Why artificial intelligence search engines won’t replace Google

The AI machines are set to take over other AI machines in a battle for global dominance. But this Black Mirror-style future isn’t set in the year 2835 involving machines called Quantum Blizzard and Cognitive Matrix, trying to take over the world. It is being predicted as the next phase in search engine development. This future is imminent and depending on who you listen to, it’s either a pathway to quick gold or a staircase to destruction. AI and marketing gurus are shouting from the rooftops how new AI search engines will destroy Google and the SEO business.

Yet, their argument is flawed. It fails to understand the commercial or technical realities of the search engine industry. The coolest search toys in town have quickly moved from ChatGPT, which is now basically a cassette player, to shiny new products like Perplexity. Ok, that’s perhaps harsh on ChatGPT. But the world of search is moving faster than it has since then the end of the 1990s. However, questions remain as to what AI search engines will look like and what will be their true impact.

AI search engines

AI search engines have come a long way

Despite the current AI search engine buzz, search engines have long used AI within their platforms. Google provides a great example, as the most widely used search engine in the world. The platform has evolved from rudimentary algorithms to sophisticated machine-learning applications. Initially, Google’s search algorithm relied heavily on basic rules. This saw keywords playing a pivotal role in determining search ranking. So, if you sold vitamin D supplements, you would have a better chance of ranking highly if you mentioned that on your webpage several times. However, this left Google searches open to Blackhat tactics that saw some shady SEO enthusiasts trying to game the system. This was not good for Google as it provided a poor user experience. After all, who wants to look at a website that crams the keyword vitamin D into one page? It’s like listening to “No Limit” by 2 Unlimited on repeat! 

However, in 2015 AI transformed how people make searches. Google introduced RankBrain, enabling Google search capabilities to transcend traditional keyword-based approaches. RankBrain has the ability to comprehend complex search queries and interpret user intent, even when explicit keywords are absent from web pages. RankBrain functions within the broader Hummingbird algorithm, which is a natural language processing (NLP) model primarily dedicated to semantic search. In short, it helped to deliver better results. For instance, when a user searches for “best health tests in the world” RankBrain can discern the user’s desire for at-home health test recommendations, considering factors like user behaviour and context to deliver more pertinent results.

AI chatbots have changed the direction

However, in November 2022, the concept of artificial intelligence search engines changed. The launch of ChatGPT turned technophobes, who were worried about operating a microwave, into AI evangelists. ChatGPT offered the world the first glance at the future of AI chatbots. Until then, chatbots were largely a gimmick, boarding on stupid. Remember Microsoft’s Tay?  That AI would be more likely to create a right-wing manifesto for idiots in the style of Tweets than explain how to make healthy meals containing a variety of vitamins.

But ChatGPT was the first domino to fall, setting off a chain of events that has sent search engines and SEO experts spiralling faster out of control than Ross from Friends attending a wedding. Built on a vast language model, ChatGPT enables users to have conversations with an AI and get specific answers to their questions. This meant, no more searching through the blue links provided by Google Search hoping for an answer. 

Surely this is the end of search engines as we know them? Thankfully for companies like Google and those people who have spent years building their SEO knowledge, the answer is much more complex than that.

Google interface. Google will continue to be important going forward despite advancements in AI search engines

What will be the different types of AI search engines in the future?

With any technical advancements, there is inevitably change. Therefore, it would be naïve to believe that search engines will remain as they are. The biggest changes will result from driving search results through the following:

  • Traditional Search Engines e.g. Google, Bing. This type of search engine is what we see today.
  • Search Generative Experience (SGE) e.g. Bing Copilot, Google SGE, Perplexity. These new AI search engines will aggregate information to provide answers to people’s questions. In many ways, they resemble advanced featured snippets, the answers provided at the top of Google search without requiring a click on a link. It’s essentially integrating AI into traditional search and will likely give you links to sources.
  • Answer Engine Optimisation (AEO) E.g. ChatGPT, Gemini. You can consider this type of AI search engine as a chatbot. You can explore topics with them and they will guide you. Moving forward they are likely to provide more citations for their advice.
  • Social Platforms e.g. Amazon, Instagram. Social media has already emerged as a search competitor. For example, over 30% of consumers utilise social media platforms as a means to seek solutions to their inquiries.

SEO experts will need to carefully understand each of these platforms, focusing on their varying use cases and optimising for them.

Before we outline each of these different platforms and the likely search use cases it’s worth addressing the elephant in the room. Are search engines going to be the DVDs of tomorrow? This is highly unlikely. 

Firstly, we need to understand how AI search engines work. They are built on large language models, which require data. From a search engine perspective, this means digesting information from a variety of sources including websites and online publications. However, if AI search engines provide you with everything you need, you will no longer need to visit a website again. Consequently, who will want to create the content that these AI search engines rely on? After all, if you are getting no online visits, what’s the point? It’s like asking Mariah Carey if she would be happy to perform in an empty room without payment so Ariana Grande can lip-sync to the world and get rich. Do you want to be the person to ask her? 

Secondly, there is the issue of monetisation. Currently, Google’s revenues are largely made up of ad revenue. Their search engine plays a significant role in this. Many of the emergent AI search engines are still pre-revenue. Of those that have started to monetise, it has been through a paid version of their platforms. Yet, this is not as scalable. So, to avoid all those pesky investors knocking on their doors, these AI search engines will need to transform from being disruptors to money-makers. That’s tough if you have killed the entire search market. 

However, that doesn’t mean things will stay the same. Going forward you will need to understand how AI and SEO work together and what that means for your digital strategy.

AI search engines rely on data insights

Niche content will see traditional search engines continue to thrive

In the future, there is a third key reason why AI won’t replace traditional search engines. This is because AI will be great at collating the best overall information as it’s intended to advise the many, not the few. So, for some searches like ‘what is NMN and what is it used for’ the AI search engines will offer great insight. However, they will not be as great at offering very specific advice, targeted at a niche user group, unless it is trained to do so. This is not practical for a generic AI.

For example, let’s assume you sell NMN supplements. In the UK interest in NMN has grown 480% over two years. Yet, the reasons for it are varied. Moreover, research into the field is fast developing. So, to ensure it remains relevant for the many, the AI will likely give answers that have been discussed many times. Therefore, there are still opportunities for niche insights to be seen in traditional search.

So, how will Artificial search engines change the landscape?

To understand how AI will change the search engine market, we need to understand the types of searches people make. Each of these types of searches will likely be impacted differently. The search types can be broken down into the following categories:

  • Explorational: This type of search is when someone seeks to discover new information or gain a deeper understanding of a topic. For instance, people may search for “benefits of cold-water therapy for mental health” to explore the potential advantages of this practice in improving well-being. Explorational searches often involve open-ended questions and may lead users to engage with various perspectives and sources to broaden their knowledge base.
  • Informational: People use these searches to find information. For example, they may ask what is cold water therapy or how many vegetables should I include in my 5 a day. The type of information they seek can vary and is perhaps the most interesting element in the future of search. 
  • Transactional: This category of search refers to queries made with the intent to complete a specific action. For example, it could include searches like “buy CGM online” or “best health clinic near me.” Users conducting transactional searches are typically ready to take direct action, such as making a purchase or scheduling an appointment, and are seeking relevant options or resources to facilitate the transaction.
  • Navigational: Used typically to find a website quickly. For example, people may type Bupa or NHS London to navigate quickly to the respective website. The intention is not to get information but rather navigate to a specific website.

Depending on the search type, we are likely to see AI search engines impact traffic in various ways.

AI searches to become the home of explorational searches 

These are searches people undertake to explore more about a topic. For example, how can I eat healthier? These types of searches are more open-ended and the user is looking to gather knowledge. AI search engines will be excellent at this. They will give people the broad basics from eating vegetables to staying hydrated. This will take over a proportion of the search volume. However, this type of search is likely to transition into informational searches after a certain point. After gathering basic knowledge, people may want to understand more about specific CGMs and if they should be used for personalising their diet.

As a result, some broad informational searches will be conducted with AI and the more specific advanced searches will be conducted via traditional search engines.

Key takeaways for explorational searches

  • AI will be used by people wanting to learn about a new subject
  • Advanced-specific searches will remain in traditional search engines

Explorational searches will be broad. These will be undertaken on AI search engines

Informational searches to face AI disruption resulting in changes to content focus

The future of search engines is likely to be predicated on how informational searches are managed. Whilst it is easy to assume AI will be a master of giving everyone the best information, the reality is more nuanced. It’s like expecting Elon Musk to give you the best guidance on supplement dosage for Methylene Blue. The guy is a brilliant engineer, but he doesn’t have the best answers for everyone. So, to understand how informational search traffic will be impacted, we should break this category down further:

Static Searches

This is perhaps the most complex. This type of information rarely changes. Therefore, we can expect a proportion of this search traffic to be taken up by AI search engines. However, static information can also change, and AI search engines will need people to update information for the AI to function. Therefore, expect more niche content designed for specific audiences to remain in traditional search engines. For example, how should individuals concerned about their glucose levels manage it through diet, exercise and technology? This type of static health information may be well-suited for AI-driven search engines to provide general guidelines. However, nuances in individual health conditions and preferences may require ongoing updates and personalised advice. This means niche content tailored to specific demographics will continue to thrive on traditional search platforms.

Originality will also continue to thrive in traditional searches. For example, you may wonder how the future of SEO marketing will look. Whilst SEO is a well-established field, using AI to understand it will become the domain of beginners (see explorational searches). For those wanting more insights, they will search for thought leaders offering unique insights based on multiple factors. An AI is unlikely to provide such information as it is designed to give the best, most common, overall answer. Moreover, anyone wanting to stand out in a specific field will be more likely to seek alternative views. After all, if everyone is using the same AI search engines and getting the same answers, how can they differentiate themselves? It’s like using TikTok for fashion tips, hoping to be edgy and different. The result is everyone dressing like they are from the 1990’s. Welcome to Shoreditch, London! 

This is real-time information. For example, the score from a sports game is likely to be best provided by traditional search. An AI could do it, but why would you need it to? These types of searches can also include breakout news like a possible cure for Alzheimer’s or trending topics. For example, Methylene Blue has soared in interest by 300% in the US, but why? If you are in the health optimisation field, you will seek answers from online experts, who will provide a breakdown of how social media is having an impact. Again, you are likely going to rely on reputable, niche publications to give you details. 

Buried Searches

This type of search traffic will thankfully be gobbled up by AI. This is the type of information that is so over-optimised by SEO that you can’t find what you are looking for without reading war and peace. As much as I like reading, sometimes I just want to find the best healthy sweet potato chocolate cake without reading about the history of sweet potatoes first! Just in case you are interested, sweet potatoes originate from tropical regions in South and Central America.  Anyway, AI will likely gather this information much more effectively, without the history.

Inspirational Searches:

Do you remember humans, those beautiful but flawed creatures that everyone spoke about before AI? Well since we are human, we still take significant pleasure in reading about other humans. These types of searches look for human stories and will continue to be popular in traditional search engines. AI may help aggregate them but we will likely want to continue finding stories written in the words of other people. Aww, what a wonderful world!

Key takeaways for informational searches

  • If you want your website to rank in traditional searches focus on original niche content creation.
  • Traditional search will also be the home of tending topics
  • Buried searches i.e. answers that are not easily found because they are buried deep into an article will be better served by AI

Informational searches will be undertaken across traditional search and AI search engines. Yet, they will continue to need data

Transactional searches will become widespread

Transactional searches are likely to be split between traditional search engines and social media. People want recommendations from people they trust so social media will become more powerful. However, people also want options and are likely to use traditional searches to find the best products and prices. However, expect AI to provide a helping hand in filtering down people’s requirements.

Key takeaways for transactional searches

  • Transactional searches will take place on traditional search engines and social media

Navigational searches to remain unharmed by AI search engines

Since navigational searches are straightforward, it’s unlikely AI will have any impact at all. If I want to find the website of my favourite Berbeine supplement provider, I am unlikely to need the help of an AI search engine. Instead, I will Google the company name and off I go. Whilst these types of searches are valuable, they depend heavily on how well you have grown a brand for your company or website. This means understanding how to grow your visibility on other platforms and drive traffic via search engines through informational-type searches. 

Key takeaways for navigational searches

  • Navigational searches will remain in traditional search engines

Which AI search engines will get the different types of traffic?

For website owners understanding how to optimise for different search platforms will be key going forward. Just because AI is likely to take a proportion of search volume, it doesn’t mean that you should ignore AI platforms. These will also be important places to grow your brand, reputation and traffic. However, we can expect the following platforms to take the following types of traffic:

  • Traditional Search Engines: Unique but niche or trending informational content. This will become the cornerstone of driving traffic in the future. Furthermore, transactional and navigational searches will likely remain on traditional search platforms.
  • Search Generative Experience (SGE): Likely to be the intersection of explorational and informational searches. These searches are where people have some knowledge of what they seek but are still unsure. To rank in this space, you need original niche content that closely aligns with traditional insights.

  • Answer Engine Optimisation (AEO): These types of AI search engines will become the bedrock of explorational searches. Going forward they will provide citations to specific websites. However, to earn one of those citations, you will likely need to be an established, trusted authority. So, think Bupa or NHS if you are looking for advice on heart health.
  • Social Platforms: These are not search engines by design but expect their influence to grow. Research from HubSpot has found 15% of individuals have a preference for social search as opposed to traditional search engines. Moreover, the combined preference for social search among Gen Z and Millennials stands at 29%. This type of search engine will likely attract informational, explorational and transactional search.

The path forward

Despite the rapid advancements in AI search engines, the future of search engines is not a foregone conclusion. While AI-powered platforms are poised to become more prevalent, traditional search engines like Google will likely continue to play a significant role. 

The key is understanding these changes, and how your online strategy must adapt. SEO will become a much more complicated field and website owners must adapt their optimisation strategies to cater to the varying use cases of different search platforms. If they do so, they can ensure their content remains visible and relevant in an increasingly diverse search ecosystem.

The furure of search engines will become more complex

Top 14 artificial intelligence search engines and assistants to try

If you are keen to explore how these AI search engines work, you can always give them a try. Below we have listed 14 of the best AI search engines on the market. As you will see, each has its own unique benefits.

  1. Google Gemini: This is Google’s answer to AI chatbots and search engines. It’s still experimental but free to use. It can answer questions in detail, generate creative text formats, and integrate with other Google services.
  2. ChatGPT: This is a popular AI chatbot and search engine known for being the first of its kind. It has a free version with limited functionality and a paid version with access to real-time data for more accurate answers.
  3. Perplexity: This describes itself as an answer engine and offers in-depth answers to questions using up-to-date information. It leverages LLMs, internet data, and its own version of Google’s PageRank to find trustworthy sources. It can answer follow-up questions and even create content in different styles.
  4. Microsoft Co-Pilot: Bing also has an AI-powered chat feature that refines search results and provides more complete answers. It uses a next-generation OpenAI language model specifically designed for searching.
  5. Mata AI: Built with Meta Llama 3, Meta AI is integrated with the Meta suite of social media apps. It enables you to get answers to questions, get recommendations and create free images.
  6. Andi Search: Andi Search throws tradition out the window with a visually rich interface and contextually relevant summaries. It uses AI throughout the search results and offers information with images, summaries, and options that are contextually relevant. It avoids showing just a list of blue links and focuses on user-friendliness. However, it has been criticised for a feature called Reader that republishes webpage content. This may leave it open to criticism and action from publishers.
  7. Exa: Feeling overwhelmed by information overload? This search engine offers links based on a user-selected category, such as tweets, research papers, or recipes. This can be useful for finding specific types of information, but it may not always be the best choice for general searches.
  8. NeevaAI: This is an ad-free, privacy-focused AI search engine that can still personalise results based on user behaviour. 
  9. Brave: This is a privacy-focused search engine that uses AI to summarise search results. It doesn’t aim to be a chatbot but rather offers summaries alongside traditional search results. It also uses AI to generate webpage descriptions for a quick overview of content.
  10. YOU: This search engine combines a large language model with up-to-date citations, making it more than just a search engine. It offers a search assistant called YouChat that can answer questions in natural language, write different creative text formats, and even run code. The platform claims to prioritise user privacy and not to sell user data. It also offers a paid subscription that uses OpenAI’s GPT-4 for more detailed and accurate answers.
  11. Phind: This is a generative AI search engine for developers. It uses a large language model and allows users to choose between different models, including GPT-3.5 and its own Phind Model. While it focuses on developers, it can also answer complex questions for a general audience.
  12. Komo: This AI search engine focuses on speed, and privacy, and offers three main features: Ask (brainstorming topics), Explore (trending topics), and Search (traditional search). It provides personalised search results and doesn’t show ads.
  13. Waldo: This search engine focuses on allowing users to fine-tune their searches and provides features like document publishing and research compilation. Designed for professional users, it offers a limited free trial.
  14. Yep: This is an AI search engine specialising in visual searches. It uses AI to understand and analyse images and provides search results based on complex user queries.

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