Artificial Intelligence Applications in Risk Management Within Integrated Management Systems: A Review

Abstract

Artificial intelligence is increasingly used in all fields, especially in the area of risk management within Integrated Management Systems (IMS). The paper aims to highlight the role of artificial intelligence (AI) in risk management, therefore providing opportunities for industrial organizations, offering significant advantages for improving the efficiency and accuracy of risk assessment and mitigation processes. By using advanced AI technologies, organizations can anticipate and manage risks more effectively, therefore optimizing operational performance and resilience. We reviewed and explored the main applications of AI implementation, risk management, the barriers encountered, and the advantages and disadvantages of using AI. A holistic analysis of IMS risk management, identification and assessment, operational efficiency of routine tasks, real-time data analysis, and immediate decision-making using AI was performed. The methods and technologies used are analyzed, along with the associated challenges, providing a comprehensive perspective on the impact of AI in industrial organizations. We conclude that the use of AI addresses challenges related to data quality, model interpretation, ethical issues, and high costs of implementation and management, which require qualified personnel. Also, we conclude that the use of AI in risk management for IMS presents significant opportunities for industrial organizations, including enhanced process monitoring, rapid information analysis, and swift response to emerging risks. This enables the optimization of risk management strategies, ultimately leading to increased operational safety and efficiency.

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