A Governance-Centric AI Framework for Cloud-Native DevOps Automation in Healthcare Applications with Secure Mobile Systems and Network-Enabled Compliance
DOI:
https://doi.org/10.15662/IJARCST.2023.0605013Keywords:
Unified AI Governance, Cloud-Native Security, Enterprise Automation, Mobile System Security, Compliance Automation, Network Governance, Policy-as-Code, AI-Driven GRC, Zero Trust ArchitectureAbstract
The rapid adoption of cloud-native architectures, mobile enterprise systems, and AI-driven automation has introduced unprecedented challenges in governance, security, compliance, and operational transparency. Traditional governance models are fragmented, reactive, and insufficient to manage the dynamic, distributed, and autonomous nature of modern enterprise environments. This paper proposes a Unified Governance-Centric Artificial Intelligence (UG-AI) Framework that integrates governance, risk management, compliance (GRC), security, and operational intelligence into a single AI-orchestrated control layer. The framework leverages machine learning, policy-as-code, continuous compliance monitoring, and adaptive risk assessment to ensure secure automation across cloud-native platforms, mobile ecosystems, and network-enabled infrastructures. By embedding governance principles directly into AI decision-making processes, the framework enables proactive compliance enforcement, real-time threat mitigation, and auditable automation workflows. The proposed approach addresses regulatory complexity, data sovereignty, identity management, and cross-platform interoperability while supporting scalability and resilience. This research contributes a conceptual architecture, governance workflow model, and implementation strategy aimed at enhancing enterprise trust, regulatory alignment, and operational efficiency in next-generation digital ecosystems.References
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