AI powered IT Networks and the Implementation of advanced Sustainable Infrastructure Solutions to Enterprise Systems globally

This paper suggested a Smart Enterprise AI Framework, which combines cybersecurity monitoring with renewable energy prediction to aid intelligent enterprise operations. Several machine learning systems were designed and integrated into a single system that is able to produce real-time insights in both security and sustainability realms. The intrusion detection model was found to be highly effective in detecting abnormal network behavior, revealing that machine learning is an effective tool in proactive cyber defense. The ensemble learning methods were suitable to model the complex patterns of the environment and time as the renewable energy forecasting models generated reliable predictions. The hybrid system was able to produce concurrent results on both security conditions and energy generation, which indicates the possibility of multi-domain AI to contribute to data-driven decision-making in the contemporary business. In general, the findings demonstrate that the framework in question has the potential to improve reliability, security, and sustainability of enterprises. Further developments in future work may be directed towards the addition of real-time streaming data, deep learning methods, and IoT-based monitoring to enhance the system scalability, prediction accuracy, and ability to be deployed in the real world.

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