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USES and CHALLENGES OF AI IN TELECOMMUNICATIONS

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AI can make a big difference with predictive maintenance. By finding patterns in the historical data, AI and ML (Machine Learning) algorithms can accurately anticipate and warn about possible hardware failures. This allows telcos to be very proactive at maintaining their equipment, fixing

Many industries value AI for its exceptional ability to analyze big data. As an industry that has constant access to vast amounts of data, it is not surprising that telecom and AI go together better than peanut butter and jelly. Let’s take a closer look at the most common ways this technology is used in telecommunications.

Predictive maintenance
As a network grows and becomes more sophisticated, maintaining it becomes increasingly difficult. Fixing issues can be a costly and time-consuming process. Moreover, it can lead to downtimes and service interruptions — something customers do not appreciate.

AI can make a big difference with predictive maintenance. By finding patterns in the historical data, AI and ML (Machine Learning) algorithms can accurately anticipate and warn about possible hardware failures. This allows telcos to be very proactive at maintaining their equipment, fixing issues before they occur, and affect the end-user.

Read More: Opportunities In Telecoms

Furthermore, these algorithms can identify the reason behind each failure, making it possible to fight the problem at its core. This is what happened with one of the world’s largest providers of in-flight connectivity and entertainment, Gogo. They partnered up with N-iX who improved the quality of their in-flight internet and made it possible to predict equipment failures. Moreover, data science models built by the N-iX team helped identify the main cause of ill-performing antennas. As a result, Gogo was able to solve the issue that was wasting costs and causing downtimes.

Network optimization
Another common use of AI in telecommunications is building self-optimizing networks (SONs). Such networks are automatically monitored by AI algorithms that detect and accurately predict network anomalies. Furthermore, they can proactively optimize and reconfigure the network to ensure that end-users enjoy the stable performance.

As companies realize the value of using AI in telecommunication network infrastructure, more and more are willing to invest in it. According to IDC, 63.5% of telecom companies are actively implementing AI to improve their network infrastructure.

Virtual assistants and chatbots
Conversational AI platforms are one of the biggest influencers on the growth of the AI in telecommunication market. These virtual assistants, or chatbots, as they are also known, can automate the handling of customer requests.

Long waiting periods are the bane of existence for good customer service and are something that human-operated call centers are very prone to. By scaling conversations to simple queries, chatbots can respond to massive amounts of customer inquiries with impressive speed. This, plus the ability to provide uninterrupted service 24/7, reflects very positively on customer satisfaction. Indeed, Vodafone saw an increase in customer satisfaction by 68% when they introduced their chatbot TOBi.

Read More: Telecoms with Artificial Intelligence

As virtual assistants develop and learn to handle more complicated requests, the need for human operators decreases. This can help companies greatly reduce their expenses. In fact, by 2022 the use of chatbots will lead to over $8b in annual savings.
Fraud detection and prevention
The fraud detection and prevention market reached $20.98B in 2020 with an expected CAGR of 15.4% during 2021-2028. Despite this, malicious attacks on businesses still cause over $3.6B of losses annually.

With AI’s excellent analytical capabilities, it is not surprising that many industries, including telecom, are finding it useful at battling fraud. The most prominent advantage of AI-powered fraud analytics is its ability to prevent fraud altogether. The system blocks the corresponding user or service as soon as it detects suspicious activity, not allowing the fraud to occur. All of this is done automatically, making the chances of not responding to an attack in time very slim.

Robotic process automation (RPA)
RPA is a form of digital transformation that relies on implementing AI. Telcos can use RPA to automate data entry, order processing, billing, and other back-office processes that require lots of time and manual work. This frees up your employees’ time, letting them focus on more important tasks, and reduces the number of errors that manual labor is prone to. As a result, your office runs smoother, your employees are more productive, and your customers enjoy error-free service.

With so much to gain, it is not that surprising that over 53% of all organizations have already begun their journey in RPA. Moreover, this number is expected to grow to 72% in the next 2 years, while in 5 years RPA will achieve almost universal adoption among businesses.
Need for additional technical expertise
AI is a relatively new technology. With limited local talent, building an in-house team can take a significant amount of time and yield little result.

A better option is to look for a technical partner that would implement AI in telecommunications for you. However, finding a vendor that has both enough competence and experience to successfully build an AI system can be a challenge in itself. Moreover, implementing AI can be quite pricey, so it is crucial to start your project with the right partner.

Read More : Telecommunications offer AI-driven services

Solution. Do your research before opting for a partnership with a software company. Take a look at their practical experience with AI, and find out what clients are saying about them. Trusted platforms such as Clutch can give you a good understanding of whether a vendor will be able to deliver the results that you expect. Look for a technology partner with expertise in ML/AI, Big Data, Cloud, DevOps, Security to help you meet your specific business needs.

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