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The Foundation for Network Monetization

By: Suchismita Mohanty

Having made significant recent investments in network infrastructure, Communications Service Providers (CSPs) need to monetize such investments through new revenue streams from both existing and new sources. With consumer revenues under pressure, focus turns more to the wholesale and enterprise opportunity and, in particular, to communications-enabling applications in vertical industries (e.g., healthcare, public safety, etc.) to afford such applications greater reach or fundamentally enable new capabilities to drive higher value to their end customers. In turn, the opportunity for CSPs is to command a greater share of that increased revenue pie, but only if they can meet the needs of such vertical industry applications, including providing dynamic, on-demand connectivity with the appropriate reach, cost, and quality of service (QoS) for ease of consumption by such applications. 

This requirement drives considerable change in CSPs, with an emphasis on end-to-end automation at the business, customer, service, and network layers, something several standards organizations (e.g., ETSI, 3GPP, TMF, etc.) have defined to various degrees. The foundation of this is the concept of autonomous networks and operations, where networks can manage themselves with minimal human intervention, enabled by AI operations (AIOps) that use data analytics, automation, and AI to automate and improve IT operations. This approach drives the desired financial outcome of increased revenues and reduced costs.


Finding the right starting point: AIOps as a foundational step

For the network itself, a cloud native foundation is critical to this transformation. It offers the agility, automation, and scalability—in addition to real-time observability—needed to manage modern network demands efficiently. By embracing cloud native architectures, CSPs can streamline operations, accelerate innovation, and enable new business models that drive long-term growth in the 5G era. The appropriate exposure of network capabilities via network Application Programming Interfaces (APIs), in particular, plays a pivotal role by enabling enterprises and developers to harness 5G's advanced capabilities such as differentiated connectivity, ultra-low latency, and precise location services. These capabilities empower the creation of innovative business models, while also opening new revenue streams for CSPs through API monetization.  

At the same time, AIOps must evolve from buzzword to embedded capability. The increasing diversity of data formats, interfaces, and network behaviours demands that AI be embedded natively within products and platforms, not bolted on externally. This inherent intelligence enables real-time insights, proactive management, and context-aware decision-making, key enablers of self-optimizing, revenue-generating networks in the 5G era.   

This highlights the importance of embedding AI natively within the network components themselves, empowered by analytics and automation to effectively scale with AI growth rather than relying on external AI tools, paving the path towards a


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