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Cloud-Enabled Enterprise Architecture using Generative AI Event-Driven Platforms and Predictive Cyber Intelligence

Abstract

The rapid advancement of digital technologies has transformed enterprise architecture into a dynamic and intelligent ecosystem capable of supporting continuous innovation, automation, and secure business operations. The emergence of Generative Artificial Intelligence (GenAI), event-driven platforms, and predictive cyber intelligence has significantly enhanced the ability of organizations to manage complex digital infrastructures while improving operational efficiency and cybersecurity resilience. This study proposes a next-generation enterprise architecture that integrates Generative AI with event-driven computing models and predictive cyber intelligence to create adaptive, scalable, and secure enterprise environments. The architecture facilitates real-time decision-making, autonomous process automation, intelligent resource allocation, and proactive threat detection through continuous analysis of enterprise events and cyber risk indicators. Event-driven platforms enable rapid communication among distributed services, while Generative AI enhances knowledge management, software development, customer engagement, and business analytics. Predictive cyber intelligence strengthens organizational security by forecasting emerging threats, identifying vulnerabilities, and automating incident response before attacks cause significant damage. The proposed architecture supports cloud-native deployment, hybrid infrastructure, interoperability, governance, regulatory compliance, and business continuity. Furthermore, it enables organizations to respond effectively to evolving market conditions and technological disruptions while maintaining trust, resilience, and sustainable digital transformation. The integration of intelligent automation with predictive cybersecurity establishes a robust enterprise architecture capable of supporting future digital enterprises operating within increasingly interconnected and data-intensive environments

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