India’s Automotive Sector Lacks a Business Use Case for AI Implementation

Abstract: Despite the rising trend of artificial intelligence (AI) use in the global automotive industry, India's automotive sector has been slow to adopt AI-driven change. This paper looks at the main reasons for the lack of strong business cases for implementing AI in India's automotive ecosystem. In India's automotive industry, investing in new technology faces many hurdles. Cost-Sensitive markets, broken supply chains, weak digital systems, and a lack of skilled workers make it harder to adopt modern solutions. On top of that, traditional manufacturing practices still dominate, and there isn't much collaboration between tech startups and established manufactures. To move forward, the industry needs practical, localized solutions and stronger partnerships between the public and private sectors. There efforts can turn big ideas into real, useful applications and help bridge the gap between technology's promise and what happens on the ground. While global counterparts are using AI for predictive maintenance, autonomous driving, and smart manufacturing, Indian automotive players struggle to connect AI applications with cost-effectiveness, scalability, and practical use.

Keywords: Artificial Intelligence (AI), Automotive industry, Cost-sensitive markets, Supply chain challenges, Weak digital infrastructure, Traditional manufacturing practices.