Introduction

Manufacturing is the foundation of a nation and the basis for its strength. General Secretary Xi Jinping emphasizes the importance of placing high-quality development of manufacturing in a more prominent position. As a strategic technology leading a new round of technological revolution and industrial transformation, artificial intelligence (AI) is evolving from a technical tool into a crucial engine for driving quality, efficiency, and power transformations in manufacturing. Leveraging AI in the transformation and upgrading of manufacturing from “Made in China” to “Intelligent Manufacturing in China” is an essential requirement for promoting high-quality development in the sector.

The Impact of Industrial Revolutions

Manufacturing is the main battlefield for the deep integration of technological and industrial innovation, as well as the primary carrier for producing key equipment and applying new technologies. On a global scale, all three industrial revolutions have driven the transformation and upgrading of manufacturing. The first industrial revolution led to the rise of machine manufacturing represented by steam engines and textile machinery. The second industrial revolution spurred the prosperity of modern communications, steel, oil, and automotive industries. The third industrial revolution birthed industries such as computers, the internet, and integrated circuits. Currently, the force of the new round of technological revolution and industrial transformation driven by AI is comparable to previous industrial revolutions, helping to fully empower high-quality development in manufacturing. AI has a strong spillover effect, widely applicable to industrial development, transforming technological variables into industrial increments.

AI’s Integration into China’s Manufacturing

China has a complete industrial system and strong comparative advantages in product manufacturing. The deep integration of AI technology in the industrial field has vigorously spawned a number of emerging high-end manufacturing industries. By 2025, the number of AI enterprises in China is expected to exceed 6,200, with the core industry scale surpassing 1.2 trillion yuan. Chinese companies have launched over 300 humanoid robots, accounting for more than half of the global total. Additionally, new generation intelligent terminals such as AI smartphones, computers, and smart manufacturing equipment are accelerating their global presence. By 2025, China’s smart watches and smart toys are expected to be sold in over 170 countries and regions. Moreover, AI, as a key enabling technology, can significantly promote the development of emerging manufacturing industries such as customized production, 3D printing, and biomanufacturing, reshaping the industrial form and development landscape of manufacturing.

Transformative Effects on Traditional Manufacturing

AI profoundly impacts traditional manufacturing through technology diffusion and industrial chain extension. On one hand, industries with high relevance to AI, strong synergy, and well-matched industrial chains are the first to undergo transformation and upgrading, even forming new paths for industrial development. Notable examples include the autonomous vehicle and drone industries. The traditional automotive industry has long relied on mechanical systems such as engines and gearboxes. With the empowerment of AI technology, the focus of the autonomous vehicle industry has shifted from engines to intelligent control systems, providing opportunities for “leapfrog” development in China’s automotive industry. Similarly, the drone industry has rapidly developed various applications such as logistics, performances, and low-altitude operations, forming a multi-industry integrated low-altitude economy. In the first two months of this year, the value added in the manufacturing of intelligent vehicle-mounted devices and intelligent unmanned aerial vehicles increased by 46.3% and 26.6%, respectively.

On the other hand, AI deeply empowers fields such as food processing, home appliances, and equipment manufacturing, continuously demonstrating its cost-reduction and quality-enhancing effects throughout the entire chain of research and development, production, and management. By 2025, the application rate of AI technology in large-scale manufacturing enterprises in China is expected to exceed 30%. With the solid promotion of the digital transformation of manufacturing, over 35,000 basic-level, more than 8,200 advanced-level, over 500 excellent-level, and 15 leading-level intelligent factories have been established in China.

The Depth of Intelligence Compared to Digitization

Compared to digitization, intelligence can be more deeply embedded in manufacturing. The application of digital technology focuses on promoting the informatization and platformization of transaction or circulation links, but it is challenging to apply in manufacturing processes such as collecting production data, directing production equipment, and controlling production processes. AI technology can achieve precise transformation and upgrading in key manufacturing areas such as production processes, equipment scheduling, and production assistance systems. For instance, AI technology is increasingly prominent in intelligent manufacturing and customized production, enhancing resource allocation efficiency in fields such as new material development, supply chain management, and inventory management.

Challenges and Future Directions

China has made significant progress in empowering manufacturing with AI, but it also faces some bottlenecks. One major advantage of developing AI in China is the abundance of application scenarios; however, there are constraints in the industrial ecosystem when empowering manufacturing with AI. Limitations in core technologies, raw materials, components, and high-quality training data hinder the implementation of AI in certain manufacturing scenarios. To develop AI-enabled manufacturing, it is essential to base this on intelligent devices and facilities, mapping and simulating the real world through the Internet of Everything. However, the construction of intelligent devices and facilities in China is relatively lagging, with insufficient support from infrastructure and equipment for the intelligent development of manufacturing. Existing general algorithms and computing architectures struggle to meet the growing demands for specialized scenarios and high-level computing, limiting the deep empowerment of AI in manufacturing. In the future, efforts to promote the transformation and upgrading of manufacturing through AI can focus on the following areas:

Building an Industrial Ecosystem for Deep Integration of AI and the Real Economy

A large-scale, clustered ecosystem is fundamental for continuously promoting the deep integration of AI and the real economy. It is crucial to further leverage the “leading goose” effect, tackle key technological shortcomings, and strengthen the efficient supply of computing power, algorithms, and data. Accelerating breakthroughs in key areas and promoting the development of industries with mature AI technologies, high industrial relevance, strong synergy, and substantial existing data accumulation, such as industrial robots, autonomous vehicles, and drone industries, is essential. Additionally, encouraging local development of AI industries tailored to specific regional conditions and continuously promoting industrial upgrades, inter-regional industrial transfers, and cross-regional industrial chain collaboration is vital.

Promoting the Intelligent Transformation of Manufacturing Equipment and Facilities

Focusing on key links such as research and development design, production manufacturing, quality inspection, and operation and maintenance services, it is important to accelerate the intelligent upgrading of production equipment, production lines, workshops, and factories. Promoting the application of technologies and equipment such as intelligent robots, smart sensors, digital twins, and flexible manufacturing will drive traditional production lines to transition towards automation, intelligence, and lean production, comprehensively enhancing production efficiency, product quality, and green safety levels. Enterprises should prioritize the intelligent transformation of high-energy-consuming and outdated “dumb equipment” to achieve real-time data collection and interconnectivity of key processes, introducing automated control systems to promote the transition of production processes from single-step automation to full-process intelligence.

Strengthening Safety Measures

It is essential to tackle key core technologies such as industrial software and intelligent sensors to build a self-controllable industrial safety barrier. Establishing a comprehensive AI safety risk prevention system, reasonably regulating AI software, computing facilities, and data resources, and encouraging manufacturing enterprises to conduct data security and algorithm model safety management certification are crucial. Exploring the deployment of “safety barriers” between AI models and industrial control systems, conducting third-party safety assessments on algorithms used in critical equipment and facilities, and effectively preventing production safety accidents caused by “AI hallucinations” are necessary measures. Extending cybersecurity governance from office management to industrial production, implementing round-the-clock risk monitoring of networked physical systems in production sites, and adhering to the principles of technology for good and collaborative governance will help establish a governance framework and policy system that adapts to the intelligent upgrading of manufacturing, ensuring a safe and controllable governance ecosystem to support the high-quality development of manufacturing empowered by AI.