Now Affordable: Managing the Tasks
You've Dreamed of in Telco/IT Networks

With such benefits, it is easier to harmonize work in different areas, where previously we had to deal with more than one required expert.

If there is a particularly favorable situation, it can also take advantage of the different daily, weekly, or other resource requirements to provide services to various customers. At the same time, the process does not require hiring additional people to analyze, plan, and execute such reconfigurations that are carried out continuously. The same analytical processes also make it possible to designate network functions that need to be expanded due to increasing utilization and new instances launched, reconstituting the reserve of operational resources.

The emergence of artificial intelligence and machine learning as a form of work automation has radically changed the situation in the BSS and OSS space in the telecom and IT verticals. While the maturity of data and the spread of function virtualization are more like Enablers, the development of artificial intelligence-based automation is a Game Changer. Replacing human labor with the work of automated systems is a major change. Still, in the case of this solution, we are adding self-improvement of the way we work and keeping the knowledge of those ways permanently in the company's resources rather than the heads of experts who may choose a different career path.

With such benefits, it is easier to harmonize work in different areas, where previously we had to deal with more than one required expert. Work is carried out continuously, at an identical quality level, devoid of such factors as fatigue. At the same time, they can be performed much faster, more precisely, and more safely. What has so far been missing from systems such as SON is the ability to add an automatic variable factor in the form of best practices and priorities that determine how the system works at different times. In a highly competitive market such as telecom/IT services, this aspect is of significant importance. It is crucial to have varying priorities in continuous advertising and promotional campaigns, and to modify them once the campaign comes to an end. This approach allows flexibility to cater to the changing needs of the customers over time, which may only be temporary. The new technologies, particularly 5G and beyond, put a far-reaching self-reliance on the use of telecommunications services by companies using such services in their business as a critical component of their service in another vertical. For example, a company producing structural components, such as in the automotive industry, communicates with individual robots through a private telecommunications network or slice. In such applications, there is a need to manage the telecommunications network without expertise, hire an expert, and rely on intuitive process control supervised by AI. With the relevant expertise inside the policies written by experts, only elements specific to a particular vertical are added, and the system takes action based on new priorities and best practices.

This is not the main topic of the article, but the rapid development of generative AI is worth addressing here. Its importance in processes is somewhat less, but it too can bring many conveniences and time-saving benefits in customer-artificial Intelligence cooperation. It can realize the dream of an intuitive interface that recognizes even complex commands, such as "generate me a typical slice," and translate it into a process. It can control documentation work, create documentation during corrective actions for postmortem reports, and translate specific system commands into content that non-experts can understand.

There are many applications of the technology discussed here, which can be used to create new services by utilizing existing resources. This includes complex services such as generating a slice with specific parameters or building services with set start and shutdown times, specified parameters, and within a defined area. This technology provides the benefit of responding to service requests immediately, at any time of the day. It also enables you to continuously optimize the usage of resources for executing services and make changes to service configurations without the customer's knowledge, which saves resources for other purposes. Switching to different resources or specific services impacted by equipment breakdowns is significantly faster and more affordable, especially when it involves sending a technician to a distant location. This approach minimizes the need for repairs, allows proactive operational reserve maintenance, and facilitates expansion efforts. Using such solutions brings the principles of vertical cooperation to a higher level, as t is possible to hand over the management of private networks or slices to their owners and CSP-controlled artificial intelligence. In addition, it is possible to introduce a labor-intensive process of optimizing energy consumption and adapting it to traffic forecasts in a given area during periods of lower demand for services, and even reducing energy consumption from fossil fuels in favor of renewable ones, which, image-wise, but also due to regulations, is becoming increasingly important. The days are coming when swarms of AI instances will be working on things we've always wanted to do but have always found too time-consuming, and tiring.


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