Christof Horn
Global Lead SW Defined Vehicle, Accenture

Christof Horn is a prominent figure in the automotive industry, particularly in the realm of digital transformation and software-defined vehicles. With over 20 years of experience, he has significantly influenced the integration of electronics and software in vehicles. He began his career after studying Physics and Mathematics at the universities of Stuttgart and Bologna and initially joined P3, which later became umlaut.

In 2021, Horn joined Accenture as the head of the Automotive Europe practice within Industry X, where he combines his expertise in vehicles with Accenture’s strengths in IT, cloud, and data. His primary mission is to support OEMs and first-tier suppliers in the transition to software-defined vehicles, helping them transform their processes, organizations, and mindsets to be more software and data-driven.

Additionally, Christof is an active keynote speaker, author, and podcaster, sharing insights on digital transformation in his podcast #digdeep. He also writes a LinkedIn newsletter called "Software driven," focusing on the challenges and developments in the software-defined vehicle sector.

Redefining the V-Model: How to Scale AI in Future Automotive Development Processes

Everyone in the Automotive industry knows that today’s  product development is in difficulties.

While the V-Model has proven to be the most successful and applied framework of the past, new aspects like technology platforms, data and cloud layers outside the vehicle, OTA-updates, open source and a lifecycle maintenance for decades are emerging. Established development approaches do not adequately address the new requirements that arise as a result, meaning that neither time to market nor development costs are satisfactory.

With the advent of Generative AI and Agentic AI, new powerful tools have entered the stage, which offer the potential to accelerate and streamline product development processes.  But first experiences indicate substantial roadblocks: the “proof-of-concept trap”, isolated co-pilots without end-to-end value, missing governance processes, tool fragmentation, and a very shaky data foundation. 

In our talk, we want to shed a light on the opportunities, roadblocks, prerequisites and next steps to obtain more impact and value from AI applications for the Automotive development process. Only those who lay the groundwork now for scalable applications of AI in product development will be able to achieve efficiency gains and cycle shortenings in the future.