (NLP), large language models, and others to offer personalized search. For example, NLP techniques allow a searcher to ask a computer a question in the same way they might ask another person — no boolean operators required.

Whether in ecommerce, customer support, or digital workplace, an AI search engine’s goal is to quickly connect a searcher with the answer they’re looking for.

7 Things Search Architects Want Leaders to Know

How Does An AI Driven Search Engine Work?

Many enterprise search engines use federated search, which is a way of centralizing content by linking pre-existing system indices. While this is functional, it’s not optimal — content isn’t ranked on the same factors, which can contribute to searcher overwhelm.

With a unified index and out of the box connectors, you unify content across multiple sources without migration, and apply the same ranking and AI models regardless of source. Search features like query pipelines empower search administrators to sculpt the search experience for each unique audience. And using pre-tuned ranking factors combined with AI technology, enterprises can gain amazingly fast, satisfying out-of-the-box relevance — including accounting for user behavior to satisfy context and intent.

Experiences Tailored to the One in a Million

Behind the Search Box: AI in Action

Let’s look at an example: you’re on an outdoor recreation website looking for a new seat for your bicycle. When you type this query into the search bar, two options rank at the top of your search results: blackburn gel bike seat and addmotor bike pad. Blackburn gel bike seat has the exact query in the title, as well as multiple other instances throughout its content. Because the addmotor bike pad only has one of the terms in its title and fewer mentions in the body content, it’s ranked lower.

But here’s where user behavior comes into play: addmotor bike pad is clicked on more often than blackburn gel bike seat, and usually users don’t return to the search page to perform another search. This is why addmotor bike pad can rank higher than blackburn gel bike seat — through user behavior, the content is considered more relevant to the inputted querry.

Search vs Gen AI in Search

While generative AI tools are reshaping user expectations around their search experience, it’s useful to know the difference between the two technologies. As discussed above, a search engine analyzes a query and returns matching results. Generative AI can retrieve data as well, but it then takes that data one step further by analyzing the results and reformulating them into new content. Because they can synthesize answers from multiple documents, generative AI is a great way to help users self-serve answers for complex queries.

If you’re wondering whether your company should opt for one technology over another, consider this: enterprises should adopt both. After all, generative AI is only as good as your search relevance. Search — also known as information retrieval — is fundamental for GenAI guardrail techniques like retrieval augmented generation, or RAG. And RAG safeguards your company from AI hallucinations, bad answers, or missing information.

Coveo offers both fully managed generative answering options, as well as robust APIs that allow you to bring the power of Coveo’s index and ranking factors into custom or existing generative projects.

Generative Answering or Agentic AI? It All Starts with the Right Retrieval

Benefits of AI Powered Search Engines

Today’s enterprises are trying to balance competing objectives: cut costs while supporting growth. AI powered search engines can help balance both. By unlocking and surfacing siloed content to people when and where they need it, customers and employees get crucial information to make the best decisions possible.

The right AI search platform does all this while growing with your business. With relevance at scale, your digital experiences continue to deliver regardless of audience size or content volume. And on top of that, AI search readies your business for new innovations like generative answering, agentic AI, or whatever comes next.

Reveal How Much AI Search Can Help Your Business

$ 0 M

saved in annual cost-to-serve via 31% reduction in support cases

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conversion rate by applying AI search to a 34,000-product catalog

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boost in self-service success after unifying 20 websites with AI search

Getting Started With the Best AI Search Engine

Today’s users expect fast, accurate, and personalized results — whether they’re customers, employees, or partners. Traditional, siloed search often can’t keep up, lacking the intelligence to understand context or scale across complex digital ecosystems. An AI powered search engine changes that — learning from behavior, adapting to intent, and connecting people to the right content at the right time.

Coveo is purpose-built for enterprise challenges. Its AI-driven platform scales effortlessly across business units, content sources, languages, and user types — no matter how large or fragmented your digital landscape is. With out-of-the-box connectors, unified indexing, and advanced machine learning, Coveo delivers relevance that both scales across and grows with your business.

Whether you're optimizing customer self-service, streamlining employee workflows, or personalizing commerce experiences, Coveo helps you turn search into a strategic advantage.

Ready to see what intelligent search can do for your organization?

Frequently asked questions

No — AI search is here to stay and is becoming the user expectation. Users want fast, consumable answers vs. clicking through the multiple data links that keyword search serves up. AI search delivers real, measurable value. It goes beyond basic keyword matching by using machine learning to understand context, predict intent, and personalize results. Organizations using AI search often see improvements in self-service success, support efficiency, and conversion rates.

With Coveo, you connect to your enterprise data where it lives –⁠ no need for costly data migrations. While more data can enhance results over time, AI search platforms like Coveo are designed to deliver value from day one. They use pre-trained models and contextual signals — like click behavior and metadata — to improve relevance even in environments with limited historical data. Our robust platform will also help you identify gaps in your data and search trends, so you know what your customers are looking for and where you have holes to fill.

No. AI augments human decision-making by surfacing the most relevant information quickly and consistently. It empowers users to make better, faster decisions — it doesn't replace them.

Google is built for the open web. AI-powered enterprise search platforms are built to understand your unique content, users, and goals — offering more relevant, secure, and personalized results within your enterprise’s digital ecosystem.

AI search improves case deflection, speeds up resolution, and enhances self-service by delivering contextually relevant knowledge articles, FAQs, and past cases to both customers and agents in real time.

Learn more about how AI search can help with customer support.

Yes. Coveo integrates seamlessly with leading CRMs like Salesforce and Microsoft Dynamics, enriching search experiences within support portals, agent consoles, and customer communities.

Learn more about how AI search enables omnichannel customer service.

Open-source tools offer flexibility but often require extensive customization, maintenance, and in-house expertise. Enterprise solutions like Coveo are turnkey, scalable, and come with built-in AI models, security, support, and connectors — so you can focus on outcomes, not infrastructure.

Build vs buy search? Choosing the best path for your enterprise.

What Is an AI Search Engine?

How Does An AI Driven Search Engine Work?

Behind the Search Box: AI in Action

Behind the Search Box: AI in Action

Search vs Gen AI in Search

Search vs Gen AI in Search

Benefits of AI Powered Search Engines

Getting Started With the Best AI Search Engine

Getting Started With the Best AI Search Engine

Frequently asked questions

See What an AI Search Engine Can Do For Your Organization