AI-Driven Sorting Algorithms: Innovations and Applications in Big Data

Sorting algorithms are at the core of data management processes, enabling efficient organization and retrieval of information. However, the fast expansion of Big Data introduces challenges that traditional sorting algorithms need help to address, such as scalability, adaptability, and processing speed. This research delves into AI-driven sorting algorithms, exploring their ability to revolutionize data processing through intelligent decision-making, real-time adaptability, and enhanced scalability. Innovations such as neural network-guided sorting, reinforcement learning-based optimization, and hybrid AI-traditional models are examined in-depth. Applications of these technologies are highlighted in industries such as healthcare, finance, logistics, and social media analytics. The findings underscore AI's potential to transform sorting methodologies and adapt to the ever-growing demands of the digital era, providing a roadmap for future research and applications.