The AI wave is rapidly propelling a new generation of young entrepreneurs and scientists to the center stage. Tech giants from the traditional internet era are now casting their nets wide, eagerly extending olive branches to the youth. Late last year, global tech behemoth Meta acquired Manus, a company founded by Chinese entrepreneurs born in the 1990s; more recently, Tencent officially announced the appointment of 27-year-old former OpenAI researcher Yao Shunyu (Vincesyao) as its Chief AI Scientist. As the global AI competition enters a critical phase, Tencent is signaling an acceleration in its AI efforts, aggressively competing for top-tier AI talent while simultaneously restructuring its AI-related organizational framework to enhance team effectiveness. It has been learned that Tencent's AI Lab, under the TEG (Technology and Engineering Group), recently underwent an organizational restructuring. Furthermore, due to personal career reasons, Yu Dong, the former Deputy Director of Tencent AI Lab, will be leaving the company shortly. Throughout this round of AI competition, compared to the aggressive, high-profile strategies of Alibaba and ByteDance, Tencent has consistently projected an image of patience. This perception was particularly reinforced in the third quarter of this year when Tencent's capital expenditures amounted to approximately RMB 12.98 billion, a decrease of 24% year-on-year and about 32% quarter-on-quarter, signaling a cautious approach to AI investment. However, a series of recent moves involving AI team reorganizations and talent acquisition indicate that Tencent's AI initiatives are quietly gaining momentum. It is understood that Yu Dong joined Tencent in 2017, serving as a Distinguished Scientist, Deputy Director of Tencent AI Lab, and Chief Scientist of Tencent YouTu Laboratory. An expert in speech processing and deep learning, Yu was one of the pioneering research leaders who first successfully applied deep learning techniques to the field of speech recognition. During his tenure at Tencent, Yu led research teams that published hundreds of papers in top-tier academic conferences and journals, and he also drove the application of NLP, speech, and digital human-related technologies within Tencent's business operations. As Tencent presses the accelerator in the AI race, frequent organizational and personnel changes are becoming inevitable. The singular goal behind all these moves is to ensure Tencent maintains a stable position at the competitive table. Since the beginning of this year, Tencent has conducted multiple organizational adjustments related to its AI business. Early on, it consolidated AI products and applications like Tencent Yuanbao, QQ Browser, Sogou Input Method, and ima into the CSIG (Cloud and Smart Industries Group). Then, in April, the TEG established new departments dedicated to Large Language Models and Multimodal Models. On the same day it announced Yao Shunyu's appointment, Tencent also revealed an upgrade to its large model R&D architecture. The TEG newly established an AI Infra Department, an AI Data Department, and a Data Computing Platform Department to comprehensively strengthen its large model R&D system and core capabilities. Following these adjustments, the organizational structure of Tencent's AI teams has become more clearly defined for external observers. The core leadership for Tencent's current AI R&D efforts now centers around Yao Shunyu and Tencent Senior Vice President Jiang Jie. Reports indicate that Yao Shunyu assumes the role of Chief AI Scientist within the "CEO/President's Office," reporting to Tencent President Martin Lau; concurrently, he serves as the head of both the AI Infra Department and the Large Language Model Department, reporting to TEG President Lu Shan. Wang Di continues as Deputy General Manager of the Large Language Model Department, reporting to Yao Shunyu. This streamlined reporting structure is undoubtedly beneficial for enhancing Tencent's AI R&D efficiency, unifying the feedback loop between model training and application development, and accelerating the iteration of AI products. Additionally, Liu Yuhong serves as head of the AI Data Department, and Chen Peng heads the Data Computing Platform Department, both reporting to Jiang Jie. Jiang Jie joined Tencent as early as 2012. As a Vice President of the Tencent Corporate Development Group, he oversees the management of Tencent's advertising platform product technology; he also holds the position of TEG Vice President and is the head of Tencent AI Lab. Analyzing the primary missions of each department reveals that the AI Infra Department, a crucial component of Tencent's large model ecosystem, will be responsible for building the technical capabilities of the large model training and inference platforms, providing stable and efficient technical support and services for algorithm R&D and business scenario implementation. The AI Data Department and the Data Computing Platform Department will focus on constructing the large model data and evaluation system, and developing the data intelligence fusion platform for big data and machine learning, respectively. An internal Tencent source revealed that this upgrade of the large model R&D architecture aims to further strengthen Tencent's engineering advantages while enhancing its large-scale AI model research capabilities, focusing the company's AI strategic layout, and improving the efficiency of AI model development. Tencent AI Lab, the entity most recently involved in organizational changes, was established in 2016, focusing on fundamental AI research in areas like computer vision, speech recognition, natural language processing, and machine learning. During that phase, AI was largely viewed as a technological reserve rather than a plug-and-play productivity tool. Success was often measured by the number of papers in top conferences, rankings on competition leaderboards, and isolated breakthroughs in specific scenarios. Nearly three years after the surge of large AI models began, global competition has intensified dramatically. By 2025, the Chinese AI battlefield has evolved from a battle over model parameters into a comprehensive contest involving capital efficiency, infrastructure, and access to user traffic. Even if Yu Dong's departure is a personal choice, it reflects a broader reality: AI talent is accelerating its mobility, and the entire industry is undergoing a significant reshuffling of technology, capital, and human resources. To emerge victorious in this global AI race, talent is arguably the most critical competitive advantage. Consequently, Tencent is compelled to recruit more AI talent. On April 17, Tencent announced its largest-ever employment initiative, planning to add 28,000 internship positions over three years with increased conversion rates to full-time roles. For 2025 alone, it aims to welcome 10,000 campus recruitment interns, with sixty percent of these positions open to technical talent. Tencent stated that against the backdrop of accelerating large model deployment, it has significantly increased hiring for technical roles in artificial intelligence, big data, cloud computing, game engines, and digital content, with an unprecedented scale of expansion for technical positions. On June 12, targeting top technical students globally, Tencent launched the "Qingyun Plan," focusing on cultivating talent in ten key frontier technology fields. More recently, reports surfaced that Tencent has been offering double salaries to top researchers from ByteDance's AI department, successfully recruiting some key personnel. This has notably reversed the previous trend of talent flow favoring ByteDance's recruitment efforts. At this three-year mark, internet giants like Tencent, Alibaba, and ByteDance have become the focal seed players in the current AI arena. However, their chosen strategic paths for AI development are markedly different. Alibaba has opted for heavy asset investment, aggressively pursuing growth in enterprise market share while pushing comprehensively into consumer AI applications. ByteDance has chosen a strategy of breaking through via its massive user traffic, using application success to fuel its underlying infrastructure development. Recently, both Alibaba and ByteDance garnered attention for their heavily promoted apps, Qianwen and Doubao Mobile Assistant, respectively. In contrast to Alibaba and ByteDance, Tencent has maintained its characteristic restraint in AI strategy, preferring to integrate large model capabilities deeply within its vast ecosystem. This approach has, however, led to external perceptions of Tencent "falling behind." In the three-way competition with Alibaba and ByteDance, whether Tencent can introduce more powerful AI products next year will be crucial to reversing this narrative.
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