Cloud-Native SAP Intelligence: A Machine Learning Framework for Ethical Automation and Risk-Resilient Business Operations
DOI:
https://doi.org/10.15662/IJRAI.2023.0605006Keywords:
SAP Cloud, cloud-native architecture, machine learning, ethical automation, risk management, explainable AI, RPA, governance, compliance, data privacyAbstract
In modern enterprises, the convergence of cloud-native architectures, SAP ecosystems, and machine learning (ML) capabilities is transforming how organizations automate and manage business operations. However, while automation drives efficiency and responsiveness, it simultaneously introduces complex ethical, security, and governance risks. This paper presents a Cloud-Native SAP Intelligence Framework that integrates machine learning with ethical automation principles and risk resilience for large-scale business operations. The framework aims to operationalize ML models within SAP Cloud environments securely and responsibly, ensuring transparency, explainability, and compliance with corporate governance and regulatory mandates.
The proposed architecture combines four layers: (1) Data Intelligence Layer, which curates enterprise data pipelines with metadata tagging, lineage, and privacy controls; (2) Ethical ML Layer, embedding bias detection, fairness auditing, and explainable AI (XAI) models; (3) Automation Control Layer, orchestrating robotic process automation (RPA) and ML-driven workflows integrated with SAP modules; and (4) Governance and Risk Layer, enforcing security, identity management, and continuous compliance through automated controls and monitoring.
A prototype implementation in SAP Cloud Platform (SCP) is demonstrated for automating procurement and inventory management processes using supervised and reinforcement learning algorithms. Evaluation results reveal improved process accuracy, reduction in SoD violations, and measurable compliance alignment with GDPR and ISO 27001 principles. This framework provides an enterprise-ready approach to aligning automation and ML with ethical governance, ensuring that SAP-driven automation remains transparent, auditable, and resilient against operational and ethical risks.
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