“老登”应用，霸榜AI

Core Viewpoint - The AI application market is currently dominated by large companies, with a significant gap in the number of original AI applications developed by startups compared to established firms. The competition landscape shows that while AI applications are experiencing explosive growth, the majority of successful applications are still from major players in the industry [6][7][10]. Group 1: AI Application Landscape - The global AI application market has reached tens of thousands of applications, categorized into TOB (business-oriented) and TOC (consumer-oriented) segments [7]. - As of mid-2025, the top 20 AI applications in China are predominantly from large companies, with only about one-third originating from startups [7][10]. - The leading applications include Doubao, DeepSeek, and Quark, with most of the top applications being upgrades of existing products rather than entirely new offerings from startups [8][10]. Group 2: Challenges for Startups - Startups face significant challenges in the AI application space due to the dominance of large companies, which benefit from established user bases, brand recognition, and extensive distribution channels [22][24]. - The cost structure of AI applications, including high expenses for API calls and user acquisition, poses a barrier for startups, especially in a market where consumer willingness to pay for AI services is low [19][20]. - The competitive landscape has shifted, with large companies leveraging their existing products to integrate AI features, thus gaining a competitive edge over startups that must rely on "cold starts" to build user bases [23][24]. Group 3: Market Potential and Opportunities - Despite the challenges, the AI application market is still in its early stages, with significant growth potential as user engagement and monetization opportunities are on the rise [25][26]. - The technological advancements in AI, particularly in model capabilities, have lowered the barriers for startups, allowing smaller teams to develop functional AI applications more rapidly [27][28]. - Startups can find niches by focusing on high-frequency demand scenarios, ensuring user investment returns, and matching technical maturity with user tolerance for errors [29][30][31].