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AI-ML Smart Network CapEx - Phase II

URN C25.0.768
Topics AI (Artificial Intelligence), Autonomous networks, Sustainability

Smart CapEx, using AI/ML to automate and optimize access and transport rollouts unlocking 15-25% CapEx efficiency gains while maintaining CX

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This Catalyst aims to improve the CapEx allocation process by addressing the double challenge of forecasting traffic more accurately, and automating and optimizing a network rollout plan that covers the traffic growth while maintaining CX. More accurate traffic forecasts require a user-friendly application to share Marketing’s commercial projections with the Network team, and translate them to the street level for both traditional, and new use cases. Calculating the optimal network rollout will make heavy use of AI algorithms in a Big Data environment, typically on the cloud. The business values are 15-20% CapEx and OpEx savings on the new Network investments and a significant OpEx saving on the existing Network Infrastructure. In this phase we focus on Transport and Core Network Planning, compared to the previous phase, in which we focused on the Radio Access Network. Additionally, this Catalysts will leverage TM Forum’s autonomous architectures by implementing the intent-driven TMF921 Intent Management API. This enhances operators' ability to integrate and automate systems more quickly and effectively, while reducing platform integration costs with legacy systems. It facilitates the adoption of automation through AI, using TMF standard interfaces with legacy adapters.

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Explore the previous phases of this project

AI Smart CapEx for green and efficient network investments

Team members

EITC  (DU) logo
Champion
Iquall Networks Inc logo
Locatium.AI logo
Orange logo
Champion
Saudi Telecom Company logo
Champion

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