Role of 6G and AI-Guided Network Slicing in Advancing Enterprise and Consumer Technology Transmission Capabilities

The rapid evolution of enterprise and consumer technology networks necessitates advanced solutions to meet the growing demands for high-speed, reliable, and adaptive data transfer efficiency. The research explores the use of 6G communication technology and AI-guided network slicing to optimize performance in enterprise and consumer technology infrastructures. The Greater Cane Rat Tuned Efficient Deep Neural Network (GCR-EDNN) model forecasts network demand and maximizes resource distribution. AI-guided network slicing dynamically allocates resources according to specific needs, improving performance, security, and scalability. Traffic data is collected from various patterns, including high-load video streaming and device communication, to optimize performance and security. The results demonstrate that the proposed framework leads to significant improvements in data transmission performance for various nodes (200, 400, 600, 800, and 1000), including enhanced throughput (0.985), network lifetime (35820), and energy consumption (0.29) achieved for 200 nodes. These findings highlight that AI-driven network slicing in 6G networks has the potential to revolutionize both enterprise digital infrastructure and consumer technology ecosystems, paving the way for smarter and more connected networks.