Understanding China’s AI + Manufacturing Roadmap: Implications on FIEs

China’s AI + Manufacturing initiative is transforming production across sectors, enabling flexible, data-driven, and high-precision operations, with significant opportunities for both large firms and SMEs. Businesses that adopt AI, engage in local ecosystems, and leverage partnerships can gain efficiency, innovation, and competitive advantage in China’s evolving industrial landscape.

China is accelerating its integration of artificial intelligence (AI) into manufacturing as part of a sweeping national strategy to reshape its industrial base and climb the global value chain. The country’s AI industry, already valued at over US$70 billion with more than 4,300 companies, is expected to expand its core value to US$140 billion and boost related sectors to US$1.4 trillion by 2030.

Central government initiatives, such as the New Generation AI Development Plan and the push to cultivate “new quality productive forces” (新质生产力), have placed smart manufacturing at the forefront of policy priorities, supported by massive investments in infrastructure, data, and talent.

At the local level, Shanghai’s recently unveiled three-year “AI + Manufacturing” implementation plan offers a glimpse into how these national ambitions are being translated into actionable roadmaps.

The plan calls for accelerating the deployment of AI-powered robotics, digital twins, and intelligent quality inspection systems in industries such as new energy vehicles, aerospace, and biomedicine. Far from an isolated case, it reflects a broader transformation underway across China’s manufacturing hubs, where AI is expected to drive production optimization, predictive maintenance, and flexible, demand-driven factory models.

For foreign companies, it signals an evolving landscape where AI-powered industrial ecosystems will increasingly shape market access, competition, and partnership strategies.

What is  China’s “AI + Manufacturing” initiative?

China’s AI + Manufacturing initiative is a strategic effort to integrate AI into the country’s industrial base, transforming traditional factories into intelligent, flexible, and highly efficient production systems. It represents a convergence of digital technology, industrial modernization, and national economic planning, designed to move Chinese manufacturing up the global value chain.

At the heart of this strategy is the concept of dual empowerment: AI technologies enhance manufacturing productivity, precision, and innovation, while the manufacturing sector provides rich, real-world data and complex operational scenarios to refine AI capabilities. By embedding intelligence across production lines, supply chains, and R&D processes, China aims to create a new generation of “smart factories” capable of high-quality, customized, and resilient industrial output.

Key objectives include accelerating the adoption of AI-powered robotics, predictive maintenance, quality inspection, digital twins, and generative AI for design and development, particularly in high-value sectors such as automotive, aerospace, electronics, biomedicine, and green manufacturing.

This approach positions AI not just as a tool for efficiency but as a core driver of industrial innovation, competitiveness, and technological self-reliance.

Core components of AI + Manufacturing
China’s AI + Manufacturing is not merely automation. It integrates multiple AI technologies throughout industrial operations:

• Smart robotics: AI-driven robots perform repetitive, hazardous, or precision tasks in sectors like automotive, aerospace, and electronics. Initiatives such as Shanghai’s “robots with licenses” program ensure that robots meet safety and reliability standards before deployment.
• Predictive maintenance and analytics: AI analyzes sensor data from equipment to predict failures and optimize production schedules, reducing downtime and resource waste.
• Quality control and computer vision: Intelligent inspection systems automatically detect defects, enhancing product quality and reducing human error.
• Digital twins and simulation: Virtual replicas of production lines enable manufacturers to optimize workflows, simulate new processes, and train AI models without interrupting real-world operations.
• Generative AI in design and R&D: AI accelerates product design, testing, and innovation, enabling rapid prototyping and customization.

China’s roadmap for AI+Manufacturing development

China has adopted a three-tiered strategy for AI+Manufacturing development, combining a strategic roadmap, adaptive regulations, and multilevel implementation to ensure the technology supports long-term economic and industrial goals.

Made in China 2025, released in 2015, first positioned intelligent manufacturing as the key direction for modernizing the industrial base, encouraging the fusion of emerging technologies such as AI with traditional manufacturing. This was followed by the New Generation AI Development Plan in 2017, which elevated AI to the level of a national strategy, laying out a three-step roadmap to 2030 and emphasizing applications in critical areas including intelligent manufacturing.

During the 14th Five-Year Plan period, two further blueprints consolidated this direction: the 14th Five-Year Plan for Intelligent Manufacturing Development (2021), which aims to accelerate the adoption of AI, big data, and 5G across manufacturing processes to build a modernized smart manufacturing system; and the 14th Five-Year Plan for Digital Economy Development (2022), which stresses the deep integration of digital technology and the real economy, promoting applications such as smart factories, smart supply chains, and industrial AI.

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In addition, complementary regulations, such as the Interim Measures for Generative AI Services and pilot programs for intelligent connected vehicles, provide an enabling regulatory framework that supports innovation and lays the groundwork for AI’s application in industrial contexts. Beyond long-term strategic guidance, the Chinese government has rolled out concrete initiatives to accelerate the deployment of AI in manufacturing. The AI+ Action initiative, launched in 2024, explicitly identifies “AI+ Manufacturing” as a key priority.  It aims to harness cutting-edge tools such as large language models, machine vision, predictive maintenance systems, and intelligent control technologies to boost efficiency, quality, and resilience in industrial operations.

Meanwhile, policies around the industrial internet, led by the Ministry of Industry and Information Technology (MIIT), are promoting the development of platforms that help enterprises migrate to the cloud, make better use of data, and apply AI-driven insights to production and supply chain decisions. These efforts are designed to strengthen the digital infrastructure of China’s industrial economy and ensure that manufacturers of all sizes can access the benefits of AI.

Most recently, on August 26, 2025, the State Council issued a critical new policy, Opinions on Deepening the Implementation of the ‘Artificial Intelligence+’ Initiative”, deepening earlier efforts with granular targets, broad sectoral scope, and robust infrastructure support Government of China. Key highlights of the 2025 directive include:

• By 2027, AI integration across six key domains should exceed 70 percent in applications like next-generation smart terminals and intelligent agents.
• By 2030, this should climb beyond 90 percent, establishing intelligent economy as a major growth driver.
• By 2035, China aims to flourish as a fully intelligent economy and society

Regional policy: localized strategies and pilot-first experimentation

Under the guidance of national strategies, China’s local governments are advancing “AI + Manufacturing” in ways tailored to their industrial foundations and resource strengths. This approach has given rise to regional demonstration clusters, policy-driven “AI + Manufacturing highlands”, that not only align with national objectives but also showcase local best practices:

• Yangtze River Delta (Shanghai, Jiangsu, Zhejiang, Anhui): Shanghai is positioning itself as a benchmark city for intelligent manufacturing, developing an “industrial brain” powered by AI, building clusters of smart factories, and promoting AI applications in pillar industries such as automotive, integrated circuits, and biopharmaceuticals. Neighboring provinces Jiangsu and Zhejiang, with strong traditional manufacturing bases in textiles, home appliances, and machinery, focus on using AI for quality inspection, predictive maintenance, and intelligent scheduling—accelerating the smart transformation of established sectors.
• Guangdong-Hong Kong-Macao Greater Bay Area (GBA): Shenzhen, already China’s leading innovation hub, is pushing the boundaries of industrial AI, robotics, and intelligent hardware, supported by a vibrant ecosystem of startups and global manufacturing giants such as Huawei, DJI, and Foxconn. Guangzhou and Dongguan, both traditional manufacturing powerhouses, are steering industries like electronics, equipment, and molds toward smart, flexible production, cultivating intelligent industrial clusters.
• Beijing-Tianjin-Hebei region: Beijing leverages its research capacity and tech talent to drive R&D in core AI technologies, including algorithms, industrial software, and large models, while building smart manufacturing demonstration zones in areas such as Yizhuang. Tianjin and Hebei, benefiting from Beijing’s technology spillover, are applying AI to upgrade heavy industry and equipment manufacturing, strengthening regional industrial coordination.
• Central and Western China (Chongqing, Chengdu, Wuhan, Xi’an): Chongqing and Chengdu are focusing on AI applications in automotive and electronics, establishing pilot bases for intelligent connected vehicles and smart factories. Wuhan and Xi’an, home to leading universities and research institutes, are advancing integration in fields such as industrial AI, robotics, and high-precision manufacturing—making these inland cities important nodes in China’s intelligent manufacturing landscape.

Beyond regional focus areas, local governments are also investing heavily in pilot-first experimentation and financial support mechanisms. Many provinces and municipalities have launched special funds and subsidy programs to help enterprises implement AI-enabled upgrades, build smart factories, and establish industrial internet platforms.

Cities like Shanghai, Shenzhen, and Beijing have been designated as AI innovation pilot zones, where new applications are tested in industrial contexts before wider rollout. Additionally, a growing number of regions are running intelligent manufacturing pilot and demonstration projects, as well as competitions to recognize “smart factories” and “digital workshops.” These showcase examples serve as industry benchmarks, accelerating the spread of best practices across China’s manufacturing sector.

Shanghai as a model

Shanghai’s Implementation Plan for Accelerating the Development of AI + Manufacturing (hereinafter, the “plan”), released in August 2025, reflects the city’s commitment to translating China’s national AI and industrial strategies into concrete action. Also known as the “Molding Shanghai · AI + Manufacturing” initiative, the plan aims to position AI at the core of industrial transformation, fostering what policymakers describe as new quality productive forces. By aligning with national directives, Shanghai seeks to serve as a model for smart manufacturing adoption across China.

Three-year roadmap and key objectives

The plan sets out a three-year horizon from 2025 to 2027, establishing clear targets for intelligent manufacturing adoption. Shanghai intends to integrate AI solutions across 3,000 manufacturing enterprises, develop ten industry benchmark models, create one hundred benchmark smart products, and establish approximately ten model “AI + Manufacturing” factories.

In parallel, the city aims to cultivate a supporting ecosystem, including integrated and specialized service providers, to facilitate sustainable growth in intelligent manufacturing.

Focus on robotics and high-value sectors

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Industrial robotics is a central component of the plan, particularly through the “robots with licenses” initiative, which promotes certified deployment in high-risk, repetitive, or hazardous tasks. Priority sectors include biomedicine, aerospace, new energy vehicles, precision manufacturing, electronics, integrated circuits, shipbuilding, advanced materials, and steel.

The plan emphasizes scalable robotics deployment across production lines, including human-machine collaboration units for complex manufacturing processes.

Smart products and end-user innovation

Beyond industrial applications, the initiative encourages partnerships between AI developers and consumer terminal manufacturers to advance end products such as AI computers, smartphones, and wearable devices.

By enabling on-device AI model deployment and cloud-end integration, Shanghai seeks to foster industrial clusters around smart consumer electronics and enhance the city’s competitive edge in technology-driven markets.

Challenges and implementation considerations

While ambitious, the plan acknowledges several hurdles. Technical integration requires standardization of industrial protocols, miniaturization of edge devices, and integration of multimodal data. Data governance and sharing remain critical, alongside the need for high-quality industrial corpora. Costs, particularly for SMEs, necessitate supportive policy and financial measures. Safety and reliability, especially in industrial models and humanoid robotics, are emphasized to ensure responsible adoption and long-term sustainability.

All in all, Shanghai’s implementation plan not only demonstrates the feasibility of AI-driven manufacturing but also provides a template for replication across China.

Complemented by policy initiatives in Beijing, Shenzhen, and Hangzhou, the city serves as a testing ground for large-scale AI integration, highlighting the centrality of intelligent manufacturing to China’s broader economic transformation.

Implications for businesses

China’s AI + Manufacturing initiative is reshaping industrial competition, innovation, and operations, offering both opportunities and challenges for domestic and foreign firms. For domestic manufacturers, AI integration enables unprecedented productivity gains, operational efficiency, and precision across production lines.

By leveraging smart robotics, predictive maintenance, intelligent quality inspection, digital twins, and generative AI for design, companies can shift from rigid mass production to flexible, demand-driven manufacturing, meeting growing consumer demand for customized products.

High-value sectors such as automotive, aerospace, electronics, biomedicine, and green manufacturing stand to benefit most, gaining competitive advantages through AI-enhanced innovation and optimized industrial workflows.

For SMEs, the implications are particularly notable. While large corporations often lead AI adoption due to greater financial and technical resources, SMEs can leverage AI to compete through efficiency, specialization, and rapid innovation. AI-driven production optimization, intelligent quality control, and data analytics allow smaller manufacturers to reduce costs, enhance output quality, and respond quickly to market trends.

Platforms like Haier’s COSMOPlat demonstrate how SMEs can participate in industrial AI ecosystems, connecting with larger industrial networks and ecological partners to access digital capabilities that were once the preserve of larger firms. Nevertheless, SMEs face challenges related to the high upfront costs of AI deployment, technical integration, and data governance, which require supportive policies, financial incentives, and collaborative partnerships.

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For foreign companies, China’s AI-powered industrial transformation presents both opportunities and strategic considerations. International firms can participate by supplying AI technologies, collaborating with domestic manufacturers, or leveraging smart factory deployments to access real-world industrial data. However, they must navigate regulatory frameworks, compliance requirements, and safety standards, particularly around industrial robotics, AI governance, and data handling. Understanding local ecosystems, aligning with certified robotics programs, and engaging with AI innovation clusters are essential for successful market entry and sustainable partnerships.

In essence, businesses that embrace this transformation, by investing in AI capabilities, building strategic partnerships, and engaging with local industrial ecosystems, can achieve efficiency, scalability, and long-term competitiveness.