AI Search
AI search is reshaping how information is accessed. Understanding the working principles, recommendation mechanisms, and brand display logic of mainstream AI search platforms helps brands precisely navigate the AI search ecosystem.
Last updated: 2025-06-01
Definition
AI search refers to information retrieval based on artificial intelligence technologies, particularly large language models and natural language processing. Unlike traditional search engines that return webpage links through keyword matching, AI search understands user intent, retrieves and integrates information from multiple sources, and generates natural language responses.
Background
AI search development has gone through two stages: AI enhancement of traditional search engines and independent AI-native search platforms. The launch of ChatGPT marked AI search entering the mainstream, followed by platforms like DeepSeek, Doubao, and Kimi, forming a diversified AI search ecosystem.
Why It Emerged
The rise of AI search stems from users' need for more efficient information access. Traditional search engines require users to browse multiple webpages and integrate information themselves, while AI search can directly provide integrated answers, greatly improving information access efficiency. Meanwhile, breakthroughs in LLM technology have made high-quality AI search possible.
How It Works
AI search systems typically contain three core modules: the retrieval module fetches relevant information from the internet, knowledge bases, and other sources; the understanding module uses LLMs to comprehend, verify, and integrate retrieved information; the generation module organizes integrated information into natural language responses. Brand information needs visibility in both retrieval and generation stages.
Applicable Industries
AI search is affecting information access across all industries. In consumer sectors, users get product recommendations through AI search; in education, students access learning resources through AI search; in healthcare, patients obtain health information through AI search. Brands need to pay attention to AI search's impact on their industries.
Examples
When a user asks "recommend a skincare product for sensitive skin," the AI search system retrieves multiple information sources including brand websites, professional reviews, and user comments, then synthesizes this information to generate a recommendation response. Brand performance across these sources directly determines whether it gets recommended by AI.