How Are Search Engines Using AI?

It seems easy enough to use a search engine; add your query, submit it, and get a results page with results pointing you to the information you seek. Behind the scenes, search engines are very complex, utilising various technologies, including artificial intelligence, to provide valuable and relevant answers to your query. This article is a helpful guide for understanding AI’s role in your favourite search engines.

Understanding AI For Search

Artificial Intelligence (AI) is a set of technologies that can learn and improve without additional human input. The different types of AI, such as machine learning, natural language processors and others, all do different things. They are also at different maturity levels, meaning some are more capable than others.

A deep understanding of how AI works is optional to understand how search engines use it. You need to know that AI is good at finding patterns in data, parsing data, and making meaningful predictions, such as what web pages have information closely aligned to your search query and intent.

Their ability to learn makes them much more powerful than traditional software and is the primary reason they are so valuable for search.


Understanding Content Written For Humans

Google has routinely said that you should not create content optimised explicitly for AI and its algorithms. The popular search engine wants you to write content for humans first. This content provides the information and answers people seek when searching on their platform. Google says that if you write content for human readers, AI will understand it and thus index and rank it accordingly.

Recently, the explosion of AI-powered platforms able to produce short and long-form content has led to search engines creating AI to detect the use of AI on websites. Google has gone as far as to say they are considering ranking websites perceived to have content created primarily by AI differently from those written by humans.

From the above, we see the first potential use of AI in search engines, detecting content written for humans by humans and ranking it accordingly.


Understanding Context and Finding The Right Results

Google was initially created to provide answers and information. This means the search engine needed an AI that could understand the words used in a query, how users used them, and which content the user was likely looking for.

Since Google already indexes billions of pages, it can use AI to find out how different words are related and then find content that aligns with those words. For example, a search for “a bed of unusual size” might bring up results for oversized beds or give users results of the different oversized bed sizes. AI enables the link between the search query and the results portrayed.

Understanding context is also crucial for producing the right results when there are conflicting results. For example, Jaguar is both a land animal and a car manufacturer. Searching for the term will bring up results for both, but searching for “Jaguar engine” will only bring up results for the car manufacturer. This shows the AI used by the search engine understands context and can give you the right results.


Using AI For Quality Control

People have always looked for ways to beat the system, and SEO is no different. In the past, certain SEO “specialists” would learn everything they could about search ranking, SEO, and how search engines worked to devise ways to beat the system. Doing so was known as  Black Hat SEO. Some techniques used included creating websites for link building, keyword stuffing, invisible text, and others.

This meant search engine result pages had high ranking pages that provided little use to visitors, harming search engines’ reputations. They started using AI to find websites utilising these tactics and banning them.

Now, search engines can detect and suppress such pages and websites in the SERPs, which is why you do not see such pages as much these days.


Producing Results When The Meaning is Unclear

Using context to understand queries and provide the right results extends to what Google calls neural matching. Google uses words in the query to provide context on how the query is related to pages on Google’s index. The page needs to be understood within the context of the query, and if this context matches the context on the page and those related to it, the page is shown as a result for that query.

Neural matching is used across all of Google’s products, languages, and regions. According to Google, it is used when the query would not be understandable by a human as-is, and thus further context would be required.


Understanding Meaning and Intent

Understanding what someone is searching for is accomplished by looking at how they structure their query. Knowing the intent behind their search is important, too. Search engines use artificial language and neural processing to understand intent and surface the right results. A search engine achieves this by looking at the combination of words used and how they can be used to provide meaning.

For example, a search for “health insurance for sick spouse” could be interpreted as someone looking to purchase health insurance for their sick spouse. Google would then provide results for it if that is possible and the steps to do so if it is.


Using Your Screen For Search

A recent addition to search engine capabilities is the ability to search for whatever is on your screen. Google is leading in this regard with its Google Lens feature. To use this feature, you can open the Google app on your Android device and then click to search for whatever is on the screen, which could be a live camera feed or an image you have taken before.

Google Lens uses AI for image recognition and other technologies to help you find different search results, such as web pages, photos on your phone or even shopping recommendations.


Enabling Multi-search

The ability to search using different input types has been a dream of many for a long time. Google has made this possible through a recent change to search that allows users to use images and text to search simultaneously.

To use this feature, click on any image you see on Google image search result pages. You can then click on the item to get more details about it. If you do not like something about it, you can type what you want to change and find it instantly.

For example, you might see brown and white curtains when you search for “living room ideas”. With multi-search, you can click on the curtains and add the colour you like at the end. Google will then show results for that curtain in that new colour. Alternatively, the search engine will show you similar results in that colour.

All of the above is powered by AI and other features that Google has worked on for some time.


Voice Search

The voice search segment is growing, and AI powers it. One of the reasons for its growth is the increase in the use of personal assistant devices in the home and on the numerous devices we carry, such as our smartphones and watches.

The primary technology used is Natural Language Processing which understands human voices in real time and translates the speech into a search term used to produce results. These systems have become so good that many people use them without thinking about how they work and making them an integral part of their daily lives.


Better targeting and Ad Quality

Ads are the biggest revenue generator for Google. The search engine has always wanted to show visitors the best ads according to their preferences, making them more likely to click. Targeting can help with both. Google has already filed patents that allow them to use AI in search result pages for better targeting. Google will use AI to improve the statistical models used behind the scenes by Google to show users ads. These improvements benefit both users and businesses. Businesses can be sure that their ads are being shown to the relevant audiences, i.e., people who are likely to buy, and users do not feel like the ads are intrusive because they are highly targeted.



Search engines have been using AI long before it became popular. They use it to decide if the content is of high-enough quality, to rank websites and pages using their algorithms, and to keep spammy websites from ranking. As the capabilities of search engines increase, we expect AI to become an even more critical part of our search experiences.

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