From tech breakthroughs to value creation: How AI is empowering China's manufacturing

As artificial intelligence (AI) moves beyond laboratory breakthroughs into large-scale industrial deployment, it is rapidly transforming China's manufacturing system across production, decision-making, human-machine collaboration and supply chain coordination.

Large-scale industrial application

Located in Guangzhou, south China's Guangdong Province, the smart eco-factory of China's GAC Aion New Energy Automobile operates more than 600 industrial robots across stamping, welding and assembly processes. In the final assembly workshop, vehicles pass through more than 200 processing stations, many of which are fully automated and operated entirely by robots. Every 53 seconds, a vehicle advances to the next workstation, which means that at the same interval a new car rolls off the line.

As a recognized "Lighthouse Factory," the plant integrates AI, big data, robotics, advanced process engineering, quality management and intelligent logistics systems, enabling more than 100,000 vehicle configuration options to meet customized demand at scale.

The transformation has delivered measurable gains: production efficiency has increased by 50%, delivery time shortened by 33%, first-pass yield improved by 8%, and manufacturing costs decreased by 58%.

Meanwhile, in Procter & Gamble's Huangpu factory in Guanghzou, technologies including AI, flexible automation and digital twin systems have been integrated into the supply chain operations, contributing to a 30% reduction in inventory and 15% in logistics costs, while maintaining a 99% on-time delivery over three years.

Flexible manufacturing

In China's Yangtze River Delta region, industrial AI is evolving toward higher flexibility and autonomy.

In a textile factory in Taicang, Suzhou City in east China's Jiangsu Province, over 500 air-jet looms have been connected to a centralized AI system that continuously monitors yarn tension, insertion speed and motor temperature. Through digital twin modeling and real-time optimization of 128 process parameters, fabric weight deviation has been controlled within 1.2%, while order response speed has been improved by 40%. The factory has also used AI to optimize its sizing process, cutting steam consumption by 300 kilograms for every tonne of yarn produced.

In advanced equipment manufacturing, SANY Group's heavy machinery smart factory in Kunshan has built a highly flexible production system, in which its AI-driven scheduling system decomposes global orders into thousands of process nodes, and allocates tasks across multiple production lines. Automated guided vehicles, connected to a cloud-based manufacturing execution system, automatically plan routes based on order priority. The factory even supports "one-unit order," with customization rates reaching 75% for mini excavators.

Expanding industrial intelligence

The impact of AI is extending beyond individual factories into broader industrial ecosystems.

According to China's Ministry of Industry and Information Technology (MIIT), by the end of 2025, more than 30% of manufacturing enterprises with annual revenue of at least 20 million yuan (about $3 million) had adopted AI technologies. Industrial intelligent agents covered over 70% of business scenarios in pioneer-level smart factories, accumulating more than 6,000 vertical domain models.

The MIIT, together with six other departments, recently issued an action plan to promote coordinated development among large, medium-sized and small enterprises in the platform economy from 2026 to 2028.

The platform economy is a new form of economy built on internet platforms.

The plan emphasizes strengthening innovation, ecosystem coordination, and openness across these enterprises, while deepening the integration of the real economy and the digital economy. It calls for greater openness in technology and data sharing, and encourages platform enterprises to strengthen AI innovation, improve algorithm governance and promote algorithm transparency.

By 2028, China aims to significantly improve the level of coordinated development among platform enterprises, form a number of replicable models for collaborative innovation, and cultivate a group of leading firms specializing in niche manufacturing segments in the platform economy.