对话西门子中国董事长肖松：重塑产业新范式，AI的真正价值将在工业端充分释放｜CES 2026

Core Insights - The role of AI is evolving from mere model competition to practical applications in various industries, focusing on "last mile" implementations, with consumer AI targeting individual users and industrial AI emphasizing reliability and foundational skills [1][3] - Industrial AI is seen as a significant value driver, but it is still in its early stages, with increasing customer acceptance and potential for China to lead in application [3][4] - Siemens is recognized as a key partner in the industrial AI space, leveraging its extensive industry knowledge and data to drive transformation [6][11] Group 1: AI Evolution and Industrial Applications - AI is transitioning to become a true collaborative entity, focusing on practical applications rather than just model performance [1] - The true value of AI is expected to be realized in the industrial sector, with current applications still in the early stages of development [3][4] - Siemens emphasizes the importance of digital twin technology, which allows for the creation of virtual models that can enhance production efficiency and quality [5][9] Group 2: Siemens' Strategic Positioning - Siemens plans to invest €1 billion over the next three years to expand its industrial AI ecosystem, focusing on creating foundational models and collaborating with partners [6][14] - The company aims to leverage its historical expertise and high-quality data to lead the industrial AI revolution, addressing complex industry needs [6][11] - Siemens' digital twin composer is a significant innovation that integrates real-time data with virtual models, enhancing operational efficiency [5][9] Group 3: Market Trends and Future Outlook - The industrial AI market is characterized by its complexity and the need for tailored applications across different sectors, with Siemens advocating for a focus on application rather than just model parameters [14][15] - The company believes that AI will not replace human expertise but will enhance it, allowing experienced workers to define and make decisions rather than just operate [4][23] - The future of AI in industrial applications is expected to see incremental breakthroughs rather than radical changes, with a focus on quality improvement and cost reduction [24][27]