AI, Data, and System Understanding Five Theses for the Future of Engineering

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Software-defined products and artificial intelligence are transforming product development. A new position paper by Dassault Systèmes and WiGeP shows that, to remain competitive, the industry needs a new level of engineering expertise. AI will not replace engineers—but it will change their role.

Germany and Europe have a long tradition of engineering excellence. But the rules of the game in industrial value creation are changing rapidly. Artificial intelligence, geopolitical dependencies, and the trend toward increasingly complex, software-defined systems are placing entirely new demands on product development.This is the conclusion reached by Dassault Systèmes and the Scientific Society for Product Development (WiGeP). During a joint symposium with experts from academia and industry, they discussed future challenges and have now published a joint position paper. The core message: engineering expertise is becoming an absolute strategic prerequisite—not only for innovation but also for Europe’s technological sovereignty.

 Engineering expertise is becoming an absolute strategic necessity—not only for Europe’s innovative strength, but also for its technological sovereignty.

Five Theses and Recommendations for Action 

In order to be able to develop complex products and production systems more quickly and efficiently than other economic regions in the future, the initiators have formulated five key propositions and recommendations for action:

1. Understanding Systems Is Becoming the Ultimate Key Competency
   The days when mechanics, electronics, and software could be considered in isolation are over. Modern products are evolving into integrated technical systems, driven by data and AI. In the future, engineers must be able to understand this enormous complexity across disciplines and throughout the entire life cycle in order to weigh conflicting objectives and make sound decisions.
2.  AI is transforming engineering—but it won’t replace it
   The good news for design engineers: While artificial intelligence will fundamentally transform development processes and drastically reduce development times, it is no substitute for humans. Neither a basic understanding of physics nor technical responsibility can be outsourced to AI. On the contrary: As the use of AI increases, human judgment and in-depth system knowledge will become even more important.
3. No Digital Twin Without Data and Models
   The foundation of modern product development consists of structured, trustworthy, and interoperable data. Only on the basis of consistent models can virtual and digital twins be created that seamlessly connect development, manufacturing, and operation. This data quality is the bottleneck: It will play a decisive role in determining the pace of innovation in the future.
4. Innovation Requires Close Collaboration Between Research and Industry
   Traditional training and innovation cycles are often too slow for today’s fast-paced environment. According to the position paper, the required engineering expertise can only emerge through close, continuous collaboration between universities, research institutions, and industry. Intensive knowledge transfer is necessary to quickly translate new methods into industrial practice.
5. Product development must become a top priority for policymakers
   Advancing product development is not merely an industrial task, but one with national and European implications. The authors call on policymakers to view product development as a strategic priority. They argue that long-term initiatives are needed to strengthen digital infrastructure, research collaborations, and modern educational models.

Germany’s and Europe’s industrial competitiveness is at stake. To make complex innovations market-ready, we now need joint investments in the future of engineering.