The Foundation for Network Monetization
Using network planning as a representative use case, we can explore the multiple factors that contribute to building an effective and scalable network infrastructure.
autonomous network. This serves as the intelligent backbone of modern CSPs, enabling resilient, efficient, and revenue-generating 5G ecosystems.
Why have an AI embedded core
design framework?
AIOps can be deployed to help reduce the operational burden on CSPs by automating routine tasks, proactively identifying and resolving issues, and optimizing network performance. This can not only enhance efficiency but also improve service reliability and customer satisfaction.
Having context awareness is crucial for enabling network components to make the right decisions on their own. This level of accuracy and relevance is often difficult to achieve using external
tools, as they may lack the system's internal perspective and real-time context. An in-built framework can act as a living, learning planning assistant, helping streamline decision-making,
improve accuracy, and accelerate time-to-deploy. Analytics and automation within this framework make it real-time actionable, paving the way towards an autonomous network.
Some of the advantages of AI embedded design in network components are enumerated below (see Figure 1).
Figure 1: Advantages of AI embedded design in network components
What is the starting point of AIOps in a CSP network?
While Radio Access Network (RAN) and Transport make up the majority of the network infrastructure in terms of scale and cost, it is the core that serves as the enabler of differentiated services,
allowing CSPs to unlock new revenue streams and monetize the network more effectively. Given that the core represents a smaller portion of the overall network, it presents a manageable and
strategic starting point for piloting AIOps initiatives. Successful implementation in the core can then be scaled to the broader RAN and Transport domains, enabling a phased and low-risk AIOps
deployment.
Network planning as a representative use case
Using network planning as a representative use case, we can explore the multiple factors that contribute to building an effective and scalable network infrastructure. Network planning is a strategic process that involves decisions spanning various functional domains within the network ecosystem. These include traffic analysis, which helps identify current usage patterns and anticipate future demand, capacity planning, which helps the network handle projected loads without degradation, and QoS, which prioritizes critical applications to maintain performance under varying traffic conditions. Furthermore, the design of network topology, adherence to security standards, and ongoing monitoring and optimization also play essential roles in maintaining the
