Li Auto Established “Computing Power Resources Division”

• Li Auto has restructured its tech organization, establishing a new “Computing Power Resources Division” led by Long Kaiwen.
• Remaining teams merged into a new “Enterprise Intelligence Division” under Shen Rong.

Li Auto has announced a major organizational restructuring within its System and Computing Group, establishing a dedicated “Computing Power Resources Division.” The new division will be headed by Long Kaiwen, former head of core systems development at Alibaba’s OS Business Unit, and is tasked with supporting the deployment of large AI models and the development of the company’s intelligent driving systems.

According to domestic media, the restructuring involved splitting and reorganizing the original “System Operations” and “Intelligent Cloud” units. The computing-related functions of the Intelligent Cloud division have been extracted to form the new “Computing Power Resources Division.” Remaining functions from both Intelligent Cloud and Enterprise Systems have merged into a new “Enterprise Intelligence Division,” led by Shen Rong, which will focus on user-facing performance development and the company’s broader digital infrastructure.

Computing power is increasingly seen as foundational to the future of smart vehicles. Under the leadership of CTO Xie Yan, Li Auto’s System and Computing Group now integrates core areas including operating systems, in-house chip development, cloud computing, and AI model technologies.

At the 2024 AI Talk event, CEO Li Xiang reaffirmed the company’s ambition to achieve L3 autonomous driving capabilities by 2025 and to reach L4 within three years. The latest structural shift is widely viewed as a proactive step to align technical resources and organizational focus with this roadmap.

Across China’s EV industry, the race for high-performance computing has become a central battlefield—particularly among Li Auto, XPeng, and NIO. XPeng recently introduced its self-developed Turing chips in the G7, focusing on the concept of “effective computing power.” NIO, meanwhile, has been equipping its vehicles with four Orin X chips since 2021 and recently debuted its proprietary Shenji chip in the ET9, delivering up to 2,000 TOPS in total. In addition, Huawei is also iterating rapidly, leveraging its MDC chip series and dense computing architecture as a strategic edge.

Against this backdrop, Li Auto’s creation of a “Computing Power Resources Division” reflects more than internal streamlining—it signals a deliberate bet on computing as a core competitive pillar. As large-scale AI models and advanced autonomous features become increasingly central to next-generation vehicles, the ability to organize and allocate computing resources efficiently is emerging as a key differentiator in the evolving automotive tech landscape.