Optimizing SAP Workflow Orchestration across Cloud Environments Using Retrieval-Augmented Generation and Zero Trust Access Control
DOI:
https://doi.org/10.64235/36j28373Keywords:
SAP workflow orchestration, Retrieval-Augmented Generation, Zero Trust Access Control, cloud computing, enterprise resource planning, generative artificial intelligence, workflow automation, identity and access management, hybrid cloud, enterprise security, intelligent process automation.Abstract
The increasing adoption of cloud computing and enterprise resource planning systems has intensified the need for intelligent,
secure, and efficient workflow orchestration across distributed business environments. SAP workflows frequently involve complex
dependencies among enterprise applications, business processes, authorization mechanisms, and heterogeneous cloud services,
creating challenges related to operational efficiency, contextual decision-making, security, and interoperability. Conventional
workflow orchestration relies heavily on predefined rules and manual configuration, limiting its ability to respond dynamically
to changing business requirements and operational conditions. This study investigates an integrated framework combining
Retrieval-Augmented Generation (RAG), intelligent workflow orchestration, and Zero Trust Access Control to optimize SAP
workflow execution across cloud environments. The proposed approach uses enterprise knowledge repositories to retrieve
relevant process documentation, configuration records, and operational policies, enabling large language models to generate
context-aware workflow recommendations. Zero Trust principles strengthen security through continuous identity verification,
least-privilege authorization, contextual access evaluation, and policy enforcement. The research methodology adopts a
quantitative experimental design to evaluate workflow completion time, execution accuracy, retrieval relevance, authorization
effectiveness, resource utilization, and security resilience. Comparative experiments assess conventional orchestration, RAGassisted
orchestration, and the integrated security-aware framework under varying workload and cloud conditions. The proposed
framework aims to improve operational adaptability, reduce manual intervention, and strengthen governance while maintaining
enterprise security requirements. The study contributes an evaluation-oriented architecture for integrating generative artificial
intelligence with secure SAP workflow management and provides a foundation for trustworthy automation across hybrid and
multi-cloud enterprise environments.
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