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Siemens: Unlocking a “New Intelligent Growth” Path for Manufacturing with the Real Value of Industrial AI
At present, the practical value of AI technology in industrial scenarios has become the focus of attention in the manufacturing sector. At this year’s China International Industry Fair (CIIF), manufacturers’ interest in AI reached a new high. Unlike in previous years, users are no longer merely curious about the technology, but are more focused on what specific problems AI can solve and how long the return on investment cycle will be. This shift from “watching the excitement” to “real implementation” marks the transition of industrial AI from proof-of-concept to large-scale application.
In this exploration of the practical value of industrial AI, Siemens—presenting under the theme of “Digital-Real Integration, New Intelligent Growth”—undoubtedly became a central highlight of the CIIF. As a pioneer and innovation driver in industrial AI applications, Siemens not only showcased nearly 20 AI-related products and solutions covering the entire value chain of design, manufacturing, and operations, but also—relying on proven digital-real integration capabilities, deep industry expertise, and high-quality data from industrial sites—provided a clear path for overcoming the challenges of AI implementation in manufacturing.
In this exploration of the practical value of industrial AI, Siemens—presenting under the theme of “Digital-Real Integration, New Intelligent Growth”—undoubtedly became a central highlight of the CIIF. As a pioneer and innovation driver in industrial AI applications, Siemens not only showcased nearly 20 AI-related products and solutions covering the entire value chain of design, manufacturing, and operations, but also—relying on proven digital-real integration capabilities, deep industry expertise, and high-quality data from industrial sites—provided a clear path for overcoming the challenges of AI implementation in manufacturing.
Breaking Down Implementation Barriers to Release the Real Value of Industrial AI
To truly implement industrial AI, the first step is to accurately match the real needs of manufacturers. At this year’s CIIF, Siemens exhibited nearly 20 AI-related products and solutions, along with real-world case studies of industrial AI deployment in sectors such as metal smelting, hydrogen energy, and energy management. The industrial AI showcase area addressed key pain points from technical support to production operations:
Knowledge management, Q&A, and retrieval: Siemens’ AI assistant, based on its knowledge base, provides more professional, reliable, and accurate answers, avoiding the awkwardness of generic AI giving irrelevant responses.
Automation engineering development environment: For example, the AI assistant embedded in the TIA Portal engineering environment can now generate PID control programs directly from AI, eliminating the need to write PLC code line by line, and can even automatically verify the correctness of the code.
Process optimization in factory operations: AI transforms “master craftsman experience” into replicable data models, identifying patterns by integrating massive production data.
Wang Haibin, Executive Vice President of Siemens Ltd., China and General Manager of the Digital Industries Division, Greater China, explained that AI can be broadly or narrowly defined. Broad AI refers to computers performing human-like thinking, such as binary operations; narrow AI breaks through the limitations of traditional algorithms to solve tasks that were previously inefficient or impossible for humans—such as code generation and process optimization in industrial scenarios.
Currently, one of the biggest barriers to industrial AI adoption is the interdisciplinary threshold. Enterprises need not only industry and process knowledge, but also data science and IT capabilities. The shortage of cross-disciplinary talent discourages many companies from adopting AI. To address this, Siemens reduces the difficulty of industrial AI application by lowering the usage threshold and building an ecosystem. For example, by acquiring the Mendix low-code application development platform, Siemens enables engineers who understand processes to generate applications without IT knowledge. The Altair RapidMiner enterprise data analysis and AI platform includes thousands of pre-built models and can intelligently find and train models, reducing the difficulty for industrial customers to use AI for data modeling. Additionally, through the open digital business platform Siemens Xcelerator, Siemens has connected 530,000 users in China and brought together over 300 ecosystem partners—more than 60% of whom are AI-related—building an open and win-win innovation ecosystem.
As Dr. Xiao Song, Global Executive Vice President and Chairman of Siemens China, stated: “The real implementation of industrial AI begins with accurately capturing demand scenarios and succeeds through deep integration of technology, data, and industry mechanisms. This is where Siemens excels—awakening dormant data with deep industry know-how and working with ecosystem innovation partners to help thousands of Chinese industrial enterprises reap the real value and benefits of industrial AI.”
Notably, at this year’s CIIF, Siemens and Zhongke Moton jointly unveiled a new generation of intelligent assembly equipment for new energy vehicles (EMB). As the first pilot in China of Siemens’ generative industrial AI assistant, Industrial Copilot, the equipment answered enterprises’ most pressing questions about AI application value with visible and calculable data.
During equipment debugging, Industrial Copilot assisted engineers in developing automation programs, significantly reducing repetitive work, improving development efficiency, and minimizing production losses caused by incorrect equipment operations. Combined with Siemens’ standardized solutions and robot libraries, Industrial Copilot helped Zhongke Moton reduce program development time by 30%, shorten on-site debugging cycles by 30%, and cut labor and material losses by 10%, fully demonstrating the real value of industrial AI in complex manufacturing environments.
Knowledge management, Q&A, and retrieval: Siemens’ AI assistant, based on its knowledge base, provides more professional, reliable, and accurate answers, avoiding the awkwardness of generic AI giving irrelevant responses.
Automation engineering development environment: For example, the AI assistant embedded in the TIA Portal engineering environment can now generate PID control programs directly from AI, eliminating the need to write PLC code line by line, and can even automatically verify the correctness of the code.
Process optimization in factory operations: AI transforms “master craftsman experience” into replicable data models, identifying patterns by integrating massive production data.
Wang Haibin, Executive Vice President of Siemens Ltd., China and General Manager of the Digital Industries Division, Greater China, explained that AI can be broadly or narrowly defined. Broad AI refers to computers performing human-like thinking, such as binary operations; narrow AI breaks through the limitations of traditional algorithms to solve tasks that were previously inefficient or impossible for humans—such as code generation and process optimization in industrial scenarios.
Currently, one of the biggest barriers to industrial AI adoption is the interdisciplinary threshold. Enterprises need not only industry and process knowledge, but also data science and IT capabilities. The shortage of cross-disciplinary talent discourages many companies from adopting AI. To address this, Siemens reduces the difficulty of industrial AI application by lowering the usage threshold and building an ecosystem. For example, by acquiring the Mendix low-code application development platform, Siemens enables engineers who understand processes to generate applications without IT knowledge. The Altair RapidMiner enterprise data analysis and AI platform includes thousands of pre-built models and can intelligently find and train models, reducing the difficulty for industrial customers to use AI for data modeling. Additionally, through the open digital business platform Siemens Xcelerator, Siemens has connected 530,000 users in China and brought together over 300 ecosystem partners—more than 60% of whom are AI-related—building an open and win-win innovation ecosystem.
As Dr. Xiao Song, Global Executive Vice President and Chairman of Siemens China, stated: “The real implementation of industrial AI begins with accurately capturing demand scenarios and succeeds through deep integration of technology, data, and industry mechanisms. This is where Siemens excels—awakening dormant data with deep industry know-how and working with ecosystem innovation partners to help thousands of Chinese industrial enterprises reap the real value and benefits of industrial AI.”
Notably, at this year’s CIIF, Siemens and Zhongke Moton jointly unveiled a new generation of intelligent assembly equipment for new energy vehicles (EMB). As the first pilot in China of Siemens’ generative industrial AI assistant, Industrial Copilot, the equipment answered enterprises’ most pressing questions about AI application value with visible and calculable data.
During equipment debugging, Industrial Copilot assisted engineers in developing automation programs, significantly reducing repetitive work, improving development efficiency, and minimizing production losses caused by incorrect equipment operations. Combined with Siemens’ standardized solutions and robot libraries, Industrial Copilot helped Zhongke Moton reduce program development time by 30%, shorten on-site debugging cycles by 30%, and cut labor and material losses by 10%, fully demonstrating the real value of industrial AI in complex manufacturing environments.
Boosting Efficiency Across the Full Value Chain to Break the “Involution” Dilemma
While accelerating the integration of industrial AI, manufacturers face another challenge—“involution” (intense internal competition)—which also requires technology-driven optimization across the full value chain to resolve. Currently, China’s manufacturing sector is grappling with diverse market demands, rising operating costs, and shrinking profit margins, forcing companies to seek new growth points. Zhang Jingsong, Head of Sales for Siemens’ East China Region, observed that many enterprises are beginning to look overseas to expand market share and find new growth opportunities. At the same time, improving production equipment efficiency and productivity across the entire value chain has become a consensus for coping with involution.
With a comprehensive portfolio of hardware and software products covering the entire industrial lifecycle and proven “digital-real integration” capabilities, Siemens helps customers achieve “right-first-time” across six dimensions: design, selection, debugging, manufacturing, operations, and low-carbon transformation—providing a path to break the involution cycle.
Design: Using Siemens NX MCD virtual simulation technology to shorten design cycles by 30%, improve change efficiency by 50%, and avoid rework costs.
Selection: Through the Siemens TIA Portal selection tool, automatically match hardware parameters, saving 80% of selection time and reducing procurement costs by 10%.
Debugging: Siemens Industrial Copilot assists in generating and automatically verifying PLC code, cutting on-site debugging time by 30% and reducing labor and material losses by 10%.
Manufacturing: The TIA fully integrated solution drives the SINAMICS S200 servo system, doubling production efficiency and increasing test pass rates by 30%.
Service: SIMICAS predictive maintenance can warn of failures 72 hours in advance, reducing unexpected downtime by 40%.
Low-carbon: The Smart ECX intelligent energy and carbon management platform helps enterprises measure carbon emissions and achieve green production.
As Wang Haibin stated: “Although involution is widespread, opportunities to break through are everywhere. When enterprises re-examine cost structures, operational efficiency, and innovation speed from a holistic perspective, they will find many areas for optimization—this is where Siemens works hand-in-hand with customers.”
Siemens’ digital industries divisions are collaborating to continuously launch innovative products tailored to the Chinese market. For example, the “Dazzling Heart 2.0” exhibit at the booth showcased 135 products from various Siemens Digital Industries and Infrastructure divisions, covering a five-layer architecture from field level to cloud.
To help customers “break out of involution,” Siemens continues to develop products that balance cost-effectiveness and high efficiency. For instance, the newly released basic distributed I/O system SIMATIC ET 200BL at the CIIF enables rapid deployment and significantly reduces engineering costs for small and medium-sized enterprises. There are also rack-mounted IPCs compatible with the domestic Kylin operating system and HMI products with integrated IoT modules.
Additionally, Siemens continues to deepen its local presence. At its Dalian factory, Siemens has localized production of multiple products, such as the SIMATIC PCS 7 V10.0 high-availability DCS solution, which ensures continuous and stable production in process industries through multi-channel power supply and network redundancy.
In terms of services, Siemens has launched the SIMICAS Intelligent Diagnostics SaaS version and the BFC Baisuda 3.0 industrial IoT connectivity software. The former enables rapid iteration and low-cost operation and maintenance through cloud deployment, providing enterprises with efficient equipment health management. The latter aims to break down OT/IT data barriers, support multi-brand equipment compatibility and full-link secure data transmission, and empower enterprises to deeply mine the value of data assets.
“As involution compresses profit margins, the balance between transformation investment and short-term benefits becomes difficult. Manufacturers face a triple challenge—coping with an uncertain market environment, building differentiated core competitiveness, and rapidly converting innovative technologies into sustainable business value,” said Wang Haibin. “Siemens is committed to bridging the real and digital worlds, driving ultimate efficiency with industrial AI, accelerating the transformation of innovation into value, and helping enterprises achieve new intelligent growth.”
We can see that Siemens, with industrial AI as its core lever and relying on full-stack product support and ecosystem collaboration, is not only driving deep integration of AI into specific scenarios, but also using a full-value-chain strategy to solve the involution dilemma. By ensuring “right-first-time” in every manufacturing环节, and positioning itself as a full-value-chain partner, Siemens helps enterprises “upgrade upward” through technological advancement and “expand outward” into overseas markets—enabling more companies to find new growth opportunities amid industry transformation.
Design: Using Siemens NX MCD virtual simulation technology to shorten design cycles by 30%, improve change efficiency by 50%, and avoid rework costs.
Selection: Through the Siemens TIA Portal selection tool, automatically match hardware parameters, saving 80% of selection time and reducing procurement costs by 10%.
Debugging: Siemens Industrial Copilot assists in generating and automatically verifying PLC code, cutting on-site debugging time by 30% and reducing labor and material losses by 10%.
Manufacturing: The TIA fully integrated solution drives the SINAMICS S200 servo system, doubling production efficiency and increasing test pass rates by 30%.
Service: SIMICAS predictive maintenance can warn of failures 72 hours in advance, reducing unexpected downtime by 40%.
Low-carbon: The Smart ECX intelligent energy and carbon management platform helps enterprises measure carbon emissions and achieve green production.
As Wang Haibin stated: “Although involution is widespread, opportunities to break through are everywhere. When enterprises re-examine cost structures, operational efficiency, and innovation speed from a holistic perspective, they will find many areas for optimization—this is where Siemens works hand-in-hand with customers.”
Siemens’ digital industries divisions are collaborating to continuously launch innovative products tailored to the Chinese market. For example, the “Dazzling Heart 2.0” exhibit at the booth showcased 135 products from various Siemens Digital Industries and Infrastructure divisions, covering a five-layer architecture from field level to cloud.
To help customers “break out of involution,” Siemens continues to develop products that balance cost-effectiveness and high efficiency. For instance, the newly released basic distributed I/O system SIMATIC ET 200BL at the CIIF enables rapid deployment and significantly reduces engineering costs for small and medium-sized enterprises. There are also rack-mounted IPCs compatible with the domestic Kylin operating system and HMI products with integrated IoT modules.
Additionally, Siemens continues to deepen its local presence. At its Dalian factory, Siemens has localized production of multiple products, such as the SIMATIC PCS 7 V10.0 high-availability DCS solution, which ensures continuous and stable production in process industries through multi-channel power supply and network redundancy.
In terms of services, Siemens has launched the SIMICAS Intelligent Diagnostics SaaS version and the BFC Baisuda 3.0 industrial IoT connectivity software. The former enables rapid iteration and low-cost operation and maintenance through cloud deployment, providing enterprises with efficient equipment health management. The latter aims to break down OT/IT data barriers, support multi-brand equipment compatibility and full-link secure data transmission, and empower enterprises to deeply mine the value of data assets.
“As involution compresses profit margins, the balance between transformation investment and short-term benefits becomes difficult. Manufacturers face a triple challenge—coping with an uncertain market environment, building differentiated core competitiveness, and rapidly converting innovative technologies into sustainable business value,” said Wang Haibin. “Siemens is committed to bridging the real and digital worlds, driving ultimate efficiency with industrial AI, accelerating the transformation of innovation into value, and helping enterprises achieve new intelligent growth.”
We can see that Siemens, with industrial AI as its core lever and relying on full-stack product support and ecosystem collaboration, is not only driving deep integration of AI into specific scenarios, but also using a full-value-chain strategy to solve the involution dilemma. By ensuring “right-first-time” in every manufacturing环节, and positioning itself as a full-value-chain partner, Siemens helps enterprises “upgrade upward” through technological advancement and “expand outward” into overseas markets—enabling more companies to find new growth opportunities amid industry transformation.
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