Abstract
Telecommunication network operators face growing pressures from rapidly increasing user numbers, highly diverse operating conditions, and a persistent mandate to reduce costs. In response, the industry has moved beyond initial digital transformation efforts and is now actively leveraging AI- and ML-based intelligence to drive higher levels of automation on the journey toward fully autonomous networks. While these approaches have demonstrated clear value for specific use cases, how they should be integrated and leveraged in networks as scale is an unfolding topic. Based on work in the Focus Group on AI-Native Networks, this talk shares relevant contributions on pertinent use cases, and proposals on how unqiuitious desployment and use of differnet forms of AI in the network can be acheived in a standard, interoperable way.
