Agentic AI–Driven API Security and Risk Management in Cloud CI/CD Pipelines for Healthcare SAP Systems

Abstract

Healthcare organizations increasingly deploy SAP systems through cloud-based CI/CD pipelines to achieve agility and scalability; however, these pipelines expose critical application programming interfaces (APIs) to evolving security threats and operational risks. Traditional API security mechanisms are largely reactive and insufficient for complex, fast-paced healthcare cloud environments. This paper proposes an Agentic AI–driven approach for API security and risk management within cloud CI/CD pipelines for healthcare SAP systems. The proposed framework employs autonomous AI agents to continuously monitor API behavior, analyze deployment metadata, and apply predictive analytics to identify security vulnerabilities, compliance risks, and anomalous access patterns before production release. By embedding intelligence directly into CI/CD workflows, the model enables proactive risk mitigation, automated policy enforcement, and adaptive security responses aligned with healthcare regulatory requirements. Experimental analysis demonstrates improved threat detection accuracy, reduced security incidents, and enhanced deployment reliability when compared to conventional CI/CD security practices. The results highlight the effectiveness of agentic AI in strengthening API security, improving risk awareness, and supporting resilient SAP deployments in healthcare cloud ecosystems.