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The Future of AI in Search

Posted by Nikki on 01-Mar-2023 10:33:04
| 8 Minute Read

Why is AI such a hot topic right now?

The emergence of Artificial Intelligence (AI) is slowly but surely changing the way we interact with technology forever, and it is now a growing topic in many industries.

In recent years, AI has been used to automate tasks that were once done manually, reducing costs and improving efficiency. But today, AI is being applied to content creation tools, video generation tools, image manipulation tools, and finally, search engines; allowing them to better recognise user intent by understanding natural language queries and providing more accurate results.

AI-powered search engines are an intriguing trend, as they quickly become able to understand the underlying semantic context of each query to return relevant results based on precisely what the user is looking for. This makes it easier for users to find what they need quickly and accurately without having to sift through irrelevant content or guess at keywords that may produce better results.

With their ability to return much more detailed answers (accurately or not) in the blink of an eye, which could increase the number of zero click searches, AI-based search engines are now becoming equal parts assets and threats to both businesses and individual users alike.

It is possible that AI represents something of a threat to businesses, when applied to search, as it is likely to increase zero click searches, forcing businesses to work harder to find other ways to reach their audience.


How is AI used in search now?

Determining search rankings

Search engines are increasingly utilising Artificial Intelligence (AI) to rank webpages, videos, and other content in search results. By analysing massive amounts of data to prioritise distinct elements—ranging from keywords to user experience—AI search engines can accurately decide which pages get shown for any given query. As such, these AI systems have been pivotal in evolving search and making it easier for users to find exactly what they need online.

Primarily, AI is used to determine a search engine’s ranking algorithm based on a variety of criteria such as relevance of content, popularity, user engagement, number of backlinks, and even the user’s own search history.

Google's AI utilises various protocols to effectively manage the algorithms that power its search engine. This allows Google to provide a tailored experience to users, focusing on factors like preferences and previous searches they've conducted. Instead of ranking sites by score alone, this system produces more valuable results for viewers in order to satisfy their request quickly and accurately.

Understanding search queries

AI is used to understand search queries through a process called natural language processing (NLP). This involves using machine learning algorithms to analyse the structure, meaning, and intent of natural language, such as the words and phrases used in search queries.

NLP enables search engines to identify important keywords and phrases in a query and determine the context of the search, allowing them to deliver more accurate and relevant results to the user.

Additionally, AI can analyse past search behaviour and user data to provide personalised results that are tailored to each individual's preferences and search history. Overall, AI and NLP are critical tools for understanding search queries and improving the accuracy and relevance of search results for users.

Algorithm evolution for content quality control

Google's algorithm has evolved significantly over the years to improve content quality control and provide users with the most relevant and helpful results. One major development has been the implementation of natural language processing (NLP) technology, including the BERT algorithm.

BERT enables Google to better understand the context and meaning of search queries, resulting in more accurate and relevant results. In 2021, Google also introduced the Multitask Unified Model (MUM), which is even more advanced and can handle more complex queries and languages.

Another recent update is the "Helpful Content" algorithm, which prioritises content that is useful and informative for users. This includes content that provides clear answers to questions, offers detailed explanations of topics, and includes helpful visuals and multimedia elements. Overall, Google's algorithm evolution has always been focused on improving content quality control and delivering more helpful and relevant results to users, and will continue that way with the inevitable emergence of ever more sophisticated AI technology over time.


What are the pros and cons of AI in search?

The advantages

There are many advantages to using AI in search engines. One major advantage is that AI can help search engines understand the context and intent behind user queries, allowing them to deliver more accurate and relevant results. This improves the user experience by ensuring that users can find the information they are looking for quickly and easily, improving user satisfaction.

AI guided search engines also offer a smarter, more efficient way of finding information on the web and can be a useful tool for a wide range of users. With AI search technology, users don't have to worry as much about searching specific keywords or the way in which they search, AI can understand more complex queries and use predictive analysis to quickly find results that are more relevant to those that a standard search engine would provide.

Additionally, AI-powered search engines are constantly learning and improving their algorithms so that users always get the most up-to-date content available. Being able to draw from a larger pool of relevant sources means a better chance of getting a comprehensive overview on a particular topic.

The disadvantages

On the other hand, there are also some potential disadvantages of using AI in search to consider. One concern is that the use of AI in content generation and ranking may lead to a lack of originality in search results. This is because AI algorithms are trained on existing content and may be more likely to recommend or produce content that is similar to what has already been published. This could result in a lack of diversity and originality in search results, which may not always be helpful or informative for users, or for businesses looking to create differentiation.

Additionally, there is a risk that some AI-generated content may be overly optimised for search engines, leading to an emphasis on keyword stuffing or other (badly executed) SEO tactics at the expense of quality and readability. This could result in content that is difficult to read or understand, which could be frustrating for users and lead to higher bounce rates and loss of traffic on websites.

Plus, the rise of AI tools has made content creation easier than ever before. However, the ease of creating content can lead to abuse by some people who may use these tools to produce a large quantity of low-quality content. This inundation of low-quality content can make it difficult for users to find high-quality and relevant content in search results. This could cause a problem if it begins clashing with the overall objective of search engines: to provide the most relevant and useful results to users. As such, it will become vital for content creators to prioritise quality over quantity to ensure that their content is useful and adds value to the online ecosystem.

Overall, while AI has the potential to improve search engine performance, it is important to consider the potential drawbacks, such as the generation of incorrect information, and to ensure that any benefits of faster content creation outweigh the potential costs of providing inaccurate or worthless content.


What will AI in search look like in the future?

The future of AI in search is likely to be characterised by even greater advances in natural language processing (NLP), leading to more accurate and personalised search results. For example, the development of the Bard AI search engine by Google has the potential to dramatically improve the quality and relevance of search results by allowing users to ask complex, multi-part questions in a conversational format. Watch the demo to see it in action.

Similarly, Microsoft's Bing search engine (watch from 21:00 to see the demo) is already using AI to improve search quality by analysing the intent behind user queries and providing more relevant results.

However, the spread of inaccurate information could rise to become a major challenge when using AI-powered search engines. In a world where knowledge is a click away, it can be challenging to decide what information is trustworthy or not. As a result, a lot of false and misleading information circulates online, and AI search engines are unable to differentiate between fact and fiction. If people were to make decisions based on wrong data, this could lead to an increase in dangerous situations with serious outcomes. Search engine providers and end users should therefore take steps to ensure that they are verifying the accuracy of their sources prior to actioning any information retrieved from AI search engine queries.

Finally, it’s safe to assume we could see search result retrieval become even faster, even more streamlined, and highly relevant, with AI algorithms analysing user behaviour and preferences to deliver improved personalised results in real time. The rise of zero click searches in particular is something that has gained significant traction in the digital search space. With AI-based search engines, users no longer need to go to a website or page to find the information they seek – the answer is often provided right away in the form of a featured snippet. Though this kind of technology is efficient for web users, it will reduce traffic on websites and is something businesses will need to factor in their strategy when trying to target their audience.

On the whole, the future of AI in search looks to be exciting and full of potential for improving the search experience for users, but guidance is needed to circumvent some potentially damaging pitfalls.


Leveraging AI to improve organic search results

By leveraging the power of AI search engines, businesses are best placed to improve their organic search engine results in three key areas:

Content development

AI can be used to generate a greater variety of content topics and formats, ensuring a comprehensive approach to organic search optimisation.

In addition, AI search engines can identify current trends and topics that are popular with customers and suggest them as part of an overall SEO strategy.

However, using AI for content does come with a caveat: AI-generated content lacks the personalised touch and quality of a professional writer, who is arguably better suited to meet a company's messaging objectives and tailor their output accordingly. While using AI technology in content creation certainly offers many advantages in speed and efficiency, it would be wise for companies to take into consideration the nuances of human expertise which cannot be easily replaced by a machine, and to ensure that any information being presented is factually and statistically correct for their end user. This is made even more important when considering Google’s updated EEAT guidelines, which may downgrade content significantly if the search engine feels the content does not display the correct level of expertise, authority or trust.

Voice search

Using voice search to improve organic rankings through leveraging AI involves a strategy that has NLP (Natural Language Processing) at its heart. Businesses should optimise content for natural language and conversational queries, as voice searches tend to be longer and more conversational in nature.

Additionally, it is important to ensure that any content produced is mobile-friendly and tailored toward featured snippets, as these are often the first results that voice assistants like Siri and Alexa will read aloud in response to a query.

Finally, it is important to ensure that website content is optimised for local search, since voice searches are often location-based. This can be accomplished by including location-specific keywords and information throughout the website content.

Image search

Leveraging AI to improve a company's organic search results with image search can be a powerful tool to increase a business’ visibility. AI-based search engines are a great way to discover images and videos not usually found when using a traditional keyword-based search engine. They offer a vast improvement over the typical “search and replace” method, as they use deep learning methods to identify photos and patterns that align more closely with a user’s query.

By using AI search engines, businesses can effectively optimise a website for a wide variety of visual content, rather than relying solely on text searches to create a powerful optimised presence.

This kind of technology helps businesses find relevant images for their content which can result in an increase in website traffic, improved customer engagement, and higher organic search rankings.


Making AI work to improve your search rankings

As AI continues to evolve and becomes more sophisticated, it will continue to play a major role in how search engines work. By leveraging the power of artificial intelligence, businesses can create tailored experiences that prioritise user preferences and previous websites visited for much more relevant searches.

However, understanding your audience is still key in order to leverage the power of AI and make it work for you. Once you have a clear understanding of who they are, what their needs are, and how they search online – then you can start making use of AI-driven technologies like machine learning algorithms to improve your search rankings.

Over time, AI driven technologies such as a search engine’s ability to interpret human language quickly and accurately, combined with businesses producing content to meet user preferences, will enhance organic search to be even more personalised. Although this might only happen after a period of chaos where uninformed website owners will try to push vast amounts of low-quality content, which will likely be downgraded as the AI learns what good looks like.

These factors combined should help businesses drive quality traffic into their marketing funnel and increase sales by providing customers with valuable information tailored specifically for them.

Getting started with using AI to improve your search results

To make sure you are getting the most out of your search engine optimisation efforts, understanding how AI works and what factors contribute to better rankings will enable you to capitalise on them in your marketing strategy. With its ability to improve accuracy and speed up searches, there's no doubt that using AI technology has great potential for improving our online experience today - not just tomorrow!

We are already working with a number of clients to leverage the evolution of AI in search to deliver better quality results for them. Our team of search specialists are here to help your business reach its digital goals too. By deploying analytics, content and SEO strategies that will optimise your success in the artificial intelligence-powered future, we can work with you to make the most of this emergent technology and gain competitive advantage in your market. Talk to us today to learn more!

Topics: SEO, Technology, Content, Strategy, Digital Marketing, Effective Search Engine Optimisation (SEO), Content Strategy & Planning