Artificial intelligence is evolving from a cutting-edge concept to a core driver of internal innovation among China's tech giants. Tencent's latest report, the "2025 Tencent R&D Big Data Report," reveals that AI has been deeply embedded in its vast R&D system, accelerating software development processes and significantly enhancing overall efficiency and product delivery speed, positioning itself as a key engine for the company's long-term competitiveness.

The most striking figure in the report shows that AI has become a daily work partner for Tencent engineers, with over 90% utilizing AI programming assistants. As a result, AI has contributed to 50% of the company's new code. This transformation has directly driven a more than 20% increase in overall R&D efficiency, with Tencent's R&D automation level improving by 67% year-over-year, saving an average of 5.3 million manual operations per month. This demonstrates that Tencent's sustained investment in AI is translating into business value.

Behind these advancements lies Tencent's substantial R&D investment and organizational scale. The report indicates that R&D staff comprise 76% of the total workforce at Tencent, meaning that three out of every four employees are engaged in research and development. For a company generating more than 325 million lines of new code monthly, the efficiency gains driven by AI translate directly to enhanced product iteration speed and market responsiveness, factors critical for investors assessing future growth potential.

AI Fully Integrated into R&D Processes, Enhancing Coding and Review Efficiency The report elaborates on how AI has permeated various stages of the software development life cycle. Supported by Tencent's self-developed Hunyuan large model, AI is not merely a supplemental tool but is actively involved in core tasks such as coding, code review, and testing.

Data shows that with AI assistance for 50% of new code, engineers have shortened their average coding time by 40%. This allows developers to focus more on creative and complex tasks. In terms of code quality control, the participation rate of AI is as high as 94%, acting as an "AI quality inspector." It conducts preliminary reviews before human engineers intervene, identifying and addressing 28% of code defects before manual review, which has increased the issue detection rate in code reviews by 44%, thereby building a robust first line of defense for software quality.

R&D Efficiency Platform Facilitates Automation Leap, Significantly Accelerating Delivery Speed The large-scale implementation of AI relies on the foundational R&D platform. The report notes that the WeDev efficiency platform has been deeply integrated into R&D practices, resulting in a 67% year-over-year increase in Tencent's R&D automation level, saving 5.3 million manual operations each month.

The efficient platform support has led to significant improvements in delivery speed. In 2025, Tencent completed an average of 16,000 demands per day, a 25% increase from the previous year, with average completion time reduced by 12 hours. Notably, the AnyDev cloud development platform has slashed the environment preparation time from one day to just one minute. In terms of code quality, the combination of automation tools and AI technology has resolved over 5.4 million code defects and security vulnerabilities throughout the year, with average bug resolution time reduced by eight hours, achieving "early detection and early resolution."

From WeChat to Gaming, AI Boosts Efficiency Across All Business Lines The efficiency gains brought by AI and platformization have been validated across Tencent's major business lines, translating to tangible business results. The report states that 81% of R&D teams have achieved full-process efficiency improvements by relying on the WeDev platform.

Specifically, the WeChat backend team has reduced compilation time by 50% through distributed compilation toolchains; the demand delivery cycle for WeChat Pay has shortened by 31%, with a 14% improvement in release quality. In Tencent's other major business area, gaming, the automation rate for art production has reached 95%.

Furthermore, 65% of the new code in Tencent Cloud comes from the AI code assistant, Codebuddy, resulting in a 31.5% decrease in average bug rates per thousand lines of code; the iteration efficiency for Tencent Advertising has doubled, with 90% of version releases achieving full-process automation.

Sustained High Investment and Open Source Strategy Highlight Technological Layout These R&D achievements are underpinned by Tencent's continuous high R&D investment and clear technological strategy. According to its Q2 financial report, R&D expenditure for the quarter reached 20.25 billion yuan, totaling 379.5 billion yuan in accumulated R&D investment since 2018.

Supporting Tencent's AI ecosystem is its long-term commitment to technology investment and an open strategy. The Hunyuan large model continues to iterate and fully embraces open source, with its image model, Hunyuan Image 3.0, securing first place in global user blind testing on the international model evaluation platform LMArena.

In terms of the external open-source ecosystem, Tencent’s open-source projects on GitHub have surpassed 520,000 stars, ranking among the top ten globally. The company has also contributed a variety of widely-used open-source tools, including the Tinker hotfix framework, WeTest automation testing platform, RapidJson parsing library, and Kona JDK.

Regarding programming language preferences, C++, Go, Python, and Java remain the mainstays of Tencent's R&D system. Go is extensively used in backend services due to its high performance and simple design, while Python has become the preferred language for AI and large model projects, reflecting the ongoing evolution of Tencent's tech stack.