Generative AI for Enterprise Integration Security across Cloud Environments through Automated Documentation and Troubleshooting

Abstract

Enterprise integration across cloud environments enables organizations to connect applications, databases, APIs, and distributed services while maintaining continuous information exchange. However, increasingly complex integration architectures introduce security risks, configuration errors, documentation inconsistencies, and operational disruptions. Generative artificial intelligence (GenAI) offers opportunities to address these challenges through automated technical documentation, intelligent troubleshooting, and context-aware security analysis. This study proposes a GenAI-based framework for strengthening enterprise integration security across heterogeneous cloud platforms. The framework combines retrieval-augmented generation, automated configuration analysis, log interpretation, security policy validation, and incident resolution recommendations. By processing integration specifications, system logs, API definitions, configuration files, and security policies, the proposed approach generates contextual documentation, identifies potential vulnerabilities, and recommends corrective actions. Retrieval mechanisms ground generated responses in approved enterprise knowledge sources, while access controls and human verification reduce the risks of unauthorized disclosure and unsafe automated changes. The research adopts a quantitative experimental methodology to compare conventional integration management with GenAI-assisted documentation and troubleshooting. Evaluation metrics include documentation accuracy, troubleshooting success rate, vulnerability detection precision, incident resolution time, response latency, and operational overhead. The study also examines prompt injection, hallucinated recommendations, sensitive information exposure, and inconsistent cloud configurations. The proposed framework aims to improve integration transparency, reduce manual maintenance effort, and strengthen security governance across distributed enterprise systems while preserving accountability, reliability, and human oversight.