Integrating Generative AI and Machine Learning in Cloud-Based ERP Systems for Real-Time SAP Optimization
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Abstract
The rapid evolution of cloud computing and artificial intelligence (AI) has transformed enterprise resource planning (ERP) ecosystems, enabling organizations to achieve intelligent automation and real-time decision-making. This paper presents an integrated framework that combines Generative AI and Machine Learning (ML) within cloud-based ERP systems to enhance real-time SAP optimization. The proposed architecture leverages AI-driven predictive analytics and generative modeling to automate data processing, forecasting, and workflow adaptation across dynamic enterprise environments. By deploying the framework in a scalable cloud infrastructure, it ensures seamless integration between SAP modules, ERP databases, and external business services. Real-time synchronization enables proactive decision-making, anomaly detection, and continuous performance improvement. The framework also incorporates secure APIs, containerized microservices, and advanced ML pipelines to ensure interoperability, data consistency, and operational resilience. Experimental validation demonstrates significant gains in system responsiveness, process efficiency, and predictive accuracy. This research establishes a pathway toward intelligent, cloud-native ERP ecosystems powered by generative AI for modern digital enterprises.
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