Telecommunications are undergoing transformation
Telecoms are transforming how they operate, optimize, and provide service to their customers as a result of AI applications
Communication service providers (CSPs) currently face growing customer demands for more superb services and an improved client experience (CX). Companies are making the most of these opportunities by utilizing the large amounts of data they have collected from their large customer base over the years.
The data on tools, networks, mobile applications, geolocations, customer profiles, usage of services, and billing is gathered from these sources. AI is used by all major telecom companies to analyze large volumes of data to extract insights into how to better serve clients, optimize operations, and increase revenue through new products and services.
As part of our mission to determine what AI means for business, we need to examine some of the major business trends: network optimization, preventive maintenance, virtual assistants, and robotic process automation (RPA).
Network Optimization
With artificial intelligence, CSPs can build self-optimizing networks (SONs), where network admins can automatically upgrade network quality depending on traffic data by region and time zone.
In the telecommunications industry, AI is being used to find patterns and patterns in data, allowing IT administrators to proactively resolve issues before customers are negatively affected.
Gartner predicts that the number of CSPs adopting artificial intelligence (AI) technologies to improve their infrastructure planning, operation and products will grow from 30% in 2020 to 70% in 2025.
Here are a few notable AI solutions –
- By using ZeroStack’s ZBrain Cloud Management, architects and engineers can analyze the storage and use of private cloud telemetry to plan and upgrade their infrastructure;
- With over 50 Tier-1 companies as customers, Aria Networks uses AI-based network optimization,
- NetFusion from Sedona Systems enables precise traffic routing and 5G-powered AR/VR services.
- AVA platform by Nokia helps CSPs automate network operations and deliver quality services using an AI-based platform.
Predictive Maintenance
Data, present-day algorithms, and AI techniques are used to predict future results based on historical data, which means that man-made AI-driven predictive analytics is one of the latest trends that help telecoms to offer better services AI technology.
Telecoms will eventually be able to use data-driven pieces of information to monitor the state of stuff, predict failure based on patterns, and proactively fix issues with communications hardware, such as cell towers, electrical cables, data center servers, and also home set-top boxes.
Until network automation and intelligence are capable of predicting issues, root cause driver analysis will not be improved. Through the use of these technologies, our daily lives will be improved in many ways, such as managing business demands and creating better customer experiences.
Here are some organizations that use predictive maintenance:
With the aid of artificial intelligence, AT&T can detect problems with its networks gradually, thereby greatly improving its ability to manage incidents. It is possible to deal with 15 million alarms a day with the technology, so customers do not notice an issue until the service is restored. As well as augmenting maintenance strategies, AI is important to the company. By analyzing video data captured by drones, the telecom giant can grow the LTE network coverage and support the telecom giant’s cell towers on a technical and infrastructure basis.
In a collaboration with Accenture, KPN has developed very top-notch cameras using 5G to scan and analyze a wide range of connected piping dynamically, detecting areas at high risk for corrosion and deciding the best remedial measures.
Robotic process automation (RPA)
Every CSP has an enormous number of customers and an endless volume of daily transactions, all vulnerable to human error. Robotic Process Automation (RPA) is one of the most recent forms of business process automation based on artificial intelligence.
By automating their back-office operations and handling the large volumes of tedious and rules-based processes, RPA can bring more measurable efficiency to telecommunications companies.
By automating labor-intensive and tedious processes such as billing, data entry, workforce management, and order fulfillment, RPA frees up CSP staff to focus on higher value-added tasks.
RPA will significantly smooth out processes and further improve productivity for CSPs in 2021 when used to ease even a small part of the staff’s workload.
Using RPA represents a 1/3 savings over offshore workers and a fifth of the savings from on-site employees, AT Kearney reports, and can reduce expenditures by 25-50%. In light of these figures, it’s not surprising that Forrester data indicates that 44% of client service companies have already implemented RPA to achieve a competitive advantage.
The following telecom companies use RPA technology:
- Celaton helps organizations smooth out inbound data, such as emails, web forms, and posts; it separates key information, approves it, and then presents a recommended response to a service rep, who then changes the message before responding to the client.
- Using Kryon, telecom companies can recognize the key processes for automating both the human and digital side of their operations for maximum efficiency and effectiveness.
- Using AutomationEdge, network providers can automate data entry, invoice preparation, and customer service.
Industry trends in Artificial Intelligence for Telecom
Among the latest trends in the telecom industry are artificial intelligence applications, which are continuously helping CSPs manage, optimize, and maintain their infrastructure and customer support operations.
There are some ways in which AI has been applied to the business environment, including network optimization, predictive maintenance, and virtual assistance. Delivering an optimized customer experience and adding value to the enterprise as a whole.
Technology is already a major part of the telecommunications industry, and as Big Data devices and applications become more accessible and refined, AI will continue to expand there into 2022 and beyond.
CustomerThink originally published this article.