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AI will transform telco networks, IT and service operations and TM Forum members have published a new white paper about the use of AI in telco operations, also known as AIOps. Find out more and get involved.
Aaron Boasman-Patel
AIOps will help telcos manage AI at scale – a must in 5G networks
TM Forum members have published a new white paper about the use of AI in telco operations, also known as AIOps. This summary explains why communications service providers (CSPs) are counting on it to increase agility, and why collaboration and industry-agreement on an AI-based software architecture is necessary. AI is going to have a profound effect on communication services providers’ (CSPs’) businesses. It will transform their networks, IT and service operations, enabling them to deliver new, complex services across the digital ecosystem. AI will help them add the agility, speed of service delivery and reliability needed to compete, coexist, and even partner with over-the-top (OTT) service providers, hyperscale cloud providers and other new, nimble digital players – and it will do so while delivering massive cost savings through elimination of manual processes. The McKinsey Global Institute estimates that AI could contribute an additional 1.2% to annual growth in gross domestic product for at least the next decade, which amounts to over $13 trillion of economic activity by 2030. This, coupled with Bain & Company’s prediction that 5G could be worth over $400 billion to CSPs in the B2B2x marketplace, means that operators will be well placed to grow revenue exponentially, which hasn’t happened since the early 2000s.
New business models enabled by 5G and AI are not the only key drivers for cognitive and autonomous network deployment. The World Economic Forum estimates that AI could save CSPs a massive $46 billion in customer acquisition costs and lost revenue through network performance, and deliver a 30% reduction in mobile infrastructure spending by using it for better network planning. Aside from the economic benefits, technological advancements outside of AI are making its deployment a must. The advent of new wireless technologies such as 5G have the potential to add even more complexity to the network, particularly in radio access network (RAN) operations. 5G will make the RAN more complex as it needs forests of tiny antennas to exploit the very high frequency bands (millimeter waves) it uses. In addition, it is estimated that by 2025 there will be a total of 100 billion device connections around the world, which will put a huge amount of pressure on networks. More devices mean more data running across operators’ networks, and IDC forecasts that by 2025 this data will grow by 10 times to reach 175 zettabytes (1 zettabyte equals a trillion gigabytes).
As devices proliferate and the IoT grows, network and service management must be zero-touch because it is not feasible for manual processes to support the volume and velocity of changes that must happen across the network. A network servicing 10 million end points and 10,000 nodes could see these numbers increase by up to five times, which in terms of incidents per hour could lead to a 25-fold increase from 400 incidents per hour to as many as 10,000.
This is impossible to handle manually. CSPs must deploy AI and automation in their networks to manage the coming increase in traffic, but large-scale deployments of AI in operators’ networks creates huge operational challenges such as how to govern, deploy, operate, control and maintain hundreds or thousands of AI models and components which will eventually form part of their core IT and network systems architecture. Unlike traditional software, AI software learns and evolves autonomously when exposed to new input data. AI models are “black boxes” which are potentially even more fragile. They are exposed to bias and are nondeterministic by nature.
TM Forum members are addressing these challenges through an initiative called AIOps Service Management, the goal of which is to develop an industry-agreed framework that re-engineers the processes involved in the lifecycle of software and service operations management to handle and govern AI software at scale. This will enable operations teams, process owners and business users to exploit AI safely and properly, maximizing its benefits, mitigating risks and ensuring the appropriate level of network and service quality. The AIOps Service Management Framework is applicable to any type of architecture due to its agnostic design, which means it can operate as an independent process framework to manage the deployment of AI in current and future architectures. It is part of TM Forum’s Open Digital Framework (ODF), which includes the Open Digital Architecture (ODA), an open, modern, software-based target architecture that enables new operating and business models fit for the 5G era. The ODA sets out an industry-agreed vision of targeted software and services. It is loosely coupled, cloud native, driven by data and AI, and is made up of standard components which can be easily procured and deployed, without the need for customization. To learn more about the ODA and TM Forum’s vision the future of the software market, download this white paper.
To learn more about how to get involved in the Forum’s work on AIOps, please contact me directly, and download the new white paper below.
