Artificial research tools are advancing, yet their understanding of search engines is evolving.
By David Pierce, a prolific writer and co-host of Vergecast, boasting extensive experience in covering consumer technology across platforms like Protocol, The Wall Street Journal, and Plugged.
AI is poised to revolutionize the research landscape. The rise of platforms like ChatGPT, Google Gemini, and Microsoft Copilot signals a shift towards innovative ways of accessing information online. Companies such as Perplexity and You.com are at the forefront of this next-generation research wave. Meanwhile, industry giants like Google and Bing are placing their bets on AI to dominate the search realm. Farewell to the era of 10 blue links; welcome to a new era of precise answers to even the most obscure inquiries about our world.
Nevertheless, it is crucial to recognize that a search engine serves multiple purposes. While some users rely on Google for vital and intricate technological insights, a far larger audience uses it for everyday tasks like checking emails, visiting Walmart’s website, or recalling historical facts. Surprisingly, a significant number of people search for “google” on Google each month, highlighting its ubiquitous role beyond research. Despite being a go-to tool for research, Google is an integral part of billions of daily online interactions.
The pivotal question amidst the emergence of potential Google competitors is not just about information retrieval but about achieving Google’s versatility. To explore this further, I decided to evaluate the latest AI products firsthand by inputting them into various AI tools and analyzing the most searched questions and queries from the SEO research agency Ahrefs. While some AI-driven language models proved more insightful than a typical Google search results page, it became evident that dethroning Google from its web search supremacy, whether by AI or other means, would be a formidable challenge.
Enthusiasts of search engines categorize answers into three main types. The most common is navigational, where users input a website’s name to reach it quickly. Navigation queries dominate Google’s top searches, from “tube” to “wordle” to “internet email,” emphasizing the search engine’s primary function of directing users to websites.
When it comes to navigational queries, AI research tools lag behind Google. Google excels at swiftly providing the desired link, whereas AI algorithms tend to offer detailed information before presenting a hyperlink, causing delays in accessing direct links. This discrepancy underscores Google’s efficiency in delivering quick, relevant results.
The second prevalent type of query is informational, where users seek specific, factual answers such as sports scores or current time and temperature. While AI tools perform well in providing evergreen information like calendar details or event dates, discrepancies arise in accuracy and consistency. For instance, differing responses on the number of weeks in a year highlight the challenge of ensuring precise and reliable information retrieval across AI platforms.
Exploration queries, the third category, involve open-ended questions that initiate a learning process rather than yielding a single answer. AI search engines excel in handling such queries, offering in-depth insights and additional resources to facilitate exploration and learning.
One notable strength of AI engines is their ability to extract buried information efficiently. For complex queries like “How to screenshot on a Mac,” AI tools excel in extracting and presenting concise, relevant information without the clutter often found in search results pages.
In conclusion, while AI-powered tools show promise in enhancing search experiences, they currently fall short of Google’s comprehensive functionality. Google’s multifaceted approach, encompassing direct answers, interactive tools, and seamless navigation, sets a high bar for AI search engines to match. The future of search hinges not only on technological advancements but also on product innovation and user-centric design. As the search landscape evolves, the competition between AI-driven tools and established platforms like Google will continue to shape the future of online information retrieval.
