SPECIFIC METHODS IN THE AUTOMOTIVE INDUSTRY: ARTIFICIAL INTELLIGENCE IN THE INTEGRATION OF NONCONVENTIONAL MECHATRONIC SYSTEMS

The present paper aims to analyze the nonconventional use of artificial intelligence (AI) in optimizing classical and modern methodologies in the automotive industry, focusing on the Waterfall model, the Just in Time (JIT) concept and Agile methodologies. AI fundamentally transforms these traditional approaches, thus responding to the need for flexibility, efficiency and adaptability in an industry in full technological evolution. In this context, methodologies such as Extreme Programming (XP), Scrum and Kanban are reviewed and adapted through the nonconventional use of AI, optimizing development processes and the integration of mechatronic systems. The paper also explores how AI improves the Waterfall model and JIT flows, providing advanced solutions for automating and streamlining production. Industry examples such as Tesla, Toyota, and Volkswagen illustrate the real impact of AI in reducing costs, increasing speed of execution, and adapting to dynamic market demands. The paper concludes that AI, through nonconventional uses, opens up new perspectives for innovation in the development of vehicles and mechatronic systems.