In the telecom industry, AI, ML and Neural Networks have some substantial business use cases, and their adoption continues to grow. These technologies have proven to be transformative in optimizing network performance, enhancing customer experience, and driving operational efficiency for Nokia and its customers.

Below are some examples:

Network Optimization: AI and ML are going to be extensively used for optimizing network performance. These technologies enable fault detection, and automated resolution, leading to increased network reliability and reduced downtime thereby enhancing the overall quality of service and Customer Experience.

Predictive Analytics: AI and ML are instrumental in predictive analytics for anticipating network congestion, equipment failures, and other issues. Nokia plans to use these technologies to forecast demand, plan network upgrades, and prevent potential disruptions, contributing to a more proactive and resilient network infrastructure.

While AI, ML, and Neural Networks have made considerable strides in the telecom industry, it's important to note that innovation is an ongoing process. The industry is continually exploring new applications and refining existing use cases. I hope this is useful.

19 January, 2024 16:41

Correct sir, as business cases are evolving around 5G an ORAN. AL/ML will help in increasing the radio network performance across all layers of the network by embedding intelligence directly on the hardware or as applications on top of the network.

In today's scenario as energy efficiency is the top agenda for CSPs.

Artificial Intelligence can help optimize the sustainability of 5G networks by reducing energy wastage, and thus their carbon footprint.
o AI systems can learn the usage patterns of networks and automatically turn off power for components when not needed.
o AI algorithms can help optimize RF propagation and its associated power levels.

21 January, 2024 15:02