AI-Enhanced Cloud Management and Digital Payment Ecosystem: Reinforcement Learning and Quantum Circuit Optimization in SAP S/4HANA Environments
DOI:
https://doi.org/10.15662/IJRAI.2025.0806009Keywords:
Artificial Intelligence (AI), Reinforcement Learning (RL), Quantum Circuit Optimization, SAP S/4HANA, Cloud Management, Digital Payments, Multi-Cloud Integration, BERT, Quantum Computing, Enterprise Resource Planning (ERP), Intelligent Automation, Cryptographic Optimization, Next-Generation Financial SystemsAbstract
The convergence of Artificial Intelligence (AI), cloud computing, and digital finance has transformed enterprise ecosystems into intelligent, adaptive, and data-driven infrastructures. This study proposes an AI-enhanced cloud management and digital payment framework that integrates Reinforcement Learning (RL) and Quantum Circuit Optimization within SAP S/4HANA environments. The proposed system leverages RL agents to dynamically allocate cloud resources, optimize transaction throughput, and minimize operational latency across multi-cloud architectures. Simultaneously, quantum-inspired optimization techniques are applied to accelerate payment encryption, fraud detection, and decision-making processes in high-frequency financial transactions.
Through the integration of BERT-based natural language understanding (NLU), the framework further enhances semantic data processing and intelligent automation within enterprise workflows. The hybrid AI–quantum approach facilitates real-time adaptability, cost efficiency, and heightened security in next-generation digital payment ecosystems. Experimental simulations demonstrate significant performance improvements in data integration speed, transaction reliability, and predictive accuracy compared to traditional cloud management methods. The results highlight the potential of combining Reinforcement Learning, Quantum Computing, and SAP S/4HANA for building future-ready, autonomous enterprise systems.
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