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THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE TELECOM INDUSTRY

Marketing Manager
Anastasia Shevchuk

INTRODUCTION

Telecommunications companies have traditionally had challenges with network operation and infrastructure issues, complex networking systems, improper resource utilization, customer support issues, network failures, and ever-increasing bandwidth requirements.

Automation and artificial intelligence give telecoms the possibility of generating good revenues, strengthening customer relationships by identifying personalized needs, and improving network capabilities.

Let's see how telecommunications companies implement artificial intelligence in their work.

AI FOR NETWORK OPTIMIZATION

AI is essential for helping Communication Service Providers build self-optimizing networks, which provide operators with the ability to automatically optimize network quality based on traffic information by region and time zone.

Artificial Intelligence applications in the telecommunications industry use advanced algorithms to look for patterns within the data, enabling telcos to both detect and predict network anomalies, and allowing them to proactively fix problems before customers are negatively impacted.

MOBILE TOWER OPERATION OPTIMIZATION

The regular maintenance of mobile towers is another obstacle that the telecom sector faces. They require on-site inspections to make sure that everything is functioning properly. In such a scenario, AI-powered video cameras may be deployed at mobile towers, notifying the Communication Security Providers in real-time during situations of hazards or raising the alarm in cases of fire, smoke, or natural disasters.

PREDICTIVE MAINTENANCE WITH AI

AI-driven predictive analytics is one of the latest trends in helping telcos provide better services by utilizing data, sophisticated algorithms, and techniques for forecasting future results based on historical data. Telecoms can use data-driven insights to monitor the state of equipment, predict failure, and proactively fix problems with communications hardware, such as cell towers, power lines, and data center servers.

In the short-term, network automation and intelligence will enable better root cause analysis and issues prediction. Long term, these technologies will underpin more strategic goals, such as creating new customer experiences and dealing efficiently with business demands.

AT&T company is using machine learning to enhance its end-to-end incident management process by detecting network issues in real-time. The technology can address 15 million alarms per day, restoring service before the customers notice any break. The company is also relying on AI to support its maintenance procedures: the telecom giant is using drones to expand its LTE network coverage and to utilize the analysis of video data captured by drones for tech support and infrastructure maintenance of its cell towers.

VIRTUAL ASSISTANTS

Virtual assistants are an emerging trend in this sector, designed to cope with the massive number of support requests for installation, set up, troubleshooting, and maintenance, which often overwhelm customer support centers. Using AI, telecoms can implement self-service capabilities that instruct customers how to install and operate their own devices.

For instance, Vodafone's website-located AI assistant, Julia, can assist customers with a range of tasks from technical support to invoicing queries, and then transmits critical, insightful data back to Vodafone to help in future decision-making.
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FRAUD DETECTION

Telecom is the most vulnerable among other industries, suffering the largest financial losses due to breaches in their cybersecurity systems. Conventional telecom security systems only identify commonly occurring issues but fail in detecting or forecasting potential future threats.

Telecom fraud happens in various forms such as subscription, voicemail fraud, identity theft, international revenue - sharing fraud, and voice phishing calls.

Telecommunications data includes highly sensitive information such as source number, destination number, call duration, call type, geography, region, and account billing information.

With the help of AI, it is much easier to implement algorithms that can detect and respond to fraudulent activities on the network. Additionally, Artificial intelligence considerably reduces response time, allowing telecom businesses to eliminate the threat before it exploits internal information systems.

CUSTOMER SERVICE

Customers don't like waiting. It's a fact.

So when a mobile user reaches out to a service provider, they don't want to wait, they want answers here and now. A telecom could double or triple the size of their customer service departments to achieve faster response & answer rates with the chatbot help. A bot can communicate with thousands of people at once .

AI models learn why customers reach out to their service providers and can predict when a customer will make a contact, allowing the telecom to take proactive action, or provide an answer now if the customer makes contact first.

AI chatbots can automate customer inquiries, while intelligently forwarding up-sell and cross-sell opportunities.

Chatbots can help to:

Optimize customer service

▪️ Chatbot telecoms – Chatbots enable telecommunications companies to solve customer problems quickly by integrating with the website and receiving several relevant data inputs about the customer.
▪️ EmailBot – makes email support easier. Having a bot reply with answers or follow-up questions. Routing other emails to the right people the first time.
▪️ CallBot – AI bot will ask customers for their problems, transcribes calls in real-time, then routes the call appropriately.
▪️ Call Analyzer – helps to evaluate agent performance and assist with coaching, while measuring customer sentiment.

Network technologies

▪️ Customer experience index – helps to understand how customers experience your wireless network. Whether or not they tell you.
▪️ Fault Grouping – helps to reduce alert noise. AI models will understand vast alert & alarm systems to provide more meaningful alerts.

AI FOR TELECOM: REAL-TIME EXAMPLES

The world's largest mobile provider, China Mobile, is leveraging AI-embedded and big data technologies for fraud detection. The company has introduced a new product – a big data-based anti-fraud system, called Tiandun - which can detect fraudulent activity, distinguish it from normal calls and intercept spam texts or calls.

China Mobile

Vodafone

Vodafone Group is a British multinational telecommunications conglomerate. The company has improved customer services with the arrival of its virtual assistant app TOBi.

TOBi can enhance customers' engagement and personalize the sales journey. Being a text bot, TOBi can directly answer most customer questions, solve problems, or suggest and offer more suitable products.

Deutsche Telekom

Deutsche Telekom has been making considerable investments in AI at various levels. From an AI-powered chatbot called Tinka, capable of providing over 1500 answers to customers' questions, to intelligent business planning tools, this CSP is actively embedding AI elements into its infrastructure and service portfolio.

SUMMARY

Artificial Intelligence can be a useful tool in the telecommunications industry. Implementation of AI by telecommunications companies resulting in the development of highly personalized products, improved fulfillment processes, and enhanced network management. It also allows telecommunications operators to provide their customers with more attractive services as well as improve their customer retention.
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