Tencent (00700) first systematically disclosed R&D progress: AI generates 50% of new code, R&D automation level increases by 67% year-on-year.

Artificial intelligence is evolving from a cutting-edge concept into a core force driving internal innovation at Chinese tech giants. Tencent (00700) recently released its "2025 Tencent R&D Big Data Report," showing that AI has been deeply embedded in its vast research and development system, not only accelerating the software development process, but also significantly improving overall efficiency and product delivery speed, becoming a key engine for this tech giant to maintain long-term competitiveness. The most notable data in the report is that AI has become the daily work partner of Tencent engineers. Over 90% of engineers are using AI programming assistants, and 50% of the company's new code is generated with AI assistance. This transformation has directly driven an overall research and development efficiency improvement of over 20%, with Tencent's research and development automation level increasing by 67% year-on-year, saving 5.3 million manual operations per month. This shows that Tencent's long-term investment in AI is accelerating the transformation into business value. Behind these advances is Tencent's large research and development investment and organizational scale. The report shows that research and development personnel account for 76% of Tencent's total employees, meaning that three out of every four employees are engaged in research and development work. For a company that adds over 325 million lines of new code per month, the efficiency gains brought by AI mean a direct enhancement of product iteration speed and market responsiveness, which is crucial for investors to assess its future growth potential. AI fully integrated into the research and development process, dual efficiency improvement in coding and review The report details how AI penetrates various aspects of the software development lifecycle. With the support of its self-developed Meta-model, AI is no longer just an auxiliary tool, but deeply involved in core tasks such as coding, code review, and testing. Data shows that with 50% of new code completed with AI assistance, engineers' average coding time has been reduced by 40%. This means that developers can focus more on creative and complex tasks. In terms of code quality control, AI's involvement is as high as 94%, playing the role of an "AI inspector." It conducts pre-reviews before human engineers intervene, directly identifying and remedying 28% of code defects that are then adopted for fixing, leading to a 44% increase in the detection of significant issues during code review, building a first line of defense for software quality. Research and development platform supports automated leaps, significant acceleration in delivery speed The large-scale implementation of AI relies on the underlying support of research and development platforms. The report points out that with the in-depth integration of the WeDev research and development efficiency platform, Tencent's research and development automation level increased by 67% year-on-year, saving 5.3 million manual operations per month. Efficient platform support has led to a significant improvement in delivery speed. In 2025, Tencent completes an average of 16,000 requirements per day, a 25% year-on-year increase, with an average reduction of 12 hours in completion time. The AnyDev cloud research and development platform has significantly reduced the environment preparation time from a day to 1 minute. In terms of code quality, the combination of automated tools and AI technology has repaired over 5.4 million code defects and security vulnerabilities throughout the year, with an average reduction of 8 hours in bug resolution time, achieving "early discovery, early resolution." From WeChat to games, AI empowerment enhances all-line businesses The efficiency gains brought by AI and platformization have been validated across Tencent's major business lines, translating into tangible business results. The report states that 81% of R&D teams have achieved end-to-end efficiency improvement by leveraging the WeDev platform. Specifically, the WeChat backend team reduced compilation time by 50% through a distributed compilation toolchain; WeChat Pay shortened its demand delivery cycle by 31% and improved release quality by 14%. In Tencent's other major business pillar, the gaming sector, the automation rate of artistic production has reached 95%. At the same time, 65% of the new code on Tencent Cloud comes from the AI code assistant Codebuddy, reducing the average per person bug rate by 31.5%; Tencent's advertising iteration efficiency has doubled, with 90% of version releases achieving end-to-end automation. Continued high investment and open-source strategy highlight technological deployment Behind these research and development achievements is Tencent's continuous high investment in research and development and a clear technological strategy. According to its second-quarter financial report, the company's R&D investment in the quarter reached 20.25 billion yuan, and since 2018, cumulative R&D investment has totaled 379.5 billion yuan. Supporting Tencent's AI system is its long-term technical investment and open strategy. Tencent's Meta-model continues to iterate and fully embraces open source. Its image model "Meta-image 3.0" ranked first in blind tests by global users on the international big model evaluation platform LMArena. In terms of external open-source ecosystems, Tencent's open-source projects on GitHub have accumulated over 520,000 stars, ranking in the top ten globally. The company has contributed a series of widely used open-source tools, including the Tinker hotfix framework, WeTest automated testing platform, RapidJson parsing library, and Kona JDK. In terms of programming language preferences, C++, Go, Python, and Java remain the mainstays of Tencent's research and development system. Go language is widely used in backend services for its high performance and concise design, while Python has become the preferred language for AI and big model projects, reflecting the continuous evolution of Tencent's technology stack.