In recent years, the GenAI wave has swept across a wide range of industries, and the automotive sector is no exception. Whether it’s improving customer experience, enhancing driving safety, or detecting road hazards, many manufacturers are exploring ways to use LLMs or GenAI to boost product value. One major automotive chip maker—Qualcomm—painted a compelling vision at its Tech Day in October 2024 for integrating GenAI and other next-generation service models into future automotive platforms.

However, bringing GenAI—cultivated on large GPU clusters in the cloud—down to on-premises or even in-vehicle systems is no simple task, and it comes with a variety of new security risks. This presentation will be divided into two main parts. In the first part, we will discuss the architecture and solutions available for practically deploying GenAI into vehicles. In the second part, we will analyze the security risks of each approach, including functionalities that have already been shown to pose concerns, as well as a forward-looking security assessment for large-scale adoption of this technology. Finally, we will provide relevant security recommendations.