Over the last decade, advances in AI and Machine learning accelerated, and the adoption of IoT and Big Data created a perfect environment for this next generation of IT-OT systems. Data centers are now pressured and needed to process challenging AI-intensive workloads while becoming more sophisticated and agile to address other important concerns such as power consumption and personalization of customer requirements including cost management. This brings up the necessity to optimize the current infrastructure handling techniques of the IoT platforms to adapt to the new nature of the IoT data including “computing, storage, and networking”. In this book chapter, we propose a novel technique to enhance IoT data platforms to optimize the whole ecosystem performance for read and write intensive applications. This approach uses AI techniques including small and large models to adapt to this new era of consuming digital transformation generated data and get the most out of it in near real-time.