U.S. Leads in Robotics AI but Trails China in Deployment, Commission Says

WASHINGTON - The United States leads in robotics artificial intelligence and advanced research but lags China in factory automation, according to a new commission report warning that America's technological strengths are not translating into industrial capacity.

The National Security Commission on Robotics for Advanced Manufacturing released its preliminary findings Oct. 13. The commission, organized by the nonprofit Special Competitive Studies Project (SCSP), warns the U.S. could lose its edge in applied robotics. Its strengths - AI modeling, computer vision and robotics research - are not translating into manufacturing capacity.
The deployment gap is substantial. Per the International Federation of Robotics, China put in approximately 295,000 industrial robots in 2024 (54% of the global total), while the U.S. installed about 34,200. The difference remained in 2025: China ~354,000; U.S. ~38,500.

These numbers refer to classic factory robots - and don't indicate which country leads in humanoids or the newest AI-driven robots.

The commission's central worry is that U.S. leadership in intelligent robotics hasn't translated into similar growth in domestic manufacturing and adoption.

Why U.S. factories are behind in robot adoption

High equipment costs and complex integration needs are major obstacles. Many companies also lack the skilled workers to run automated systems, according to the commission.

Smaller manufacturers are particularly affected. About 95% of U.S. manufacturers are small or medium-sized and lack the capital and engineering resources to automate production.

Installing a robot is only part of the expense: manufacturers must modify production lines, integrate control software, establish safety procedures, and provide ongoing maintenance. Also, they won't adopt robots until they're cheaper, but developers need larger deployments to bring costs down.

Newer physical AI systems can enable robots to manage diverse tasks and reduce integration costs. But those improvements do not eliminate the financial and operational barriers to adoption.

The report also identifies fragmented federal oversight as robotics-related programs are spread across multiple agencies, while no single lead agency oversees deployment.

Why deployment matters for physical AI

Manufacturing statistics cannot capture the gap between developing robotics AI and deploying robots in real-world applications.

AI systems operating in physical settings need information about machine interactions with objects and varied environments. Unlike language models trained largely on digital information, robotic systems must learn how actions affect the physical world.

The commission says developers cannot access robot logs from real-world use. Fewer industrial deployments limit their access to real-world training data, systems’ assessments and robot performance improvements.

The fact that China has a larger stock of industrial robots does not necessarily indicate more advanced AI; however, a larger production base enables firms to automate operations and standardize equipment.
The commission also highlights supply-chain vulnerabilities. China dominates production of several components and materials used in advanced manufacturing, including permanent magnets needed for many electric motors.

For American robotics companies, developing competitive AI software is therefore only one of several hurdles. Commercial success requires reliable hardware, consistent component supplies, adequate manufacturing capabilities, and consumers willing to use new technology.

The preliminary report is an independent assessment. The commission will publish its final recommendations in March 2027.