How Artificial Intelligence is Transforming the Telecom Industry

Artificial Intelligence (AI) is conquering every sector, providing new dimensions across all industries and accelerating digital transformation. Within Telecoms, the rise of 5G has opened the flood gates to a new world of opportunities and possibilities now possible with AI.

Digital transformation is a goal for businesses that are looking to leverage data, automation, and digitalization as a means of creating differentiation and competitive advantage. Governments around the globe have also realized the impact of 5G on digital transformation and have been allocating spectrum for Enterprises willing to leverage 5G to drive AI and Automation. 5G enables the private wireless infrastructure for the Internet of Things (IoT) and drives digital transformation, powered by AI and Edge Compute.

The applications for AI across telecoms are endless. AI in mobile network infrastructure is expected to lower costs by automating functions that typically require human interaction and to speed new revenue-generating service offerings, which becomes increasingly important in the deployment of edge, open radio access networks (Open RAN), and cloud-native 5G cores. 5G is the latest generation of wireless technology providing faster speed, lower latency, and the ability to connect a very high density of sensors. AI brings a new computing paradigm in which algorithms learn from the data to efficiently handle the ever-growing amount of information that sensors generate, including being able to infer patterns and trends in near real-time.

AI has become central to the telcos’ digital transformation as it aids the delivery of superior performance in the short and long term. Today’s Communications Service Providers (CSPs) face increasing demands for higher quality services and better customer experience. Telcos are capitalizing on these opportunities by leveraging the vast amounts of data collected over the years from their massive customer bases.

Consider these benefits of integrating AI technology:

Reducing Cost

The Telecom industry is one of the sectors that generate massive amounts of data requiring heavy investments in data management infrastructure. Thus the telecom operators are trying their best to reduce operating costs. The major challenge is that customer data are present at various sources. So manually managing the data and data sources prove time-consuming and involve significant additional expenses. But with AI and Machine Learning (ML), the management of Big Data will be much easier.

Optimizing Mobile Tower Operations

The regular maintenance of mobile towers is another hurdle that the telecom sector faces. They require on-site inspections to make sure that everything is functioning correctly. In such a scenario, AI-powered video cameras may be deployed at mobile towers, notifying the CSPs in real-time during situations of hazards or raising the alarm in cases of fire, smoke, or natural disasters. With the installation of IoT sensors at the mobile towers and the implementation of various ML algorithms, Big Data can be more efficiently analyzed and actioned.

Improving Customer Service

Another advantage that AI provides to CSPs is the automation of the customer service mechanism. Based on the adage, ‘The Customer is the King,’ offering the best customer care service is an important strategy for every business. If the customer is not satisfied with the services provided, there is a possibility of them shifting to an alternative service provider. However, providing quality customer service efficiently is not easy when done manually or in conventional ways. That’s where the advantages of AI come into play.

Also in today’s digital world, customers expect a lot, and their expectations are not only limited to excellent service. They demand personalized experiences every time they connect. Here, Intelligent Virtual Assistants can enable efficient customer engagement. As a foundational technology, AI can help telecom reinvent customer relationships through personalized, intelligent, and persistent two-way conversations at scale.

Detecting and Preventing Fraud

ML algorithms cut down fraudulent activities happening in the telecom industry, such as fake profiles, illegal access, etc. With the aid of advanced ML algorithms, the system can detect the irregularities occurring on a real-time basis, which is far more effective than what human analysts can perform.

Enabling Predictive Analytics

All CSPs manage vast amounts of data in their day-to-day operations. With technologies such as AI and ML, they can derive better business insights from the data. Through the process of Predictive Analytics, CSPs can make efficient and effective business decisions. Some of the major benefits of Predictive Analytics include customer segmentation, customer churn prevention, predicting the lifetime value of the customer, product development, improving margins, and price optimization.

Driving New Business

One of the main promises of 5G is to bring Industry 4.0 use cases to fruition by enabling high speed, low latency, and dense deployment of endpoints such as sensors, robots, and video cameras. This opens up a significant new business opportunity for telecom operators to not only provide outsourced IT services to the enterprises but to also offer innovative process automation services driven by AI at the Edge. Some example services are intelligent video analytics for object detection and automated inferencing, and sensor data analytics and control of industrial equipment for preventive maintenance. These AI-driven services are geared to address a trillion-dollar new business segment, for which telecom operators will be one of the beneficiaries.

AI and the Future of Networks

AI plays an essential role in todays’ telecommunications digital transformation across all verticals.  The crucial integration of AI technology within the telecom industry will help assist and guide CSPs in delivering, managing, optimizing, and maintaining the telecom infrastructures necessary today and for future networks.

For more information, visit Mavenir’s AI and Analytics webpage.

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