Recently, the traditional Internet search giant Google announced that its "Gemini" artificial intelligence (AI) model will integrate Google's search function. Subsequently, the Open Artificial Intelligence Research Institute (OpenAI) in the United States announced the official launch of ChatGPT's real-time search function. With the rapid development of AI technology, AI search engines have gradually become an emerging force in the field of information acquisition, providing users with more intelligent and personalized search experiences. Why are various companies deploying AI search? What is the difference between AI search and regular search? Can domestic search engines transform into AI? These are all issues of concern to people. With the breakthrough development of generative AI in 2023, AI tools are rapidly deployed in multiple fields, and search is one of them. AI search is not just a simple upgrade of traditional search engines, but a reshaping of the way information is obtained through technologies such as deep learning and natural language processing. The founder of the "Confusion" artificial intelligence company, Aravind Srinivas, describes it as an "answer engine" - when users ask questions, it provides a concise and clear answer, and all answers indicate their source, along with a series of associative questions, forming further interaction with users and expanding and extending related topics. Fu Xiaolan, Director of the Technology and Management Development Research Center at Oxford University and Fellow of the British Academy of Social Sciences, stated in an interview with reporters that AI search has reshaped the traditional keyword matching model through semantic understanding and deep learning technology. This significant change in the way information is obtained will enable AI search to play an important role in fields such as healthcare, law, finance, and startup valuation. Zhou Xiaopeng, Vice President of Alibaba's Intelligent Information Business Group, stated in an interview that the core value of search engines is to connect users with the information they are seeking. AI search has reshaped the way information is obtained, bringing the distance between users and information closer to zero. This is the core foundation for the broad prospects of AI search in the future. In addition, the characteristics of AI search technology determine that it can handle more complex queries, not limited to text, but also understand and index diverse content such as videos, images, and voice. This multimodal processing capability enables AI search to extract information from a wider range of data sources, providing users with richer and more accurate search results. At the same time, AI has also reshaped the product form of search, enabling AI writing, AI file summarization, etc., turning search from a tool into a versatile AI assistant. Facing the wave of AI search, traditional search engines are also upgrading to "AI" by introducing intelligent agents into traditional search. Rong Wei, the head of brand operations at Baidu Search, recently stated in an interview that intelligent agents are widely regarded as a promising direction for AI applications. According to the commonly used definition in the industry, an intelligent agent is a computer program that can interact with the environment, collect data, and use data to autonomously decide to complete predetermined tasks. Its biggest feature is autonomy - humans only need to give it an ultimate goal, and it can decompose the goal, obtain relevant data resources, and provide feedback results on its own. Therefore, it can complete more complex and fuzzy tasks, greatly enhancing the practical value of generative AI. Intelligent agents can largely be seen as an extension and upgrade of search engines. Before the birth of generative AI, people mainly relied on search engines to manually find answers - trying to search for a large amount of information sources using different keywords, in addition to referring to information on websites and communities. In the era of generative AI, search engines have become the central connectors of intelligent agents. Regarding the scenario of obtaining information, Zhou Xiaopeng stated that search is the entry point for users to initiate demands. In the face of complex problems, AI search can break down and infer user intentions, retrieve, analyze, and summarize information from the entire network, and generate and aggregate multimodal answers. Search results are not the goal, solving problems is the core. Therefore, AI search can provide richer content forms and interaction methods, evolving to some extent into AI assistants in various user scenarios. Privacy protection has become the focus of future development. Although AI search engines have shown broad market prospects, their development still faces many challenges. Data privacy and security issues are the focus of user attention, and how to protect user privacy while providing high-quality services will be an important issue that AI search engines need to address. Fu Xiaolan believes that privacy protection, technological compliance, and ethical issues all pose higher requirements for the development of AI search engines. In the future, with the continuous advancement of technology and changes in market demand, AI search engines are expected to achieve breakthroughs in more fields, bringing users a more intelligent and convenient search experience. Zhou Xiaopeng stated that security and compliance are the cornerstones for every product seeking greater development. AI products will inevitably encounter many new problems in the development process. Strengthening technical support, clarifying privacy policies, limiting data usage scope, and ensuring data compliance are the responsibilities that every practitioner should fulfill. He said, "In this process, multiple roles such as industry, academia, institutions, and government need to constantly communicate, constantly narrow cognitive differences, and reach consensus