Today, people place as much trust in the answers provided by AI as they did in search engines two decades ago. However, this trust can be easily exploited, as demonstrated by the case of Putian-system hospitals, which once manipulated search engine results, leading to tragic consequences. So, is AI with internet search capabilities inherently more reliable than traditional search engines? The answer is a resounding no—AI's vulnerabilities are far more profound than we can imagine. Research indicates that while AI boasts a 10 to 30 percentage point higher accuracy rate than traditional search engines when answering health-related questions, and is capable of understanding symptoms described in everyday language and providing coherent responses, it still suffers from critical flaws. For instance, the quality of AI's answers is highly contingent on the prompts it receives; slight variations in wording can significantly alter the results. Moreover, AI may generate information that appears credible but is, in fact, inaccurate, as it relies on pre-existing training data rather than real-time information retrieval. When it comes to newly emerging health issues or the latest treatment guidelines, AI may lack the necessary updates due to gaps in its training data. Additionally, AI typically does not cite its information sources, making it difficult for users to verify the reliability of the information provided. On issues requiring specialized knowledge, such as rare diseases or specific treatment plans, AI's performance often falls short of that of traditional search engines. Therefore, both AI and traditional search engines have their respective strengths and weaknesses. The ideal approach is to leverage the strengths of both while maintaining a critical mindset.