Application of Artificial Intelligence in Risk and Reliability Management of IT systems in a DevSecOps Approach

The paper analyses the use of artificial intelligence (AI) in the risk and reliability management of IT systems in the context of the DevSecOps approach, which integrates security into the software lifecycle. In response to the growing number of cyber incidents and the limitations of traditional methods, specific AI tools and algorithms used in the automation of security tests, IT infrastructure monitoring and failure prediction were presented. The research was based on a review of 42 scientific publications and the analysis of empirical data from five IT organizations, using quantitative and qualitative methods (surveys, interviews, case studies). The results indicate that the integration of AI in DevSecOps increases the effectiveness of threat detection by 35%, reduces incident response time by 40%, and improves the reliability of IT systems. Key challenges such as data quality, model interpretability, and regulatory compliance were also identified. The article formulates recommendations for DevSecOps teams and technology decision-makers and indicates directions for further research in the field of ethics, interoperability, and auditability of AI systems.