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How is Artificial Intelligence Transforming the Telecom Industry?

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The telecommunications industry is no longer limited to providing basic telephone and Internet services; It is now at the epicentre of technology growth, led by mobile and broadband services in the Internet of Things (IoT) age. This growth will continue, and its main engine will be Artificial Intelligence (AI). 

Today’s communications service providers face a growing demand for higher quality services and a better customer experience. Telecommunications companies are taking advantage of these opportunities by using the vast amount of data collected from their immense customer bases over the years. This data telecom companies take from devices, networks, mobile applications, geolocation, detailed customer profiles, service use and billing information. 

The telco industry is also harnessing the power of AI to analyse and process these vast volumes of Big Data to extract actionable insights and provide a better customer experience, increase revenue and improve operations through new services and products. 

In 2021, there were more than 10 billion active IoT devices, according to Statista. Estimates say that the number of devices will exceed 25.4 billion in 2030. By 2025, there will be 152,200 IoT devices connected to the Internet per minute, which is why more and more operators are joining this trend, recognising the value of AI in the telecommunications industry. 

The telecommunications sector has never been oblivious to new technologies, innovation and change. It’s been paving the way for others for quite some time. But today, telcos and many other companies across the spectrum are facing a state of rapid change, uncertainty and disruption, thanks to 5G, the IoT, AI and many other acronyms. 

This development presents an unprecedented opportunity for organisations to move towards fully automated infrastructure operations that provide better end-to-end services, increase revenue, and at the same time, reduce costs and energy waste. At the same time, customer expectations have never been higher, and business processes are under great strain. 

Current challenges in the telecom industry

Operational Costs 

Operational tasks are increasingly complex with millions of subscribers and many customised products and solutions, as face-to-face support is not an option. Even simple tasks like service setup, billing, order fulfilment, and payments now pose a challenge. 

Managing complex operations demands more resources and tools, which also increases the overall financial expenses of telecommunications companies. 

Also, consumers want everything to be swift. They are not able to tolerate any delays in operational processes, especially while facing a pandemic and a global quarantine. It is time to be more decisive than ever.

Customer demands 

Most telecommunications service providers receive millions of customer requests every day, now more than ever. As the number of requests increases, the inability to go to physical stores and the fact that many employees work from home, providing quick and empathetic assistance becomes a problem. 

In this crisis, immediacy, personalisation and omnichannel communication are more critical than ever. Ignoring these needs can lead to long wait times, annoying conversations with multiple executives to resolve the problem, and unsatisfactory automatic responses. 

All of this can harm a customer’s relationship with the company. Also, what we want the least is an altered customer. Being empathetic and providing instant solutions is vital to maintaining a long-term relationship with clients.

Big data 

Customer acquisition cost is not the only thing companies need to consider when acquiring a customer. It is vital to tie this metric to customers’ total cost over time since combining these metrics will enable operators to improve their strategies and make them more effective. 

Rather than learning to predict consumer behaviour more effectively, companies need to use all the information that results from the analysis they are currently doing to optimise each resource they invest in each customer. 

This behaviour translates into the maximisation of their income. 

It is not a matter of lack of information. For example, telecommunications companies have precise data as relevant as how many times a user recharges per month or how much that same customer recharges. 

However, operators must use big data to refocus their strategies and improve customer costs throughout their lifetime, says TalkHome.co.uk. To the extent that they do so, they can improve their earnings. 

Security and data breaches 

With brand new technologies, ensuring network security became another tremendous challenge for telecommunications operators. New technologies pose new threats to network and application security. This problem occurs in teams working remotely and customers calling for help from home. 

It requires a slew of operational and technical enhancements to meet customer expectations for system security. In the specific case of telecommunications companies, it is necessary to apply measures, such as reliable and secure authentication functionalities.

Regulatory challenges

Regulation for several six-year terms has been a pending issue in the telecommunications area. Not sharing the network, as is done in other markets, makes companies not as competitive as possible. In addition, this also limits the entry of new foreign competitors who can invest in quality fibre optic networks. 

The problem in the background is that each operator invests in infrastructure for their use, which impacts the customer’s acquisition cost. Not being able to share the network makes it unprofitable for those companies that cannot make these investments in infrastructure to invest in acquiring more clients in that region. 

And this not only affects a specific company but also weakens the entire telecommunications sector. 

As soon as operators can share the network, they will compete on an even floor where competition stems from legitimate criteria of quality of service. The customer’s acquisition cost is related to competition criteria and not regulation. 

How AI is Revolutionising the Telecom Industry

Personalised Customer Service 

Another application of AI in telecommunications is conversational AI platforms. Also known as virtual assistants, they learn to automate and scale one-to-one conversations so efficiently that they can reduce business expenses by up to 30%. 

Increasingly, customers are not interested in spending time on the phone. If they need support, they turn to their mobile devices or computers, prefer to seek solutions through messaging customer service agents or self-service databases. 

Telecommunications companies have turned to virtual assistants to help deal with the myriad of support requests for installation, configuration, troubleshooting, and maintenance, which often overwhelm customer service centres. With AI, operators can implement self-service capabilities that show customers how to install and operate their own devices. 

Data-Driven Decision Making 

AI-powered predictive analytics is helping telcos provide better services by utilising sophisticated algorithms, data, and machine learning techniques to predict outcomes in the future based on historical data. 

This development means that operators can use data-driven information to monitor equipment health and anticipate failures based on patterns. They can also proactively troubleshoot communications hardware problems such as cell phone towers, power lines, data centre servers, and even set-top boxes. 

In the short term, network intelligence and automation will enable better problem prediction and root cause analysis. In the long term, these technologies will lend credence to more strategic goals, such as efficiently addressing emerging business needs and creating new customer experiences. 

AI for Network optimisation 

AI is essential to help operators build self-optimising networks, which can autonomously optimise the network based on information on traffic by region and time zone. AI applications in the telco industry use advanced algorithms to look for patterns within data, allowing operators to detect and predict anomalies in the network. It also enables them to fix issues before customers are negatively affected proactively. 

According to Forbes, 83% of organisations believe AI is a strategic priority for their businesses. This statistic is because AI optimises your network and your infrastructure. AI can analyse, optimise and correct errors in real-time. 

Providing uninterrupted service creates a self-organising system, a network that can be optimised and configured automatically. Furthermore, the AI ​​will predict whether a similar problem can occur in the future and take steps to prevent and solve it beforehand. Therefore, this improves performance.

Robotic Process Automation (RPA) for Telecommunications 

Operators have large numbers of customers involved in millions of daily transactions, each susceptible to human error. RPA is a form of AI-based business process automation technology that can bring greater efficiency to telecommunications functions by enabling telcos to facilitate their back-office operations and high volumes of repetitive and rule-based actions. 

By streamlining the execution of complex, time-consuming, and labour-intensive processes such as billing, data entry, workforce management, and order fulfilment, RPA frees operations staff for higher value-added work. 

Improved Quality of Service 

An IVR (Interactive Voice Response) is a cloud telephony technology based on Artificial Intelligence that enables customers to call a business to help themselves. 

The IVR or Virtual Assistant helps route calls to different departments of an organisation. Using prerecorded FAQs in the system, a virtual assistant can also handle more straightforward customer inquiries by itself. It even greets customers with a welcome message that can be personalised at any time. 

Chatbots with AI 

The chatbots with AI are gaining popularity among businesses to interact with customers because they can answer particular questions automatically; collect user data for agents before they engage with the customer to deliver an excellent experience; facilitate an efficient and straightforward interaction between company and user; save customers time as AI provides some general information in chat, and many customers prefer chatting rather than calling, which is why artificial intelligence chatbots are an asset for any organisation  

Cyber Security

The telecom industry is growing at one of the fastest rates globally. Like other sectors, it is also prone to fraud: authorisation, cloning, illegal access, theft, etc., are some of the more common fraudulent activities. 

AI can protect business data and detect and stop these unauthorised activities as it can detect irregularities in traffic and block them to obtain essential or sensitive information. 

Machine learning refers to the ability of software to learn from the activities it performs and use data prediction to process tasks faster. This machine learning functionality of Artificial Intelligence allows the software to act more quickly every time we use it. This speed saves agents and organisations a lot of time and also eliminates the possibility of errors. 

Conclusion 

According to a Deloitte survey, 40% of telecommunications, media and technology executives say they have made “substantial” benefits from cognitive technologies, and 25% have invested $ 10 million or more. More than three-quarters expect cognitive computing to “substantially transform” their businesses in the next three years. 

In conclusion, with Artificial Intelligence in telecommunication, the whole process has become much faster and simpler. Their union means that telecommunications companies can rapidly process hefty amounts of data and solve user problems using available data as soon as possible. They can also extract essential insights from customer interaction data, detect problems in advance, and offer customers an optimal experience. 

Last Updated: December 24, 2021

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