创业邦·2025-12-11 10:15Core Insights - The article discusses the evolution of AI search engines, highlighting the shift from traditional link-based search to AI-driven solutions that provide direct answers and enhance user experience [3][4][6][12]. Group 1: Strategic Shift - Traditional search engines are experiencing a decline, with Google's global market share dropping below 90% for the first time in a decade [8]. - AI applications like ChatGPT and Perplexity are gaining traction, with ChatGPT reaching over 700 million weekly active users and covering about 10% of the adult population globally [8][12]. Group 2: Product Form - AI search engines are redefining user interaction through conversational interfaces, allowing for multi-turn dialogues and direct answers, which enhances the efficiency of information retrieval [14][15]. - The integration of multimodal capabilities enables AI search to process voice, images, and videos, expanding its application across various devices and contexts [15]. Group 3: Market Dynamics - The AI search market is diversifying into four evolutionary paths: traditional search engine upgrades, native AI search engines, ecosystem integration, and vertical service-driven solutions [20][21][23][24]. - The global search engine market is projected to grow from $204.76 billion in 2024 to $421.42 billion by 2031, indicating a compound annual growth rate (CAGR) of 11.0% [37]. Group 4: Value Chain Transformation - The demand for high-quality, structured data is increasing, leading to a revaluation of first-party data as a critical asset for AI training [27]. - Marketing strategies are shifting from Search Engine Optimization (SEO) to Answer Engine Optimization (AEO), focusing on making content more suitable for AI consumption [29][30]. Group 5: Future Outlook - The article emphasizes the need for a sustainable value distribution mechanism among platforms, brands, creators, and users to ensure long-term ecosystem prosperity [36]. - The transformation in search capabilities is driven by the necessity to address user needs more effectively, moving from mere information retrieval to actionable insights and solutions [35][37].