AI Enabled Cloud Architectures for Intelligent Secure and Resilient Enterprise Systems with Autonomous Decision Intelligence
DOI:
https://doi.org/10.15680/IJCTECE.2024.0706026Keywords:
AI-enabled cloud, autonomous decision intelligence, enterprise systems, cybersecurity, adaptive architecture, resilience, machine learning, deep learning, intelligent systems, cloud scalabilityAbstract
The increasing complexity of enterprise operations and the exponential growth of data have made traditional IT infrastructures insufficient to support modern organizational needs. AI-enabled cloud architectures have emerged as a transformative solution, enabling intelligent, secure, and resilient enterprise systems with autonomous decision-making capabilities. This research explores the design and implementation of AI-driven cloud architectures that integrate advanced machine learning and deep learning algorithms to enhance enterprise efficiency, security, and adaptability. Autonomous decision intelligence allows systems to analyze large volumes of data in real time, predict operational trends, detect anomalies, and implement corrective actions without human intervention. Cloud computing provides a scalable, distributed, and flexible platform for deploying these intelligent systems, ensuring seamless resource management and operational continuity. Security mechanisms, enhanced with AI, proactively detect cyber threats and respond dynamically to protect sensitive enterprise assets. Resilience is achieved through self-healing architectures capable of maintaining performance during failures or unexpected disruptions. This study proposes a comprehensive framework for AI-enabled cloud architectures that combines autonomous intelligence, adaptive scalability, and robust cybersecurity to support enterprise digital transformation. The findings highlight that such architectures enable organizations to optimize decision-making, reduce operational risks, enhance system reliability, and achieve sustainable, intelligent enterprise operations.
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