AI Driven Multi-Cloud Data Consistency and Security Architecture for Always-On Digital Enterprise Systems
DOI:
https://doi.org/10.15662/IJRAI.2026.0902004Keywords:
Artificial Intelligence, Multi-Cloud Architecture, Data Consistency, Cloud Security, Always-On Enterprise Systems, Predictive Anomaly Detection, Automated Policy Enforcement, Distributed Cloud Management, Compliance, Data SynchronizationAbstract
Modern enterprises increasingly rely on multi-cloud infrastructures to ensure scalability, high availability, and operational flexibility. However, managing data consistency and ensuring robust security across distributed cloud platforms presents significant challenges. Data replication, synchronization delays, heterogeneous security policies, and dynamic workloads complicate traditional management approaches, exposing critical enterprise systems to risks such as data breaches, inconsistencies, and compliance violations.
This research proposes an Artificial Intelligence (AI) driven multi-cloud data consistency and security architecture designed for always-on digital enterprise systems. The framework integrates AI-powered monitoring, predictive anomaly detection, automated data synchronization, and adaptive security policy enforcement. By continuously analyzing transactional patterns, network flows, and system interactions, the architecture identifies potential inconsistencies, predicts security threats, and autonomously enforces corrective actions across multi-cloud environments.
The methodology includes designing the architecture, implementing AI-based data management and security modules, simulating multi-cloud enterprise workloads, and evaluating performance metrics such as data consistency, latency, throughput, security breach detection, and compliance adherence. Results demonstrate that the AI-driven framework significantly improves cross-cloud data consistency, enhances security posture, reduces manual management overhead, and supports uninterrupted operation of critical digital enterprise services. This approach enables enterprises to maintain secure, consistent, and always-on operations while dynamically optimizing resources across multiple cloud platforms.
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