Year: 2025
Type: article
Abstract: In today's dynamic markets and project environments, risk management has become one of the critical components of successful project management.Traditional risk assessment and management methods often fail to account for the dynamics of modern business and may be limited by human errors and subjectivity.Artificial Intelligence (AI) offers new opportunities for forecasting, evaluating, and managing risks, providing greater accuracy and adaptability in this process [1,2].One of the key aspects of implementing AI in risk management is its ability to predict potential risks in the early stages of a project.Using machine learning (ML), AI can analyze large volumes of historical project data and uncover hidden patterns and trends that may indicate potential threats.Predictive algorithms enable real-time analysis of current project conditions, identifying anomalies or deviations that may signal risks [3,4].For instance, studies show that using AI for risk forecasting in construction projects can reduce unexpected delays by 30% [5].This approach is also suitable for IT projects, where risks may involve requirement deviations, market changes, or technical issues [6].AI also enables the automation of risk management processes, including assessment and monitoring.Using cognitive algorithms, AI can continuously evaluate risks, automatically updating information on the project's status based on new data.This approach significantly reduces the time required for information processing and allows for more rapid responses to changes [7].AI also facilitates optimizing resource allocation in a project based on risk probability assessments, reducing costs and minimizing losses from risky events [8].Integrating AI into risk management models, such as the "Three Lines of Defense" (3LoD) model (Fig. ), improves the organization's overall resilience to risks.This model integrates AI into three lines: operational control, risk management, and independent audit [9].For example, the first line of defense-operational controlutilizes AI to automate operational monitoring and identify potential problems early.The second line-risk management-uses AI to analyze and evaluate threats, while the third line-independent audit-applies AI to assess risk management effectiveness objectively [10.1].Fig. -Diagram description of the 3LoD model [10.2]
Authors: Plakhov, V., Dotsenko, N.
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7197106619