Tailoring AI and Cloud in Modern Enterprises to Enhance Enterprise Architecture Governance and Compliance

Artificial Intelligence (AI) and cloud computing technology implementation in modern enterprises helps them operate more flexibly and scalable with optimum results on the efficiency scales. The integration of these technologies into the Enterprise Architecture (EA) causes governance and compliance management as well as risk management problems. The research uses Multi-Agent Deep Reinforcement Learning (MADRL) to optimize cloud infrastructure operations by fulfilling both enterprise governance standards and industry regulations. The developed intelligent system learns to generate optimal outcomes, which simultaneously produce the highest compliance benefits with minimum operational expenses and upper-level performance improvement through multiple decision sequences. System metric collection starts the methodology, which is then followed by training a (MADRL) model for effective resource management and governance policy enforcement. An intelligent system supports adherence to security regulations, efficient workloads and compliance by rewarding good behavior, but punishes those who do not comply or whose results are ineffective. During its 100 training sessions, the model develops its decision-making capabilities, and assessment happens by evaluating its response times and efficiency costs while analyzing reward values. The study verifies MADRL’s possibility to automate cloud operations while enhancing regulatory compliance as well as operational performance.