中关村科金：不追风口，做ToB大模型价值落地的“深耕者”

Core Insights - The article highlights the paradox of high consumption and low returns in the AI industry, emphasizing that 95% of generative AI investment projects fail to deliver expected financial returns, with only 5% achieving commercialization [1][4] - Beijing Zhongguancun KJ Technology Co., Ltd. is positioned as a leading player in the enterprise-level AI model application market, having established a strong foothold by focusing on vertical applications rather than chasing trends [1][3][4] Market Dynamics - By mid-2025, the daily consumption of enterprise-level AI models in China is projected to reach 10.2 trillion tokens, equivalent to 46 billion 2,000-word articles, indicating a massive demand for AI solutions [1] - The article discusses the shift from a "technology showcase" era to a focus on "value realization" in AI, where deep engagement in vertical sectors is essential for successful AI integration [1][4] Company Strategy - Zhongguancun KJ's strategy began with a "reverse layout" in 2014, focusing on intelligent audio and video technology instead of mainstream computer vision, which has become a core asset for connecting businesses with customers [4] - The company has strategically chosen to concentrate on enterprise-level intelligent interaction scenarios, particularly in the smart customer service sector, which is seen as a critical entry point for large model applications [4][12] Competitive Position - In the latest IDC report, Zhongguancun KJ ranks fourth in the Chinese intelligent customer service market, leading among AI model companies [5] - The company’s approach emphasizes that the winners in the AI arms race will be those who can translate model capabilities into commercial value, rather than merely possessing the largest models [6] Implementation Framework - Zhongguancun KJ has proposed a "platform + application + service" three-tier engine strategy to accelerate the deployment of vertical AI models, addressing core issues of usability and effectiveness in enterprise applications [13][16] - The company aims to create a closed-loop system that activates enterprise data assets, integrates various AI capabilities, and continuously optimizes performance through iterative feedback [12][16] Industry Applications - The article provides examples of successful collaborations across various sectors, including finance, manufacturing, and infrastructure, showcasing how Zhongguancun KJ's AI models enhance operational efficiency and knowledge transfer [18][19][21][22] - Notable projects include a training platform for securities firms that improves training efficiency by 70% and a model for the shipbuilding industry that enhances intelligence analysis efficiency by 60% [19][21] Conclusion - The article concludes that the true value of AI lies not in the amount of computational power used but in the ability to understand and address industry-specific challenges, marking a shift from theoretical to practical applications in AI [25][26]