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Using AI Tools to Enhance the Risk Management Process in the Automotive Industry

  • Diana Dragomir,
  • Florin Popișter,
  • Kamil Erkan Kabak

摘要

The paper presents an exploratory investigation concerning the usage of AI tools in automotive companies in order to streamline their risk management processes. A risk identification procedure is performed at organizational and process levels, and a comparative analysis is undertaken between the classical approach for developing proper mitigation measures and the AI-supported manner of doing the same. Some of the most popular tools in this field are employed and studied, such as large language models, data analytics and knowledge representation. The differences and changes are analyzed from the point of view of their effectiveness, efficiency and adaptability within the existing manufacturing frameworks in the automotive industry.