Modernizing Enterprise Systems through Generative AI Autonomous Operations and Cloud-Native Engineering
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Abstract
Enterprise modernization has become a strategic priority for organizations seeking to improve operational efficiency, accelerate innovation, and remain competitive in rapidly evolving digital markets. The convergence of Generative Artificial Intelligence (Generative AI), autonomous operations, and cloud-native engineering has created new opportunities for transforming traditional enterprise systems into intelligent, adaptive, and scalable digital platforms. Generative AI enhances enterprise capabilities by automating content creation, software development, knowledge management, decision support, and customer engagement through advanced natural language processing and machine learning models. Autonomous operations utilize artificial intelligence, predictive analytics, and intelligent automation to monitor, optimize, and manage enterprise infrastructure with minimal human intervention, thereby improving system reliability, reducing operational costs, and enabling proactive issue resolution. Cloud-native engineering provides the architectural foundation for modernization through microservices, containers, Kubernetes orchestration, serverless computing, and Infrastructure as Code, enabling highly scalable, resilient, and flexible enterprise applications. This paper examines the integration of these technologies within modern enterprise architectures and proposes a comprehensive framework for designing intelligent, secure, and cloud-native systems. The framework emphasizes automation, observability, continuous integration and deployment, cybersecurity, governance, and operational resilience. The study concludes that combining Generative AI, autonomous operations, and cloud-native engineering significantly enhances organizational agility, software quality, resource optimization, and business innovation while supporting sustainable digital transformation across diverse enterprise environments.
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