Integrated Artificial Intelligence Framework for Enterprise Cloud Modernization and Intelligent Threat Management Systems

Abstract

Enterprise organizations are rapidly adopting cloud computing to improve operational efficiency, scalability, and digital transformation. However, cloud modernization introduces complex cybersecurity challenges that require intelligent, adaptive, and automated defense mechanisms. Artificial Intelligence (AI) has emerged as a transformative technology capable of enhancing cloud modernization while strengthening threat detection, incident response, and risk management. This study proposes an integrated artificial intelligence framework that combines cloud modernization strategies with intelligent threat management systems to achieve secure, resilient, and efficient enterprise cloud environments. The framework incorporates machine learning, deep learning, natural language processing, behavioral analytics, and predictive security models to automate infrastructure management and identify sophisticated cyber threats in real time. The proposed approach emphasizes continuous monitoring, intelligent workload optimization, zero-trust security principles, and automated incident response to improve organizational resilience against evolving cyberattacks. The research adopts a qualitative methodology supported by an extensive review of existing literature, industry best practices, and conceptual framework development. The findings indicate that integrating AI into enterprise cloud ecosystems significantly enhances resource utilization, minimizes operational risks, reduces security incidents, and supports regulatory compliance. Furthermore, AI-driven threat intelligence enables organizations to proactively identify vulnerabilities and mitigate emerging attacks before they affect critical business operations. The proposed framework offers a comprehensive foundation for secure cloud modernization and sustainable digital transformation across diverse enterprise environments