COVER STORY
The Rise of AI-Driven
Vehicle Development
Between Promise and Responsibility:
By combining human expertise with data-driven intelligence, AI creates
a seamless link between engineering, simulation, and testing. It not only
accelerates innovation but also enhances quality, reliability, and trust, which
are essential values in shaping the next generation of mobility. FOCUS asked,
Stefan Bruhnke, Roland Wanker, and Jens Poggenburg to shed light on the
significance of this topic and how artificial intelligence is redefining what’s
possible in vehicle development.
Why is AI a true game changer for vehicle development rath-
er than just another tool?
Bruhnke: AI is changing our overall approach to development.
It influences methods, processes, and even how we think
about systems. AI helps shorten development cycles across
the entire chain, from requirements to predictive mainte-
nance. It is the foundation for future concepts such as the
software-defined vehicle.
Wanker: For me, AI is a powerful catalyst. It brings automa-
tion and efficiency into areas that were too complex to handle
manually, especially in simulation. What matters most is that
engineers can access and use information across the organi-
zation faster and more intuitively.
Poggenburg: AI gives us a new level of confidence. It
strengthens the credibility of results, for instance, in ADAS
validation or over-the-air software updates. It also enables
us to align our entire portfolio with AI-enriched methods,
from development tools to customer services. This marks a
fundamental shift.
How is AI changing the way AVL develops, simulates, and
tests vehicles, and how are these areas more closely linked
through AI?
Poggenburg: AI is changing how we work together. It takes
data usage to a completely new level. We can use information
that already exists in the company faster and more effectively,
which makes collaboration across business units much easi-
er. In 2026, we will launch an AI-supported Service Center that
will serve as a direct interface between customers and AVL
experts. It will enable knowledge sharing and problem solving
in real time, making collaboration even more efficient.
Bruhnke: What AI enables is a truly holistic approach. We gen-
erate data from simulations, from tests, and from develop-
ment work itself. With consistent data management, which AI
makes possible, we can connect it all and even feed back field
data into the requirements process. This makes the entire
development more focused.
Wanker: Simulation is already one of the strongest drivers
of efficiency, and AI is pushing that even further. The world
is looking for speed, and AI helps deliver it. It connects data
sources, automates model creation, and enables engineers to
get to results faster.
Can you share examples where AI has accelerated develop-
ment or made new results possible?
Bruhnke: A good example is our AVL Vehicle Composer. It
uses trained AI models to create a Virtual Twin very early on
in development. You can evaluate multiple vehicle attributes
simultaneously and immediately see how a change in one
component affects the overall system. This can shorten
concept phases by up to three months and reduce hardware
prototypes by up to 40 %.
Wanker: One clear use case is virtual calibration in real-time
simulation. Without AI and machine learning, this speed and
precision would not have been achievable.
Poggenburg: In testing, AI supports both parameterization
and planning. We can now use far more data from lab, road,
and fleet operations in a unified process. This expands test
coverage and improves the quality of results. The boundaries
between virtual and physical testing are becoming more and
more fluid.
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