Advanced tech infrastructure allows scaling of AI
The most AI-mature automotive companies have built sophisticated technical infrastructures that enable breakthrough AI applications in their vehicles while supporting deployment across manufacturing, customer platforms, and service operations.
General Motors has constructed a “data factory” processing telemetry – remote moderation – of tens of millions of vehicles. The platform democratizes vehicle health and safety insights across the organization, enabling predictive maintenance analytics and real-time fleet monitoring capabilities.
Toyota’s Advanced Drive system, part of its “Teammate” initiative, leverages AI, computer vision, and deep learning for hands-off freeway navigation. Their collaboration with Stanford Engineering achieved the world’s first fully autonomous tandem drift in July 2024.
Hyundai Motor has developed AI-powered features integrated directly into their vehicles, including the panoramic curved display and dual wireless charging in the Santa Fe compact SUV. Across their vehicle lineup, predictive AI systems enable the detection of potential vehicle maintenance issues before they arise, enhancing reliability and customer satisfaction. Beyond vehicles, Hyundai deployed DAL-e Delivery and Parking Robots in June 2024 at their Seoul facility, demonstrating practical applications of AI in logistics and space management. These delivery robots handle last-mile package distribution while parking robots optimize vehicle positioning in constrained urban environments.
Volkswagen Group has integrated ChatGPT-powered voice assistants into vehicles for seamless control, while their September 2024 partnership with Google Cloud integrated generative AI into customer applications, creating new value propositions that enhance vehicle ownership experiences. They announced plans in April 2024 to test their fully autonomous ID Buzz robotaxi in Hamburg, with the service designed to integrate seamlessly into the city’s existing transportation infrastructure while collecting real-world performance data to refine autonomous driving algorithms.