AI with Purpose Summit 2025: Siemens’ Vision for Industrial-grade AI

Keywords: Industrial-grade AI, Large Language Model, Industrial Foundation Model, Simulation, Digital Twin, Siemens, Industrial Internet of Things

Summary

The Siemens AI with Purpose Summit 2025 is a landmark event that brings together over 800 participants, including C-level executives and engineers, to explore the transformative potential of AI in the industrial sector. This year’s summit showcased the latest innovations, practical applications, and strategic insights, highlighting Siemens' commitment to driving digital transformation and enhancing industrial processes.

The AI summit was filled with insightful speeches, panel discussions, and networking opportunities. The author shared his thoughts, "Days after the Siemens AI with Purpose Summit 2025, I’m full of insight, inspiration and motivation to further explore what's coming to industrial-grade AI.”

The event emphasized the importance of collaboration, trust, and interaction in leveraging the full potential of industrial AI technologies.

The Basis for Siemens’ Vision for Industrial-grade AI: The Industrial Foundation Model

The Industrial Foundation Model (IFM) is Siemens’ vision of a data model that “speaks the language of engineering.” According to the company, existing consumer-grade GenAI technologies rely on generic data from the internet, which is usually just text. The IFM addresses this shortcoming by handling complex data that includes images, 3D models, 2D drawings, and other complex, industry-specific structures. The goal is to support engineers with use cases such as identifying machining features and recommending strategies, accelerating P&ID creation, and processing complex engineering data.

A key to using the IFM will be agents (copilots) that are integrated in e.g., engineering tools. These agents/copilots are trained to understand a company's standards and best practices, and specific engineering rules and norms. Tapping into this knowledge, the agent/copilot can guide even an inexperienced user through complex design processes.

Industrial Foundation Models were a key focus at the Summit. The IFM concept left an impression on attendees and led to deep discussions during the event, including their future ability to understand and convert diverse industrial data formats, enabling true multimodal AI. Siemens managing board member Cedrik Neike highlighted the need for industrial-grade foundation models, stating, "To unlock the full potential of AI in industry, we need multimodal, industrial-grade foundation models—built to understand machines, workflows, and real-world constraints.”

The Role of Simulation Software in the Industry

Simulation software is crucial for industrial applications, providing a safe, efficient, and cost-effective environment for developing, testing, and optimizing AI-driven systems. Siemens' use of digital twins in manufacturing automation was highlighted, with one participant noting, "Siemens uses digital twins in manufacturing automation to continuously improve processes.” The acquisition of Altair by Siemens was also discussed, with the integration of Altair's high-end simulation software and AI tools into Siemens' portfolio, enhancing their AI strategy.

Simulation software offers several key benefits for industrial applications:

• Virtual Commissioning: Before real machines are built or retrofitted, complete production lines can be virtually tested using simulation software. This allows for the training and validation of AI algorithms, such as those for predictive maintenance or process optimization, in a simulated environment. This approach reduces downtime, speeds up time-to-market, and lowers costs.
• Training AI Models with Synthetic Data: In many industrial scenarios, real data may be insufficient or incomplete. Simulation software can generate synthetic, yet realistic, data to train AI models. For example, a model for defect detection can be trained with simulated defect images before real defects occur.
• Digital Twins: A digital twin is a virtual representation of a real machine or system. Combined with AI, digital twins can predict states, make optimization suggestions, and detect anomalies. Siemens uses digital twins in manufacturing automation to continuously improve processes.
• System Integration and Interoperability: Industrial systems are complex and consist of many components, such as sensors, robots, and controllers. Simulation software helps integrate AI-driven controls into these systems and test their behavior in the overall context.
• Risk Minimization and Safety: In safety-critical areas like energy, chemicals, and transportation, simulations can identify hazards before they occur. AI can learn to recognize and avoid critical situations in the simulation.

Siemens offers platforms such as NX and Simcenter for product and process simulation. Combined with AI algorithms, companies can simulate production processes, develop AI models for efficiency improvement, and later deploy these models in the real world.

Siemens' AI Strategy and Portfolio

Siemens' AI strategy is focused on integrating advanced technologies to drive innovation and efficiency across various industries. At the heart of this strategy is the Siemens Xcelerator platform, which combines software, hardware, and services to create a comprehensive digital business ecosystem. This platform enables companies to leverage AI for enhanced productivity, operational efficiency, and sustainability.

One of the key components of Siemens' AI strategy is the Industrial AI Suite, which provides scalable AI infrastructure for the shop floor. This suite includes tools for data analysis, predictive maintenance, and process optimization, allowing companies to harness the power of AI to improve their operations. Siemens' Industrial Copilot for Operations is another significant offering, bringing AI tasks directly to the shop floor for real-time decision making and reduced downtime.

In addition to these offerings, Siemens is expanding its AI portfolio through strategic partnerships and acquisitions. The Altair acquisition brings advanced simulation software and AI tools to Siemens' portfolio, enhancing design optimization, predictive modeling, and data science. This integration supports Siemens' goal of developing industrial-grade AI solutions that can optimize complex industrial processes and improve decision making.

Siemens' collaboration with leading technology companies such as NVIDIA, Microsoft, Accenture and AWS, to name just a few, further strengthens its AI strategy. These partnerships enable Siemens to deliver innovative solutions like digital twins, software-defined automation, and AI-driven design tools. Siemens showcased these advances at the Hanover Industrial Fair 2025, highlighting its role in accelerating digital transformation and sustainability across industries.

Overall, Siemens' AI strategy is built on a foundation of innovation, collaboration, and a commitment to driving real-world impact. By integrating AI with its comprehensive portfolio of industrial software and hardware, Siemens is empowering companies to stay competitive, resilient, and sustainable in an increasingly complex world.

Startups and Award Winners of the Summit

The Industrial AI Awards were a highlight of the Summit, recognizing innovative contributions to the industrial-grade AI field.

• PAILOT GmbH: Awarded for its Generative Physics Platform, which transforms production processes by enabling real-time evaluation of designs and immediate consumption and flow statistics of the hull, generating high-fidelity NURBS geometries for direct CAD workflows.
• plus10: Recognized for its self-learning AI software that optimizes complex manufacturing lines. The solution enhances machine performance and reduces downtime through continuous learning and adaptation.
• BeyondMath: Honoured for its innovative AI-powered 3D simulations that provide high-precision modeling and analysis for various industrial applications.
• Blockbrain: Received the audience award for its modular AI platform concept, which allows for flexible and scalable AI integration across different industrial processes.
• Compute Maritime: The company presented its product “NeuralShipper” in the Start-Up Area, which provides real-time evaluation of designs and immediate consumption and flow statistics of the hull, generating high-fidelity NURBS geometries for direct CAD workflows. This solution is currently unique because it runs on-premises, ensuring data security and compliance while delivering high-speed performance and accuracy.

Impact of the Altair Acquisition

The acquisition of Altair by Siemens is a significant strategic move that enhances Siemens' portfolio and strengthens its AI strategy. Altair is renowned for its high-end simulation software, such as Altair HyperWorks, Radioss, and AcuSolve. These tools complement Siemens' existing solutions such as Simcenter and NX, providing a more comprehensive suite of simulation capabilities. This integration allows Siemens to offer more robust and versatile simulation tools, which are essential for developing, testing, and optimizing AI-driven systems.

Altair brings advanced AI tools to Siemens, including AI-driven design optimization, predictive modeling, and data science platforms like Altair SmartWorks and RapidMiner. These tools enhance Siemens' ability to leverage AI for design exploration, anomaly detection, and process optimization. The integration of these technologies into Siemens' Xcelerator platform strengthens Siemens' position in the AI and industrial automation markets.

The combination of Altair’s simulation software and Siemens’ products and solutions will create powerful synergies. This integration enables the development of real time, learning digital twins that can predict states, make optimization suggestions, and detect anomalies. These capabilities are crucial for improving efficiency, reducing downtime, and enhancing decision making in industrial applications.

Altair's cloud-native platforms for simulation and data analysis, along with its high-performance computing (HPC) management tools such as PBS Works, expand Siemens' cloud and HPC offerings. This expansion allows Siemens to provide scalable and flexible solutions for small and medium-sized enterprises (SME), making advanced simulation and AI tools more accessible to a broader range of customers.

The acquisition of Altair aligns with Siemens' AI strategy by integrating AI and simulation more closely. This integration supports Siemens' goal of developing industrial-grade AI solutions that can understand and optimize complex industrial processes. The combined strengths of Siemens and Altair position Siemens as a leader in the industrial AI space, driving innovation and delivering value to customers.

Conclusion

Industrial software-defined automation (ISDA) and industrial-grade artificial intelligence constitute the fundamental elements of Siemens’ future vision for industrial automation. Across all domains of automation, technology is poised to transition towards IT-like architectures and integrate AI capabilities into software, encompassing engineering, design, and data analysis tools. Through substantial investments in these technological advancements, Siemens is strategically positioned to assist its industry clients in addressing the challenges presented by the digital era.

The Siemens AI with Purpose Summit 2025 demonstrated the immense potential of industrial-grade AI to drive innovation, efficiency, and collaboration. As Cedrik Neike stated, "Everyone has the same ingredients to make a croissant. But only with the right environment—temperature, timing, and care—can you make one that tastes like it’s fresh from a Parisian bakery.”

The future of industrial-grade AI will be shaped by collaboration, openness, data sharing and the courage to change.

ARC Advisory Group clients can view the complete report at the ARC Client Portal.

Contact Us if you would like to speak with the author.

Obtain more ARC In-depth Research Market Analysis.