Generative AI Enabled Agentic Enterprise Architectures for Autonomous Digital Operations and Cloud Native Intelligence
Abstract
Generative Artificial Intelligence (AI) is transforming enterprise computing by enabling intelligent, autonomous, and adaptive digital operations across cloud-native environments. The emergence of agentic AI systems, characterized by autonomous decision-making, reasoning, planning, and execution capabilities, has created new opportunities for enterprises seeking operational efficiency, resilience, scalability, and innovation. Agentic enterprise architectures integrate large language models, machine learning frameworks, cloud-native platforms, microservices, orchestration tools, and intelligent automation mechanisms to establish self-governing digital ecosystems. These architectures support autonomous workflows, proactive incident management, dynamic resource optimization, predictive analytics, and real-time business decision-making. Cloud-native intelligence further enhances these capabilities by leveraging containerization, serverless computing, Kubernetes orchestration, edge computing, and distributed data platforms to deliver scalable and resilient services. This study examines the conceptual foundations, technological components, and operational implications of generative AI-enabled agentic enterprise architectures. It explores existing literature on autonomous systems, AI-driven enterprise transformation, intelligent automation, and cloud-native computing. The research adopts a qualitative and conceptual methodology to analyze emerging architectural models, implementation strategies, governance mechanisms, and organizational outcomes. Findings suggest that integrating generative AI with cloud-native infrastructures enables enterprises to achieve higher levels of autonomy, agility, and operational intelligence while addressing challenges related to security, ethics, governance, interoperability, and trust. The study contributes to understanding future enterprise architectures supporting autonomous digital operations and intelligent business ecosystems
Article Information
Journal |
International Journal of Emerging Trends in Engineering and Management Research |
|---|---|
Volume (Issue) |
Vol. 10 No. 6 (2025): International Journal of Emerging Trends in Engineering and Management Research (IJETEMR) |
DOI |
|
Pages |
18891-18898 |
Published |
November 11, 2025 |
| Copyright |
All rights reserved |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Antonio Brogi (%2025). Generative AI Enabled Agentic Enterprise Architectures for Autonomous Digital Operations and Cloud Native Intelligence. International Journal of Emerging Trends in Engineering and Management Research , Vol. 10 No. 6 (2025): International Journal of Emerging Trends in Engineering and Management Research (IJETEMR) , pp. 18891-18898. https://doi.org/10.15662/ijetemr.2025.1006001 |
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