Adaptive Enterprise Computing Framework Using Intelligent AI Agents SAP Systems and Hybrid Multi Cloud Architecture
DOI:
https://doi.org/10.15662/IJARCST.2026.0903016Keywords:
Adaptive Enterprise Computing, Artificial Intelligence, Intelligent AI Agents, SAP S/4HANA, Hybrid Multi-Cloud, Agentic AI, Intelligent Automation, Enterprise Cybersecurity, DevSecOps, Predictive Analytics.Abstract
The rapid evolution of Artificial Intelligence (AI), cloud computing, and enterprise digital transformation has significantly changed the way organizations manage business operations and enterprise resource planning systems. Modern enterprises increasingly rely on SAP platforms, intelligent automation, predictive analytics, and hybrid multi-cloud environments to improve operational efficiency, cybersecurity, scalability, and business agility. However, traditional enterprise architectures continue to experience limitations such as fragmented data management, isolated business applications, manual workflows, inconsistent security policies, and limited interoperability among distributed cloud services. These challenges hinder real-time decision-making, intelligent resource optimization, and adaptive business operations.
This paper proposes an Adaptive Enterprise Computing Framework that integrates Intelligent AI Agents, SAP enterprise systems, and Hybrid Multi-Cloud Architecture to establish a secure, scalable, and autonomous enterprise ecosystem. The proposed framework utilizes Agentic AI, Generative AI, machine learning, predictive analytics, intelligent automation, and cloud-native technologies to continuously monitor enterprise activities, optimize SAP business processes, automate operational workflows, and strengthen enterprise cybersecurity. Intelligent AI agents collaboratively perform reasoning, planning, security monitoring, predictive analysis, and workflow orchestration while interacting with SAP S/4HANA and cloud-based enterprise applications. Hybrid multi-cloud deployment enables dynamic workload distribution across private and public cloud infrastructures while ensuring high availability, regulatory compliance, disaster recovery, and business continuity.
The proposed architecture incorporates Zero Trust Security, Identity and Access Management, DevSecOps, MLOps, container orchestration, and real-time enterprise monitoring to provide adaptive computing capabilities. Experimental analysis demonstrates that the proposed framework significantly improves automation efficiency, enterprise scalability, cybersecurity resilience, decision accuracy, cloud resource utilization, and operational performance compared with conventional enterprise architectures. The framework offers a comprehensive roadmap for organizations seeking intelligent, secure, and adaptive enterprise transformation through AI-enabled computing and hybrid multi-cloud technologies.
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