Su Po: Building a Batch of Leading Global Flagship Intelligent Factories to Drive Digital and Intelligent Transformation of Small and Medium-sized Enterprises

Special Topic: China Development Forum 2026 Annual Conference

The China Development Forum 2026 Annual Conference was held in Beijing from March 22 to 23. During the “Manufacturing Digital and Intelligent Transformation Seminar,” Su Bo, Vice Chairman of the National Strategic Advisory Committee for Building a Strong Manufacturing Nation and former Vice Minister of Industry and Information Technology, stated that through the in-depth implementation of intelligent manufacturing projects, China has achieved historic accomplishments in leading and promoting the construction of a strong manufacturing country. The country has successfully taken the first strategic step from being a major manufacturing nation to becoming a world manufacturing power. The overall manufacturing level has steadily risen from mid-to-low end, with many key sectors reaching mid-to-high end. Notably, fields such as 5G communications, high-speed rail equipment, shipbuilding, new energy vehicles, wind power, and solar power generation have reached world-leading levels, contributing 50% of global capacity.

He introduced that China’s smart factory construction has gradually expanded from pilot demonstrations to large-scale upgrades, significantly enhancing the comprehensive competitiveness of manufacturing. To date, over 35,000 basic-level, more than 8,200 advanced-level, over 500 excellence-level, and 15 leading-level smart factories have been built.

Su Bo emphasized that the digital transformation of manufacturing has fostered new technologies, new industries, and new business models, driving rapid development in manufacturing equipment, industrial software, and intelligent manufacturing system solutions, forming a market valued at five trillion yuan. Meanwhile, China has issued 497 national standards related to intelligent manufacturing, established over 500 undergraduate programs in smart manufacturing at higher education institutions, and deepened international exchanges and cooperation. These efforts provide solid standard support, talent assurance, and a foundation for international collaboration to facilitate the digital and intelligent transformation of manufacturing.

Regarding current industry development trends, Su Bo pointed out that the new generation of artificial intelligence is evolving from general large models to industry-specific large models. Industrial intelligent agents and embodied intelligence have become core variables in the digital transformation of manufacturing. These technologies, deeply integrated with advanced manufacturing, form a new generation of intelligent manufacturing technologies characterized by self-perception, self-decision-making, self-execution, self-adaptation, and self-learning, pushing intelligent manufacturing into a new stage of high-level development.

He clarified that in the next decade, China will continue to focus unwaveringly on intelligent manufacturing, which has been the core direction since the implementation of the manufacturing power strategy 15 years ago. The future will revolve around the deep integration of new-generation artificial intelligence with manufacturing, with innovation in intelligent manufacturing systems as the main focus and breakthrough point. Efforts will be made to address weaknesses in foundational industrial intelligent technologies, promote advanced exploration and widespread application, and strive to create an upgraded version of intelligent manufacturing that combines virtual and physical elements, is autonomous and evolving, and is safe and efficient. By 2030, large-scale manufacturing enterprises will generally adopt digital and networked manufacturing, with phased progress in new-generation intelligent manufacturing innovation; by 2035, most manufacturing enterprises will have achieved digital, networked, and intelligent manufacturing, with new-generation intelligent manufacturing applications leading globally.

To achieve these goals, Su Bo proposed four key tasks. First, strengthen strategic guidance, improve comprehensive promotion mechanisms, create new architecture and development pathways for intelligent manufacturing, and summarize regularities and effective experiences to support the upgrade. Second, promote innovation in intelligent manufacturing technologies and equipment, strengthen key core technology breakthroughs, and overcome multi-dimensional intelligent perception, industrial AI, factory operating systems, and other core foundational technologies to support system integration innovation and accelerate the development of a new generation of intelligent manufacturing technology systems, including the development of advanced intelligent manufacturing equipment.

Third, accelerate the exploration and cultivation of new business models and modes in intelligent manufacturing, promote graded and categorized construction of smart factories, create demonstration benchmarks, widely promote mature models and solutions, and popularize digital and networked manufacturing; support leading enterprises in applying deep learning, large models, digital twins, and other technologies to build a number of globally leading pilot smart factories, drive the digital and intelligent transformation of small and medium-sized enterprises, and cultivate new pathways for leapfrog development in intelligent manufacturing. Fourth, strengthen international cooperation, optimize the development ecosystem for intelligent manufacturing, continuously iterate national standards, deepen international exchanges and cooperation, actively promote the internationalization of smart factories, equipment, software, standards, and solutions, and enhance China’s international competitiveness and influence in intelligent manufacturing.

Disclaimer: All conference transcripts are compiled from on-site shorthand notes and have not been reviewed by speakers. The publication of this article by Sina is for the purpose of conveying more information and does not imply endorsement of its views or verification of its descriptions.

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Editor: Li Siyang