Digital News

　　In August 2025, the State Council issued the Opinions on Deepening the Implementation of the “AI Plus” Initiative, highlighting the development of the “AI Plus” industry as one of the key initiatives. As a general-purpose technology, AI bears revolutionary significance in empowering high-quality development in an all-round manner and will serve as a key driver for fostering new quality productive forces and developing a modern industrial system. Overall, AI is poised to explore new frontiers in industrial development and to shape new development models of industries in the following three aspects.

　　First, leverage “AI Plus” to foster new models of future manufacturing. Historically, each wave of scientific and technological revolution has brought about disruptive changes in manufacturing methods. During the First Industrial Revolution, traditional handicraft workshops gradually evolved into factory-based production. Then the Second Industrial Revolution gave rise to large-scale assembly line operations. Today, the “AI Plus” initiative is leading a new wave of transformation, promoting production toward intelligence-driven models and deep integration of the digital and real economies. This shift is poised to bring about a qualitative leap in efficiency and fundamentally reshape production models across a wide range of industries. In design and planning, AI can integrate diverse resources, such as people, materials, knowledge, skills, and standards, to determine the “optimal solution,” thereby greatly enhancing production efficiency. In manufacturing, AI enables real-time monitoring and data analysis of equipment operating conditions, production status, and quality conditions, thus allowing for targeted process improvement and workflow optimization. In labor organization, AI can effectively make up for the limitations of human capabilities, such as insufficient strength, low endurance, poor stability, and limited environmental adaptability. It is capable of performing tasks that humans are unable to do (e.g., dangerous and hazardous work environments) or tasks that are unsuitable for humans (e.g., a large amount of tedious and repetitive work). The organizational model of “human–machine collaboration” will become the norm.

　　Second, leverage “AI Plus” to explore new scenarios of future consumption. Production plays a crucial role in shaping consumption. It not only defines specific consumption targets and shapes consumption patterns, but, more importantly, infuses sustained impetus into consumption. Notably, disruptive and innovative products often act as key “triggers” for initiating a new cycle of innovation. For example, the launch of the iPhone by Apple Inc. in 2007 revolutionarily pioneered the new era of smartphones. Today, the new generation of AI is fueling transformative changes in products such as smartphones, computers, automobiles, and home appliances, serving as a key engine to open a new chapter in the consumer electronics industry and revitalize the consumer market. Taking automobiles as an example, in the industrial era, cars had a single function, serving merely as a means of transportation. In the AI era, however, Intelligent Connected Vehicles (ICVs) have been upgraded into “intelligent agents” capable of seeing, hearing, speaking, driving, thinking, and learning. They serve as intelligent life “stewards,” and collaborate remotely with various smart home devices.

　　Third, leverage “AI Plus” to create new pathways for future innovation. As a general-purpose technology, AI acts as an “enabler for innovation,” providing opportunities for improving scientific R&D efficiency and fostering emerging industries. In the field of technological innovation, AI can identify patterns and generate knowledge from massive volumes of heterogeneous data. For example, a team at the Massachusetts Institute of Technology (MIT) used deep learning models to screen over 100 million compounds in just a few days to develop new antibiotics. With the empowerment of AI, the discovery of scientific and technological principles is evolving from an inference approach based on “formula + theory” toward one grounded in “parameters + algorithms.” In the realm of industrial innovation, AI will accelerate cross-disciplinary integration with cutting-edge fields such as biology, energy, and materials, leading to a collective surge of innovation. For example, AI can efficiently support all links of materials, including design, preparation, and characterization, greatly facilitating the discovery and application of new materials and injecting fresh vitality into industrial development.

　　Next, China should seize the opportunity and intensify efforts in promoting “AI Plus,” fully combining its technological advantages with the strengths of its enormous market and complete industrial system, thus creating a new quality productive force that drives the profound transformation and upgrading of industries.

　　First, accelerate the development of an “AI Plus” innovation ecosystem. By closely integrating a well-functioning government with an efficient market, China should build a “formation” where leading AI enterprises are dominant and small and medium-sized sci-tech companies spread widely, strengthening the entire process from technology R&D, product development, brand building, market promotion, to user services. This will establish a complete “hardware-system-industry” chain, creating benchmark new products and scenarios in fields such as industrial manufacturing, consumer services, scientific R&D, and urban governance, thereby systematically enhancing China’s overall influence in AI.

　　Second, establish a governance system adapted to “AI Plus.” New business forms are accompanied by their own growing “pains,” and AI faces issues such as the generation of false information, algorithmic bias, and data breaches. It is crucial to accelerate the improvement of a governance system that fits these new business models, governing AI for good and for all. On one hand, technology-based regulatory measures should be fully leveraged, using technology as a shield to address technology-driven harms. For example, developing intelligent detection tools to identify improper, harmful, or illegal AI-related content. On the other hand, institutional responses to new hotspots and issues arising from AI should be strengthened, with “agile governance” as the guiding principle, and rules regarding data, algorithms, data security, personal information protection, and intellectual property should be continuously improved.