This thesis analyses the problems and obstacles faced when AI-based automation is introduced in the automotive industry in India, which is developing fast with Industry 4.0 technologies. Its purpose is to uncover how much AI is being used and what factors, positive or negative, shape its usage. Both quantitative questionnaires and qualitative interviews were carried out with professionals from the automotive, manufacturing, IT and logistics industries. It is evident from the findings that AI is gradually growing in use, mainly for real-time choices, planned maintenance and organising processes. On the positive side, adoption helps a company improve its work, cut downtime and offer better products; still, the main challenges faced are high prices, not enough technical knowledge, infrastructure faults and worries about data privacy. It puts forward the importance of investing strategically in training, infrastructure improvement, and digital technology. It helps both theory and practice by linking what is found in studies to models such as TAM, DCT and the Digital Transformation Capability Framework.