AI Influence on the Automotive Industry: A Qualitative Study of Technological Transformation and Industrial Restructuring

Abstract

This paper explores the multifaceted influence of artificial intelligence on the automotive industry, employing a qualitative research methodology to examine the ongoing transformation across the entire industrial value chain. Based on semi-structured interviews with 23 industry professionals—including R&D engineers, product managers, supply chain directors, and quality control specialists from automotive OEMs, Tier 1 suppliers, and technology firms—the study identifies four key domains of AI-driven transformation: autonomous driving systems, smart cockpits and user experience, intelligent manufacturing and quality management, and supply chain optimization. The findings reveal that AI is fundamentally reshaping not only vehicle capabilities but also the core logic of competition—shifting the industry from hardware-centric differentiation to AI-driven user experience and operational efficiency. However, the research also identifies persistent challenges, including the “trust gap” between AI capabilities and user acceptance, data privacy concerns, and organizational barriers to AI adoption. The study concludes that while AI presents unprecedented opportunities for value creation—estimated at approximately USD 300 billion annually by 2030 [5]—its successful integration requires systemic transformation rather than isolated technological deployment, alongside the establishment of trustworthy AI frameworks