Autonomous Cloud Intelligence Systems Powered by Artificial Intelligence for Secure Data Platforms and Decision Excellence
DOI:
https://doi.org/10.15662/IJEETR.2026.0802179Keywords:
autonomous cloud systems, artificial intelligence, secure data platforms, decision intelligence, cloud security, zero trust, machine learning, data governance, anomaly detection, explainable AIAbstract
Autonomous cloud intelligence systems represent a transformative evolution in enterprise computing, combining artificial intelligence (AI), cloud infrastructure, and advanced analytics to enable secure, self-managing data platforms and enhanced decision-making capabilities. These systems leverage AI-driven automation to manage data pipelines, optimize resource allocation, detect anomalies, and ensure data security in real time. As organizations increasingly rely on data-intensive applications, the need for intelligent cloud systems capable of autonomous operation and resilience has become critical. This paper explores the architecture, design principles, and implementation strategies of AI-powered autonomous cloud intelligence systems, emphasizing their role in securing data platforms and achieving decision excellence. The proposed framework integrates machine learning, deep learning, and reinforcement learning techniques with cloud-native technologies such as microservices, containerization, and serverless computing. Security is addressed through zero-trust models, encryption mechanisms, and AI-based threat detection systems. Additionally, the study highlights the importance of data governance, privacy preservation, and explainable AI in ensuring trust and compliance. Through comprehensive analysis and evaluation, this work demonstrates how autonomous cloud intelligence systems can enhance operational efficiency, reduce human intervention, and provide accurate, data-driven insights, ultimately enabling organizations to achieve strategic and competitive advantages in dynamic environments.References
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