Siemens Digital Industries Software

Dreamforce 2025 has officially wrapped! 🤝 This year, we proudly launched our first-ever Manufacturing Lounge at Dreamforce — featuring a Thought Leadership Theater and a Podcast Studio. Together with our partners, we explored how manufacturers can unlock new value through aftermarket services, AI-driven innovation, and connected ecosystems. 🎙️ Our theater sessions captured powerful insights from industry leaders on topics like: ✅ How agentic AI is transforming service operations with a 360° view of product and customer data ✅ Making complex service documentation conversational with visual AI tools ✅ Using digital twins to accelerate asset monetization and drive customer loyalty ✅ Bridging the last mile in service with augmented reality and frontline enablement ✅ Integrating PLM, CRM, and ERP to streamline quoting, spare parts, and service workflows 📢 These conversations will be available soon on our podcast — stay tuned to hear directly from Siemens and our partners on how we're shaping the future of manufacturing. Thank you to everyone who joined us at the Lounge. We’re already looking forward to Dreamforce 2026!

AI is more than just a technological advancement for software development. It’s a fundamental shift. How software is now ideated, developed, and deployed...Generative and agentic AI is changing all of it. 💡 But those are just two of the main ingredients to transforming into a successful digital enterprise. You also need: 1️⃣ Data governance – Optimize and automate processes that help you get data so that you can make the right decisions 2️⃣ Data analytics – Gain the ability to get the right data to help make those right decisions 3️⃣ Workflow orchestration – Create an orchestration layer that gives you end-to-end automation across your complex tech stacks 4️⃣ Generative AI - Invest in the right data governance and integration tools to build the right models that can help you leverage genAI anywhere across the value chain 5️⃣ Agentic AI – Lay the foundation down across your systems so that you can build agents The successful digital enterprise means building intelligent, adaptive software. You can empower yourself to build these by embedding agentic and generative AI into an intelligent software development solution like Mendix – part of the Siemens Xclerator ecosystem. With Mendix as part of the Siemens Xcelerator portfolio, we make custom development of intelligent software easy, whether that’s extending Teamcenter data or making a custom UI from Opcenter that fits your needs. Head over to the link in our comments for more information!

For engineering students today, one of the hardest parts of launching a career is demonstrating your value without extensive professional experience on your resume. For Hani Qaqish, an emerging leader at Siemens and technical product manager for NX X, credentials were key to verifying his skills and even beating imposter syndrome when he first started his career. 💡 “When I started at Siemens, everyone seemed so high-functioning, and I was lacking confidence,” Hani admitted. “That’s why credentials became important to me.” With specific credentials to underline his skills in key areas, Hani was able to step into the workforce with confidence. Less than two years since earning his bachelor’s degree, he now manages a key product for Siemens. 🥳 Learn about Siemens' newest credential, designed to prepare emerging engineers for industry - the link is in our comments! 🔗

The AI vs. AI cybersecurity battle is here. 🛡️ The cat-and-mouse game has leveled up. Fixing bugs is not enough; we need to secure the entire digital foundation. ⚔️ The defender's edge: Agentic AI can finally automate complex, mundane tasks like maintaining security-configuration baselines—a process too complex for traditional automation. This closes the gaps left by slow, manual updates ⚔️ The LLM risk: Relying on external large language models (LLMs) without a framework is a critical risk. Continuous validation isn't optional; it's mandatory to ensure security and model fitness over time. AI helps support slow security practices, and robust security ensures AI is production-ready. Check out the link in our comments to better understand the importance of cybersecurity for industrial AI.

The aerospace and complex industries are in a massive digital transformation, rapidly moving toward software-defined products. Here are critical takeaways on adapting to this shift: 🧠 AI is "shifting left": AI now goes beyond analysis and testing, moving into the development process itself 💡 Embracing change to unlock value: Digitalization requires cultural and business model shifts, which is the hardest part. Successful transformation requires rethinking old assumptions and committing to long-term investment 🛠️ Shift-left means the right model: While digital twins are crucial, they don't replace physical testing. The goal is a hybrid approach where you use high-fidelity simulation or a simple physical mock-up, depending on the need 🗺️ Transformation is a journey: Digitalization is continuous. Companies must challenge assumptions and focus on high-value, easy-to-adopt steps For more insight on how to navigate the shift to software-defined product development, head over to the link in our comments for more info!

The pace of innovation in industry means a linear path from classroom to career just doesn't cut it anymore. As Siemens USA CEO Barbara Humpton puts it, "the learning never ends. There are just myriad opportunities every year as new things appear on the horizon.” Many US manufacturers face a dual challenge: critical labor shortages and a widening gap between the skills employers need and the expertise employees possess. The solution lies in upskilling and redefining education for a modern workforce. How do we get there? 🏫 Industry & academia collaboration: Partnerships like Siemens' microcredentialing program with Penn State University and University of Colorado Boulder are vital for preparing graduates and upskilling mid-career professionals 🏫 University as a "lifelong partner": Universities must embrace flexibility and focus on real-world skills—integrating hands-on experiences with advanced tools like the digital twin 🏫 A mindset shift: Lifelong learning is a foundational skill. It's about being curious, taking initiative, and having "the ability to manage your own lifelong learning," as Humpton shares The takeaway? Investing in the development of current talent is not just a strategy—it's essential for building resilient, future-ready teams. Head over to the link in our comments for more information.

Aerospace and defense (A&D) manufacturers are at a crucial inflection point. The shift to high-volume production for products like drones and satellites demands a complete rethink of traditional low-volume assembly lines. Reworking complex factories and processes carries significant risk—errors and sub-optimal layouts can cost millions and cause major delays long after construction is finished. The solution? Simulate before you construct. The production digital twin offers a game-changing way to de-risk these massive investments. By creating a virtual replica of an entire factory, assembly line, or process, engineers can: 🔄 Identify and fix errors before laying a single physical foundation 🔄 Optimize operations against key performance indicators (KPIs) like efficiency and throughput 🔄 Forecast and mitigate disruptions (like supply chain issues) in real-time, even after the factory is operational, using live data from IoT sensors For A&D companies investing in the next generation of aircraft and spacecraft, this tool isn't a luxury—it's essential for ensuring new or refitted factories are built for peak performance and future demand. Head over to the link in our comments to better understand how the production digital twin prepares A&D manufacturers for the future.

Today’s engineering students will likely experience the largest industrial transformation in 100 years. 🏫 Dr. Michael Readey of the University of Colorado Boulder made this point to emphasize the importance of students learning to become more adaptable. “Just think about where electric vehicles are going, not just in terms of cars but buses and even electric airplanes,” said Dr. Readey. 🚗🚌✈️ “So, while we teach plenty of fundamentals, the world is changing very rapidly, and we need to be prepared for it. And as educators, it’s very important that we are mindful of that.” In Dr. Readey’s experience, practical, project-based challenges driven by industry are essential to help students apply foundational knowledge and develop key durable skills. As an example, senior design projects offer a great opportunity for industry to expose engineering students to practical challenges and better understand the application of core concepts. 💡

Siemens + Ducati Motor Holding = a 1st place partnership 🏍️ 🤝🥇 Through this ongoing collaboration, we support the Ducati team's mission of creating powerful, sustainable and safe racing and street motorcycles with cutting-edge tech from the Siemens Xcelerator portfolio. “Our partnership with Siemens has not only helped us meet current challenges but has also positioned us perfectly to meet future challenges, both on the racetrack and in the global market. We are ready to continue winning, with innovation as our guiding principle.” — Massimiliano Bertei, CTO, Ducati Motor Holding Learn more about how this multi-domain team is racing ahead of the competition from design to simulation to production with a winning combo that includes NX software, Teamcenter software and Simcenter software. 🏆🏁 Link to the full story in the comments.

"If drones are 'unmanned,' why do they always need a pilot on the ground?" 🤔 That simple question from NxtQube’s founder sparked a mission: to achieve truly autonomous drone operations. 🛰️ Most commercial drone missions get stuck in logistics—travel, manual mission planning, and on-site battery swaps. NxtQube's game-changer is the Drone in a Box (DiaB): a weatherproof docking station that launches, lands, charges, and monitors UAVs 24/7 without human intervention. To turn this vision into a scalable, robust product, they needed powerful engineering tools. By leveraging Solid Edge through the startups program, NxtQube was able to: 🚀 Reduce the dock's weight by over 60% while increasing robustness 🔬 Use FEA simulation to ensure a product life of 4–5 years in harsh conditions 📈 Scale production from 150 to 300 drone ports annually This partnership isn't just about hardware; NxtQube is building the world's first Agentic AI Platform for drones. Learn how simulation and smart design are powering the future of autonomous infrastructure for agriculture, utilities, and logistics - the link is in our comments!