The average person ‘Googles’ something at least 3 to 4 times a day. (Probably way more, if we’re being honest.)
Search engines have been invaluable tools in the discovery and exploration of the Internet, with diverse platforms from the likes of Google, Bing, Baidu, and DuckDuckGo dominating the market.
In 2021, we wrote an insight predicting the future of search engines based on a recent (at the time) patent for ‘queryless search,’ published by none other than Google. The patent is no longer accessible — and many things have changed dramatically in just two years.
More specifically, artificial intelligence (AI) has taken the internet by storm, transforming the way it works and opening a plethora of capabilities for search engines.
AI has also begun to revolutionize the way we search.
Google's most recent initiative to enhance its search engine with AI is a testament to the rapidly evolving landscape of search technology.
The new Search Generative Experience (SGE) integrates the capabilities of generative AI seamlessly into Google Search, enabling users to quickly find and comprehend information. With SGE, you can make sense of a topic through AI-generated summaries and insights, get suggestions on how to dive deeper into the subject, and receive natural prompts for further exploration. Generative AI in search can also provide diverse viewpoints so you can see the bigger picture and make more informed decisions.
This is an advanced iteration of Google’s older ‘queryless search’ concept (that we discussed previously), which aimed to enable their search engine to give users the results they’re looking for — without the need for the user to provide any search queries. Essentially, the goal was to optimize the user experience by automating the search process.
‘Queryless search,’ in turn, was a development from Google’s existing Discover feature. Google Discover is a more basic service that curates and suggests webpages that may be relevant to the user, creating a personalized content feed. It operates by examining your browsing history and user data to make general assumptions based on your behaviors, and then identifies other related trends you may be interested in.
If we dive even deeper into the history of Google’s AI innovations, one of its earlier developments was the Google Voice Search function (2011). Voice Search is powered by various AI technologies, including speech recognition, natural language processing (NLP), and machine learning, which enable the tool to understand and respond to user queries in a natural way.
Since 2017, Google has also made it possible for users to search visually using Google Lens, or even across modalities — combining both images and text with multisearch. This is just further proof of their long-term commitment to leveraging AI advancements to enhance search.
Altogether, Google’s AI-powered solutions have enhanced search in a number of ways:
Chatbots are the prime example of conversational AI developments revolutionizing the digital landscape for both businesses and individuals. Whereas ChatGTP — the trailblazing bot created by OpenAI — is more widely known, Google is a close contender with its own chatbot-slash-AI-assistant, Google Bard.
According to Bard itself,
“Google Bard is powered by PaLM 2. PaLM 2 is a more advanced version of PaLM which was released in April 2022, and allows Bard to be much more powerful and efficient, perform at a much higher level, and fix previous issues.
PaLM stands for "Pathway Language Model". PaLM is a factual language model from Google AI, trained on a massive dataset of text and code. It can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative, human-like way. PaLM is still under development, but it has learned to perform many kinds of tasks, including
Bard advances the Google search experience further by offering users immediate personal assistance. Enhancing basic search engine capabilities, these developments make ‘Googling’ even more intuitive and user-friendly.
What also makes Bard different is that it’s based on a real-time updated Internet database — unlike ChatGPT, whose (free version) knowledge is limited to data published before 2021.
Search can’t get any easier than this, right?
One major issue with research is forming and asking the right questions.
Traditional search engines struggle in this aspect. For instance, classic Google simply searches for what you request (which is often not very concrete), sometimes adding a few synonyms, and then generates dozens of search engine result pages (SERPs) full of links. You then have to manually go through at least 1 or 2 webpages to identify and answer. This can quickly make the search process inconvenient and tedious.
However, with AI tools, a user can form their query as a full sentence and get the result they’re looking for without the need to visit other pages. This represents a major shift in the search process: we are transitioning from a “questioning” approach that uses keywords to a more conversational way of searching — one which offers users direct answers to their questions versus simply listing out links to webpages.
The value of generative AI bots like ChatGPT and Bard is that they not only facilitate specific query-based searches for users, but they have also started to offer recommendations.
Traditionally, users rely on the search results of the very first SERP to find what they need.
When ‘Googling’ something, most of us will select from the first 3 to 5 links to get the answers we’re looking for and make our conclusions and decisions. However, integrating generative AI in search can supercharge this process.
AI chatbots are able to understand not just the context of user questions and queries, but also the user. Their NLP capabilities enable them to provide customized results and answers in line with our preferences and interests. Consequently, AI reimagines relevance in search by shifting away from generic metrics, like page views and keywords, and focusing instead on delivering content that is truly valuable and reflective of every user.
While Google is at the forefront of these advancements, other search engines, such as the new Bing and DuckDuckGo, are also effectively incorporating AI into their systems — albeit through slightly different approaches. For instance, DuckDuckGo’s DuckAssist (powered by OpenAI) removes the ‘chat’ from ‘chatbot’: instead, it generates clear, cohesive, and complete answers to user queries — without the human-like learning and conversational element.
Google has access to the best data and data analysis methods available. But this hasn’t prevented issues in search result quality for users.
It’s widely acknowledged that search engine results are dominated by strategic keyword-loaded language, paid links, and sponsored content as companies compete to secure top positions in SERPs. However, this emphasis on search engine optimization (SEO) has compromised the authenticity of search results, potentially leading to a decline in the overall quality of search.
While Google is now aiming to reverse this trend, many sources have started to suggest alternative platforms like TikTok as the preferred search engine for younger Gen Z users. These individuals find more value in responses based on human opinion rather than SEO-influenced results that may fail to reflect the actual quality of webpage content.
By now, we can conclude that AI is actively shaping the search experience to fulfill Google's vision of ‘queryless search.’
It’s also becoming clear that the future of AI-powered search goes beyond just conversational, voice, and visual options. Instead, the focus is on leveraging AI to create a frictionless search experience — regardless of the method employed. The search engines that can help users make sense of the world in various ways, be it through text, images, voice, or any other means, will emerge as the leaders in this space.
While industry giants like Microsoft and Google continue to experiment with chatbots and other intelligent tools, other platforms are also introducing their own AI solutions. At the same time, users are starting to tailor their searches to different channels that cater to their specific needs and can offer more personalized results and answers.
TikTok, renowned for its content discovery capabilities, serves as a prime example of the potential for search in a diverse and fragmented content landscape. Platforms like Amazon (for products), YouTube (for tutorials and entertainment), and Reddit (for personal anecdotes and advice) each fulfill distinct search needs, further emphasizing the evolving nature of search.
In this dynamic environment, the prospects of a centralized search engine like Google may raise questions about its relevance and capabilities.
Ultimately, a truly satisfying search experience occurs when AI tools can anticipate user needs, providing relevant responses and recommendations, and even fulfilling desires that users may not have been aware of themselves.
And while discovery in the search process can be positioned as a positive feature, it often creates more work for users, who are obliged to evaluate results to get a clear answer. Search becomes more impressive when AI algorithms eliminate the burden of users having to act as their own digital librarians or curators.
In essence, the future of search engines lies in creating a personalized and intuitive search experience where AI-driven algorithms proactively understand and cater to user preferences and needs — going above and beyond their expectations.
As AI technology continues to progress and present new solutions, the future of search engines looks promising.
Generative AI and chatbots are transforming the search experience, crafting a highly personalized, conversational, and intuitive approach. By leveraging AI capabilities, search engines can produce relevant and reliable results while offering tailored recommendations based on individual preferences.
However, the future of search also entails its own set of challenges. The rise of platform-specific searches and the demand for more proactive search algorithms highlight a shift in users' expectations. To remain relevant, search engines must continually innovate, adapt to changing trends and demands, and strike a balance between personalization and privacy.
The future of search is now, and it is up to search engines to shape an information-rich landscape that meets and exceeds users’ continuously evolving needs.
If you’re interested in pursuing innovation to enhance your company’s strategy and improve operational excellence, don’t hesitate to reach out to us at hi@mad.co.
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