Core Viewpoint - AI has become an essential component for the survival of automotive enterprises, transitioning from an optional technology to a core competitive advantage for the next decade [6][7]. Design Phase - AI enhances the efficiency of "creative realization" by tenfold, significantly reducing the automotive design cycle from weeks to hours through systems like AiCube [12][13]. - Custom design processes have been revolutionized by NVIDIA RTX AI workstations, compressing development timelines from six months to six weeks while improving efficiency and quality [15][16]. - Future automotive design will increasingly rely on "human-machine collaboration" as AI capabilities are integrated into modeling tools [18]. Manufacturing Phase - AI is transforming automotive manufacturing from mass production to flexible intelligent manufacturing, enhancing resilience [19]. - The Li-Mos system at Li Auto's manufacturing base has improved production efficiency by 20% and reduced operational costs by 25% through real-time AI monitoring [21]. - AI-driven flexible production lines have decreased model switching time from four hours to 27 minutes, allowing for the simultaneous production of multiple vehicle models [23]. Product Value Reconstruction - The automotive industry is evolving from "wheeled sofas" to "mobile intelligent terminals," with AI as the driving force behind this transformation [24]. - Tesla's Full Self-Driving (FSD) system exemplifies AI's role in enabling complex decision-making capabilities in autonomous driving [25][27]. - Huawei's investment in AI has led to advancements in human-vehicle interaction, shifting competition from hardware specifications to AI-driven user experiences [29]. Sales and After-Sales Service - AI is transforming marketing from one-way communication to interactive engagement, as demonstrated by Dongfeng's AI co-creation launch event that attracted 280,000 participants [38][40]. - The digital upgrade of the vehicle pickup process by Autox3 enhances transparency and efficiency, creating a win-win situation for vehicle owners, service centers, and parts suppliers [42]. Implementation Insights - Four key actions for AI transformation in automotive enterprises include building a closed-loop technology system, restructuring traditional business processes around AI, establishing high-quality data governance, and cultivating cross-disciplinary talent [43]. - The integration of AI into the automotive industry is a long-term ecological reconstruction rather than a one-time technological upgrade [45].