The current industry consensus on whether AI can completely replace search engines is:In the short to medium term, AI is unlikely to completely replace search engines, but is more likely to be an evolutionary and fusion relationship.

AI is profoundly changing the way we obtain information, but the core functions of traditional search engines and AI models each have their own advantages and limitations.

The advantages of search engines:

1. Comprehensiveness and breadth:Traditional search engines can provide extremely extensive and comprehensive information sources by crawling and indexing the entire Internet (trillions of pages). They aim to help you discover new websites, articles, and perspectives.
2. Source transparency and verifiability:Search engines return a series of links that you can click on to enter the original website, verify the accuracy of information, view the author's background and publication date, which is crucial for tracing, conducting in-depth research, or evaluating the credibility of information.
3. Discovering new content:When you are unsure of what you are looking for, search engines can help you discover unexpected but useful information through keyword matching and relevance ranking.
4. Mature advertising model:Search engines have mature advertising monetization models that support their huge infrastructure and research and development investment.
5. Real time performance:Search engines can quickly index and display the latest published content.

The advantages of AI models (generative AI such as ChatGPT, Gemini, Copilot):

1. Direct answer and summary:AI can directly answer your questions and provide concise summaries without the need for you to click on multiple links for filtering and reading. This is very efficient for factual issues or scenarios that require a quick overview.
2. Understand complex intentions:AI excels at understanding complex queries, contexts, and user intentions in natural language, enabling multiple rounds of dialogue and providing more personalized and relevant answers.
3. Content generation and restructuring:AI can not only search for information, but also generate new content (such as drafts, code, ideas) based on existing information, or integrate, analyze, and restructure multi-source information.
4. Mission accomplished:Some AI models can assist in completing more complex tasks, such as planning travel, writing emails, analyzing data, etc.

Challenges and limitations of AI replacing search engines:

1. The problem of "hallucinations":AI models sometimes generate information that sounds reasonable but is actually incorrect or fictional. This is fatal in scenarios that require high accuracy, such as healthcare, law, and scientific research.
2. Timeliness:The training data for most large AI models is up to a certain point in time, which limits their ability to handle real-time news, latest research, emergencies, and other information, requiring additional real-time search capabilities.
3. Insufficient source transparency:Although some AI models have begun to attempt referencing sources, they often do not present all potential sources as clearly and intuitively as traditional search engines, and it is difficult to quickly verify the completeness and bias of their answers.
4. High cost:Running large-scale generative AI models requires enormous computing resources, and their unit query costs are much higher than traditional searches.
5. Lack of deep exploration:AI has strong summarization ability, but for scenarios where users want to conduct in-depth exploration, compare different viewpoints, and analyze raw data on their own, it cannot replace the user's experience of browsing multiple original web pages.
6. The challenge of advertising monetization model:AI directly provides answers, posing challenges to the traditional model of advertising placement and click through rate (CTR), which raises questions about its commercial sustainability.

Future Development Trends: Fusion and Evolution

Currently, what we are seeing is a deep integration of AI and search engines, rather than a simple replacement:

1. AI Enhanced Search Generative Experience (SGE):Google's "AI Overview" (formerly known as SGE) and Microsoft's Copilot (integrated into Bing) are typical examples. They provide AI generated summaries and answers on top of traditional search results, while retaining links to the original webpage. Users can quickly obtain a summary or click on the link to gain a deeper understanding.
2. Multimodal search:AI makes it possible to search through images, voice, and videos, and can understand more complex cross modal queries.
3. Personalization and predictability:AI can gain a deeper understanding of user preferences and historical behavior, provide more personalized search results and recommendations, and even predict the information that users may need.
4. Vertical AI Assistant:AI assistants targeting specific fields such as healthcare, law, programming, and travel planning may replace general search in these vertical areas, providing more professional and accurate services.

Conclusion:

AI will not "completely replace" search engines because the user needs and advantages of the two services are different. Search engines excel atDiscovery and breadthAnd AI excels atSummarization and Deep Understanding。

The future search experience is more likely to be an AI driven search engine that combines the advantages of both: AI serves as an intelligent assistant to help users quickly obtain information and understand complex concepts; As a vast knowledge base and information portal, search engines provide comprehensive and verifiable raw data and deep exploration paths. Users can flexibly choose whether they need an AI direct answer or a search result list containing multiple sources based on their own needs.