The United States is at risk of losing its leadership in autonomous vehicles (AVs) as China rapidly advances in industrial capacity and deployment, according to a new report from the Special Competitive Studies Project (SCSP), a nonprofit and nonpartisan initiative focused on strengthening America's long-term competitiveness in artificial intelligence. The report, titled "The Autonomous Vehicle Crossroads," evaluates national competitiveness across five categories: innovation leadership, industrial capacity, market ecosystem, talent pipeline, and national leverage.
In innovation leadership, the U.S. maintains dominance with vehicles that set global standards for safety and reliability, and leads in software development, particularly in vision-language-action (VLA) models. However, China controls the physical layer of AVs, including supply chains and vehicle manufacturing capacity, and holds approximately 90% of the Light Detection and Ranging (LiDAR) remote sensing technology market, a critical component for autonomous driving.
The market ecosystem is essentially tied, with both countries receiving similar global funding for AVs. The U.S. holds the largest share, but China's aggressive globalization has fueled mass deployment. In talent, China produces significantly more engineering graduates with AV-relevant skills and integrates intelligent vehicle curricula into university systems, whereas the U.S. struggles to compete for a limited pool of skilled engineers.
National leverage gives China an edge due to strong state support and coordinated regulatory frameworks that promote faster large-scale deployment. In contrast, U.S. regulations remain a patchwork of inconsistent testing and development across states. The report warns that scaling of AVs will affect autonomous systems in other industries, including industrial robotics, smart infrastructure, and dual-use military systems, and notes that components and cars are increasingly sourced from China.
For a deeper dive into the U.S.-China strategic competition in autonomous vehicles, the full report is available at scsp.ai.
