The text discusses the potential impact of AI on the search industry. Companies like Perplexity and You. com are emerging as next-generation search products, while Google and Bing are also investing in AI for search. However, the author argues that the real challenge for these new players is not just finding information, but also replicating all the functionalities that Google offers. The author conducted tests by inputting popular queries into various AI tools and found that while some AI bots provided useful information, they often took longer to deliver the results compared to Google. Additionally, AI search engines struggled with navigation queries, where Google excels at quickly providing the desired website.

For information queries, AI results were inconsistent, especially for real-time or location-specific information. However, AI tools performed well in answering buried information queries, where they were able to extract and present relevant information more efficiently than Google. Exploration queries, which involve a learning process rather than a straightforward answer, were better suited for AI search engines as they offered more in-depth responses and useful citations. Overall, the author concludes that while AI has potential, current AI search engines are too slow to replace the comprehensive and fast results provided by Google, especially in fulfilling the primary goal of search queries, which is to find a link or answer quickly.