Human and AI as Drivers of Innovation
Used as a strategic tool, artificial intelligence (AI) optimizes processes and enhances products. Torsten Gollewski, Executive Vice President R&D Innovation & Technology at ZF, discusses the growing importance of AI for his department.
Mr. Gollewski, within just a few years, artificial intelligence (AI) has evolved from a niche topic into a widely used tool. What impact is it having on innovation?
AI is fundamentally transforming innovation and development processes. At present, two key perspectives stand out in driving major technological advances: the integration of AI into physical systems – often referred to as Physical AI – and the use of autonomous, goal-oriented AI systems, known as Agentic AI. The most significant shift, however, lies in the depth of value creation within development.
Could you explain that in more detail?
With AI, we are able to manage complexity in development far more effectively. For example, we can generate and evaluate product variants much faster. AI also enables data-driven decision making.
As a result, development is shifting away from a highly segmented, sequential workflow toward a highly integrated, non-linear, AI-supported value creation process that is much more individualized. This leads to shorter development cycles and better outcomes.
Where do you see the main challenges?
We need a fundamentally new understanding of development, because AI represents perhaps the most significant transformation we have ever faced in this area. It is a misconception to believe that simply applying AI to existing processes will yield substantially better results.
Our experience shows that processes must be completely redesigned when AI is integrated to unlock its full potential. In short, AI delivers its greatest benefits only when the entire development process is transformed alongside it.
Why is that so difficult?
AI is currently receiving enormous attention and promises a great deal. However, the scale of the transformation it requires within organizations is often underestimated.
We must understand where, how, and how quickly AI should be deployed in both processes and products – and it must be implemented across the entire company. Otherwise, its impact will remain limited.
When applied correctly, the increased speed enabled by new learning methods is a major advantage. Some studies indicate that savings of up to 20 percent can be achieved in both development activities and indirect costs.
Executive Vice President R&D Innovation & Technology at ZF
What are the key priorities in research and development?
To remain competitive on a global scale, we must consistently leverage AI in both products and processes. This requires access to large volumes of high-quality data.
With this foundation, we can describe and specify products far more precisely. AI-based product design allows us to improve product performance while simultaneously reducing costs. At the same time, we need skilled professionals who can translate this technology into scalable, robust processes and applications.
What tasks do developers perform with AI?
We focus on two main areas: AI in our products and AI in our development processes. In products, AI makes them smarter, more efficient or even enables entirely new functionalities, for example as virtual sensors in solutions like “TempAI.”
In product development, AI accelerates processes by helping us quickly move from requirements, stored data, trained company knowledge, or globally available information to viable product concepts.
What happens next in the process?
Engineers then evaluate these concepts and build upon them. The second focus area is AI as an “agent” or development partner for example in software and system development, in the use of digital twins, in virtual testing, and in mechanical engineering.
Both areas significantly accelerate our development timelines, but they always depend on a solid data foundation.
What are the biggest effects of this AI transformation?
The most notable improvements are in speed, efficiency, and product quality. Development and release cycles are becoming significantly shorter.
Processes that previously took weeks can now be completed in days or even hours. Efforts in testing and requirements analysis have also been greatly reduced, as many routine tasks are now automated.
For our competitiveness, it is essential to adopt the advantages of AI faster than our competitors and to do so across the entire organization, not just in development. Our customers are closely monitoring our structures and are well aware of the efficiency gains that can be achieved.
How does ZF organize the use of AI in development?
The AI Tech Center serves as our central hub for AI in development. It consolidates expertise and ensures the widespread adoption of AI across all areas.
The center works closely with specialist departments, covering everything from specifications and coding to design and testing.
A key priority is scaling successful projects quickly across large parts of the organization, leveraging synergies, and ensuring measurable impact. The AI Tech Center brings together knowledge and capabilities to maintain competitiveness and avoid fragmentation across sub-organizations.
Where do you see the automotive industry in 20 years thanks to AI?
The industry will be profoundly shaped by AI – particularly influenced by developments in China. The ways data is utilized together with OEMs and the innovation cycles of technology companies will look very different from today.
We are already seeing what is possible: product changes can be implemented rapidly, and their impact can be visualized in simulated production environments or digital factories. This trend will undoubtedly continue to accelerate.
Product development itself will also be fundamentally transformed by the ever-growing volume of data. Innovation will become more diverse and dynamic, opening entirely new creative possibilities for engineers.
