Artificial Intelligence Strategies For Securing SAP Cloud Systems In DevOps-Driven Enterprise Environments

This review article evaluates the implementation of defensive artificial intelligence to secure SAP cloud systems within high-velocity, DevOps-driven enterprise environments. As organizations transition to cloud-native platforms like RISE with SAP and the Business Technology Platform, traditional perimeter-based security and manual patching cycles are becoming obsolete against automated, AI-generated threats. The research explores \\\"shift-left\\\" security strategies, where AI-augmented code analysis and contextual vulnerability prioritization are embedded directly into the CI/CD pipeline to catch flaws at the point of creation. A primary focus is placed on autonomous threat hunting and anomaly monitoring, leveraging unsupervised machine learning to establish behavioral baselines for complex transactional patterns and administrative access. Furthermore, the paper analyzes the role of AI in enforcing Zero Trust architectures through dynamic, risk-based identity governance and conditional access. The study addresses critical implementation constraints, including the \\\"Shared Responsibility\\\" model in cloud ERP and the necessity for explainable AI to satisfy forensic audit requirements. The review concludes by outlining the roadmap toward the \\\"Autonomous SOC,\\\" where agentic AI and self-healing infrastructure-as-code provide continuous, real-time resilience for mission-critical SAP landscapes in the 2026 threat environment.