The use of AI in the process of quantitative risk assessment of logistics entities

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This analysis reveals the role of AI in enhancing risk assessment in logistics, suggesting improved accuracy and efficiency.

AI optimizes logistics risk assessment, improving forecasting accuracy and reducing costs with automation.
Machine learning methods like neural networks and decision trees enhance the analysis of data in real time.
Integrating diverse data sources enables a comprehensive evaluation of operational and economic risks.
Despite benefits, AI implementation faces challenges such as data quality, ethical issues, and resource demands.

Kirovych et al. (2025) studied this question.

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