Automotive engineering is undergoing a transition in which software, connectivity and artificial
intelligence increasingly determine vehicle functionality throughout the complete product lifecycle. The softwaredefined
vehicle extends development beyond the traditional point of production, as functions, operational
knowledge and customer-facing features can continue to evolve after deployment through over-the-air updates.
Artificial intelligence adds another dimension to this development. AI is becoming relevant not only for perception in
advanced driver assistance and automated driving, but increasingly for decision making and more integrated endto-
end approaches. These developments create significant opportunities for vehicle functionality and customer
experience, while at the same time increasing the importance of systematic verification, safety engineering and
lifecycle management. This paper provides an editorial perspective on this changing automotive engineering
landscape. Particular attention is given to AI safety, verification pipelines, continuous engineering, software-defined
vehicle architectures, over-the-air updates and the emerging use of end-to-end AI. The central observation is that
these topics are closely connected. Vehicles are becoming continuously evolving cyber-physical products, while
safety arguments have traditionally been developed around controlled configurations and well-defined engineering
baselines. Future automotive engineering therefore requires development, verification, monitoring and update
processes that can preserve engineering evidence across repeated product changes. AI further extends this
requirement because its behaviour depends on data, operational conditions and statistical performance in addition
to conventional software correctness.