AI-Native Cars and Organizational Transformation: A New Paradigm for Vehicles as AI's Physical Embodiment

Recently, an automotive brand named AIVA released an advertisement that featured no close-ups of the vehicle body or battery range specifications—only an AI entity narrating its role as a family member. In an exclusive interview with China Central Television (CCTV), Li Bo, President of AIVA’s parent company, stated that as AI evolves from narrow artificial intelligence toward general artificial intelligence, the century-old category of automobiles may be fundamentally redefined. Industry data shows that by 2026, the penetration rate of large AI models in vehicles has already exceeded 20%. However, user complaints about tech features are now growing faster than complaints about the mere presence or absence of functions, indicating that simply “adding AI to cars” is no longer sufficient to meet market demands. The industry must now explore how AI can truly redefine the automobile. Cars have become a critical physical-world entry point for AI for three key reasons: First, compared to devices like smartphones, vehicles offer greater energy reserves and computational power, enabling real-time operation of on-device large models and establishing a foundation of user trust. Second, cars are used frequently and over long periods; combined with China’s smart cockpit penetration rate exceeding 80%, this allows for massive accumulation of user data to continuously drive AI evolution. Third, vehicles are equipped with rich sensor suites and integrated systems, enabling a complete closed-loop from perception to action—giving them the unique combination of an “energy base + data-rich mine + execution terminal.” In product definition, AIVA adopts an “AI-native” approach: instead of the traditional model of building a car first and then adding features, it starts by defining required AI functionalities and capabilities, then reverse-engineers the entire vehicle design accordingly. Its product philosophy centers on “deep understanding × time freedom × space freedom,” leveraging AI to take over routine tasks and reconfigure cabin layouts to enhance user experience. On the organizational front, AIVA has implemented a “Everyone Raises Shrimp” mechanism—extending AI tools from individual productivity to team collaboration—and hosts skill competitions to internalize AI capabilities across the company. It has formed an “AI Rising Stars” team to develop the “AI Scout” system and is exporting its AI capabilities throughout the supply chain. The company’s organizational philosophy emphasizes using AI to shorten decision-making chains and expand individual capability boundaries. AIVA has garnered support from multiple stakeholders, including Chongqing’s industrial cluster, Seres, Volcano Engine, and CATL, driving forward AI-native vehicles, organizations, and end-to-end services with dual engines of technology and user demand. Yet significant challenges remain, including the need to establish a new framework for user-perceived value, address counterintuitive product forms, and overcome psychological barriers among users. Currently, AIVA is testing this new paradigm—but ultimately, the market demands automotive products that users actively choose and that align with their aspirations for mobility.