Bob Monkman

The automotive industry is experiencing a clear split in development velocity. While leading Chinese OEMs operate with cloud-native, software-defined architectures and deliver new vehicles in roughly half the traditional cycle time, many incumbent manufacturers are transitioning, balancing software-defined ambitions with established hardware-led processes. This results in a widening efficiency and capability gap that directly impacts cost, innovation speed, and global competitiveness.

This talk examines the consequences of maintaining current development models. In a software-defined vehicle ecosystem, given the pace of innovation reshaping the competitive landscape, slower iteration can contribute to an ever-widening gap, underscoring the need for more open, AI-accelerated collaboration. We explore the potential impact of AI as a practical accelerator across the software development lifecycle, outlining potential efficiency gains from modern AI techniques, the infrastructure prerequisites to enable them, and how collaborative industry initiatives, such as S-CORE, could act as force multipliers for incumbents.