Unveiling the Impact of Artificial Intelligence on Automotive Supply Chain Operations

ABSTRACT

This study examines the transformative impact of artificial intelligence (AI) on supply chain management (SCM) within the automotive manufacturing sector, with a focus on AI adoption, its influence on key performance indicators (KPIs) and integration challenges. A mixed‐methods research design was employed, combining quantitative survey data collected from supply chain professionals with qualitative insights derived from semi‐structured interviews with industry experts. The quantitative data were analysed using statistical techniques to assess the relationship between AI adoption and SCM performance, whereas thematic analysis of interview data provided deeper contextual understanding of organisational and technological dynamics. The results indicate that AI adoption significantly improves operational performance, particularly in inventory turnover, delivery lead times and order accuracy. However, the findings also reveal critical barriers, including data quality limitations, system integration complexities, ethical concerns related to algorithmic bias and data privacy and potential workforce displacement. The study further identifies organisational readiness—driven by leadership commitment, innovation‐oriented culture and robust technological infrastructure—as a key enabler of successful AI implementation. Based on these findings, the study recommends the development of structured AI adoption frameworks, including phased implementation strategies, investment in digital infrastructure, and targeted workforce reskilling initiatives. It also emphasises the need for ethical governance mechanisms to ensure transparency, accountability, and responsible AI deployment. These insights provide actionable guidance for practitioners and policymakers seeking to enhance supply chain performance while addressing the broader socio‐technical implications of AI integration.