Integrating Gray Relational Analysis with AI-Augmented Automation and Ethical Governance in SAP Cloud: A Machine Learning Framework for Security, Risk, and Software Maintenance Optimization
DOI:
https://doi.org/10.15662/IJRAI.2023.0606015Keywords:
Gray Relational Analysis (GRA), AI-Augmented Automation, SAP Cloud, Machine Learning, Ethical Governance, Security Optimization, Risk Management, Software Maintenance, Predictive Analytics, Responsible AI, Cloud Compliance, Enterprise Automation, Decision IntelligenceAbstract
As enterprises increasingly migrate critical operations to SAP Cloud platforms, ensuring robust security, effective risk management, and efficient software maintenance has become vital. This study introduces a comprehensive framework that integrates Gray Relational Analysis (GRA) with AI-augmented automation and ethical governance principles to optimize system reliability and compliance at scale. By combining machine learning (ML) models with GRA-based multi-factor evaluation, the proposed framework enables precise correlation analysis between operational parameters, security indicators, and maintenance efficiency metrics within SAP Cloud environments. The approach supports data-driven prioritization of risk factors and automation of remediation strategies through intelligent policy orchestration. Ethical governance mechanisms—rooted in transparency, accountability, and fairness—are embedded to ensure that AI-driven decision-making aligns with global regulatory and corporate responsibility standards. Leveraging SAP-native technologies such as SAP AI Core, SAP GRC, and SAP Build Process Automation, the framework enhances anomaly detection, predictive maintenance, and compliance monitoring. Empirical results demonstrate that integrating GRA with AI automation improves accuracy in risk prediction, reduces system downtime, and strengthens ethical oversight in automated processes. This research contributes a scalable and explainable model for responsible AI governance in cloud ecosystems, advancing both the theoretical and practical understanding of secure, ethical, and intelligent enterprise automation.References
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