Autonomous DevOps-Driven Zero-Trust AI Governance for Rural Healthcare and Financial Cloud Environments with SAP Optimization
DOI:
https://doi.org/10.15662/IJRAI.2024.0706025Keywords:
Zero-Trust Security, AI Governance, Rural Healthcare Systems, Financial Cloud Platforms, Autonomous DevOps, Threat Detection, OptimizationAbstract
The increasing reliance on cloud-powered intelligent systems in both rural healthcare and financial platforms demands a secure, scalable, and resilient governance framework. This work proposes a Zero-Trust AI Governance model that integrates continuous authentication, encrypted data pipelines, and strict access control to mitigate insider and external threats. The framework leverages autonomous DevOpsdefense mechanisms, including real-time anomaly detection, predictive risk scoring, and automated policy enforcement across distributed environments. To support resource-constrained rural environments, the model incorporates lightweight AI inference, edge computing, and secure hybrid-cloud orchestration. Additionally, optimization strategies, such as adaptive workload balancing, AI-driven configuration tuning, and performance-aware scaling, enhance operational efficiency without compromising trust or compliance. The proposed architecture aligns with regulatory frameworks including HIPAA, GDPR, and financial cybersecurity standards to ensure ethics, accountability, and transparency. Overall, the model ensures a unified security posture that strengthens operational resilience, fosters data integrity, and enables trustworthy AI deployment across healthcare and financial ecosystems.
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