The Role of Artificial Intelligence and Cloud Computing in Transforming Automotive Manufacturing: Enhancing Production Intelligence, Supply Chain Agility, and Financial Transactions in the Digital Economy
Keywords:
Artificial Intelligence in Automotive Manufacturing,Cloud Computing in Industry 4.0,Smart Manufacturing,AI-Driven Production Optimization,Digital Transformation in Automotive Industry,Supply Chain Agility,Intelligent Supply Chain Management,AI-Powered Quality Control,Predictive Maintenance,Cloud-Based Manufacturing Solutions,Digital Economy in Automotive Sector,Automotive Financial Transactions,Real-Time Data Analytics,Cyber-Physical Systems in Manufacturing,Industrial IoT and AI IntegrationAbstract
Despite having a sluggish first half of the last decade, the automotive industry is undergoing a major transition with the emergence of autonomous vehicles, electric vehicles, and connected vehicles. Consequently, the companies that manufacture automotive vehicles are reshaping current production methods and workflows to accommodate and facilitate this industry transition. Automotive manufacturing is traditionally very capital and labor-intensive. In recent years, however, breakthroughs in Artificial Intelligence and Cloud Computing have acted as important catalysts of change, as they have ameliorated technology accessibility, alleviating one of the main hurdles restricting their adoption. These technologies are already being used to facilitate or automate many activities at automotive manufacturing companies, such as vehicle design, supply chain and logistics operations, factory setup and operation, workforce management, quality control, marketing, sales, and after-market service management. Consequently, the efficiency of many key workflows is being dramatically improved, while costs, timing, and risks are comminuted. AI and CC are enabling the centralization and synchronization of previously discrete activities, thereby enhancing cross-functional decision-making. In this essay, we provide a detailed analysis of the role of these two technologies in enabling and supporting this transformation. We then examine the impact of their adoption on specific activities within these automotive manufacturing workflows. By highlighting key lessons and challenges, our analysis will serve both as a roadmap for automotive manufacturers to implement AI- and CC-centric transformations and as a guide for policymakers seeking to engineer similar transformations in other industries. Our essay will also identify important gaps in existing research and highlight opportunities for future academic work.
