3 Questions for… Steve Basra, Director, Global Head of Automotive, Google Cloud

In this interview, Basra, who has held management positions at Hyundai and Toyota, explains how generative AI is redefining automotive software development workflows, what responsible AI implementation looks like in mission-critical vehicle systems, and how Google Cloud is accelerating AI-driven innovation within OEM ecosystems.

ADT: How is generative AI redefining automotive software development workflows?

Basra: Generative AI is reshaping automotive software development workflows by acting as an intelligent assistant across the entire lifecycle, from faster development cycles and enhanced software quality to boosting efficiency and creating a better developer experience.

Developers now leverage AI tools for tasks like accelerating code generation and completion, automatically creating diverse test cases and synthetic sensor data for validation, analyzing complex requirements for clarity and consistency, generating documentation from code, and assisting in debugging by suggesting root causes. This AI augmentation helps manage the escalating software complexity in modern vehicles, automating repetitive tasks and enabling engineers to focus on higher-level design and problem-solving, ultimately streamlining processes from initial concept to final testing.

What does responsible AI implementation look like when integrated into mission-critical vehicle systems?

Adopting powerful technologies like generative AI requires both bold innovation and a deeply responsible approach. Given the critical nature of these systems, especially in the automotive sector, deployment must be deliberate, ensuring safety, expertise, and high-quality information. 

Fine-tuned large language models, which are models that are pre-trained on smaller, specific datasets, offer improved accuracy for targeted topics. The quality of gen AI outputs is also improved by "grounding" the model, which connects generated text to real-world information and context. This means that for every judgment or assessment produced, models can footnote or directly link back to a piece of supporting data. Explainable gen AI models enable OEMs to transparently explain their decision-making processes to customers and employees, building trust and confidence in the AI-driven services they offer. 

What role does Google Cloud play in accelerating AI-driven innovation within OEM ecosystems?

As automakers navigate the rapidly changing automotive industry, the transition to software-defined vehicles, and connected seamless customer experiences, Google Cloud plays a pivotal role by offering advanced AI, cloud, and data analytics solutions that enhance the entire OEM value chain. 

For in-vehicle experiences, Google Cloud’s Automotive AI Agent enables OEMs to build customized, high-quality AI assistants using generative AI, and our Auto SDK provides modern AI-powered mapping solutions. Google Cloud also extends to customer interactions beyond the car; Google’s TPUs (Tensor Processing Units) are helping OEMs accelerate the development of the next generation of ADAS and autonomous driving solutions. Imagen helps personalize marketing with tailored content and promotions for a more convenient shopping experience.

Furthermore, Google Cloud provides intuitive technologies to optimize operations: automakers can leverage data for better demand planning and inventory forecasting with Vertex AI, while the Manufacturing Data Engine uses predictive analytics to help reduce recalls and costly production delays. Finally, Google Cloud addresses workforce productivity, with Gemini helping to train employees and mitigate knowledge loss, and Gemini Code Assist enabling developers to operate more effectively.