Group 1 - The integration of AI large models is driving new modes such as platform design, intelligent production, and personalized customization, while open-source AI technologies are lowering the barriers for enterprises to adopt intelligent solutions [1] - For large enterprises, the focus should be on leveraging industrial software to apply AI technologies, while for small and medium-sized enterprises, a "Model as a Service (MaaS)" approach is recommended to reduce the technical challenges of AI adoption [1] - The upgrade of industrial networks is crucial for the deep integration of AI and industry, with a policy goal to promote the transformation of at least 50,000 enterprises by 2028 [1] Group 2 - Future efforts should focus on innovating new industrial networks, building high-quality industrial data sets, and cultivating industrial intelligence, emphasizing real-time, deterministic, and secure network capabilities [2] - The establishment of innovation coalitions in key industries such as automotive and steel is necessary to create valuable industrial data sets and develop a multi-level application system [2] - The development of industrial intelligence should follow a step-by-step approach from device level to enterprise level, enhancing capabilities progressively [2]
政策密集发力 “工业互联网+AI”融合迈入新阶段
Xin Lang Cai Jing·2026-01-25 21:22