Introducing pervasive AI in telecoms: AI monetization use cases
10 Sep 2020
Introducing pervasive AI in telecoms: AI monetization use cases
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Artificial intelligence (AI) is popular for two things: being useful and quite expensive to adopt. The future of the telco industry depends on artificial intelligence and CSPs need more innovative, secure and customized solutions. So, how can communication service providers (CSPs) monetize AI and gain market leverage?
AI: your most (in)expensive employee
Introducing artificial intelligence into any organization always entails costs. Often, the costs are quite high in comparison to enlisting a traditional workforce. There is a big “but” in this, though. The greatest challenge of building and maintaining network and service management systems is gathering knowledge from experts. Each professional has a different approach to addressing problems. Collecting and unifying data can be very difficult and time-consuming. Bringing in new employees puts even greater strain on the process. Adopting artificial intelligence provides specialists with a helping hand, a practical tool that takes on tedious, repetitive tasks, allowing employees to handle the crucial ones. Experienced employees are still needed - they verify the results of AI’s work, but the knowledge systemization process is all automatic. With their help, artificial intelligence can perform tedious tasks more effectively and faster than any human, which brings cost optimization.
Introducing AI: first steps
Introducing AI should begin with the area where applying AI-driven automation is crucial. Since telcos should organize their data before bringing in tools containing AI, it is a good idea to have a schedule for introducing the new solutions. Apart from that, such changes always entail some bigger or smaller issues from the technical aspect and in the human context. It’s important to prepare everything and everyone before the process begins. If you’d like to learn more about the first steps in AI introduction, download on this white paper on introducing pervasive AI.
Pervasive AI in use
AI is making its way in the telco industry. Most of the telecoms are utilizing it one way or another. At Comarch, we have already had a few successful deployments of AI-driven services within our customers’ environments. The ones described below are based on real scenarios that we have experienced when working with telecom operators.
Automated baseline generation and anomaly detection (ABGAD)
Anomaly detection based on machine learning can identify performance indicators that do not match the expected pattern in a dataset and improve detection coverage by discovering new patterns consisting of multiple baseline violations. Traditional technologies made employees analyze multiple sources and monitor hundreds of thousands of parameters. ABGAD allows anomalies to be prioritized and cases with highest priority can be analyzed first, speeding up the entire process significantly. This kind of automation increases the number of variables and makes them more flexible and dynamic. Apart from that, being able to link different variables and determine the symptoms enables the identification and neutralization of any problems before they influence customer experience.
Automated situation detection (ASD)
Automated situation detection is another great example of AI-driven technology thatenables the identification of events not matching expectations anduncoveringinteractions between them. When a situation is detected, it can be prioritized. Cases with highest priority can be analyzed first, making the system operate at the highest possible capacity. In this way, telecommunications companies can increase productivity and asset utilization by ensuring that situations detected in the system are identified and classified. The main advantage of ASD is the reduction of the number of events leading to the definition of a single failure. The work required by the teams will be classified according to the root cause of the situations, and the symptoms or noise that are usually reported will disappear once the source component isfixed.
Automated problem detection (APD)
Automated problem detection performs root-cause analysis on trouble tickets that have been clustered into problems, which helps the user identify the root causes.The system enables problem identificationthat is more precise than the one performed by the experts. Machine learning provides a solution for finding potential events in the network, where any unsolved problem could lead to emergency situations. This reduces tasks for teams and causes no disruptions to the end users. It also provides the ability to find links and connect customer trouble tickets with network trouble tickets. These use cases are just some possibilities when it comes to the solutions that artificial intelligence can provide for the telco industry, especially the area of assurance and analytics. If you’d like to learn more about the AI-driven solutions for telecoms, visit our website or schedule a free demo of Comarch Intelligent Assurance – AI-powered Service Assurance Solution for Telecommunications.
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