Implementing Artificial Intelligence in Telecommunications

Telecom Business Review | Monday, May 31, 2021

The use of artificial intelligence in telecoms is currently at an all-time high, and the future seems even more promising. There are estimates that the global AI in the telecommunications market will reach $14.99 billion by 2027.

FREMONT, CA: Traffic on a global scale and the quantity of network equipment are expanding substantially. This makes network administration difficult, costly, and time-consuming. AI can improve and automate networks, maintain their health and security, and save operational expenses.

Numerous sectors respect Artificial intelligence (AI) for its extraordinary capacity to evaluate massive amounts of data. Given that the telecom business has constant access to large volumes of data, it is not unexpected that AI and telecom go together like peanut butter and jelly. Let's examine the most prevalent use of this technology in telecoms.

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Predictive servicing: As a network expands and becomes more complex, it becomes increasingly harder to maintain. Fixing problems can be an expensive and time-consuming endeavor. In addition, it can result in service interruptions and downtimes, which customers do not appreciate.

AI can significantly improve predictive maintenance. AI and Machine Learning (ML) systems may reliably forecast and warn about potential hardware problems by identifying trends in past data. This enables telecoms to be highly proactive with equipment maintenance, resolving faults before they affect the end user.

These algorithms can also determine the cause of each failure, making it possible to address the issue at its core. For instance, Gogo, one of the world's top suppliers of in-flight broadband and entertainment, experienced this.

Network enhancement: Another prevalent application of AI in telecommunications is the creation of self-optimizing networks (SONs). These networks are monitored automatically by AI algorithms that detect and precisely forecast network irregularities. In addition, they can optimize and modify the network proactively to ensure end-users enjoy the steady performance.

Businesses increasingly recognize the benefits of employing AI in telecommunication network infrastructure and are increasingly prepared to invest in it. IDC reports that 63.5 percent of telecom companies actively utilize AI to enhance network infrastructure.

Virtual assistants and chatbots: Conversational AI platforms are one of the most significant factors influencing the expansion of AI in the telecommunications market. These virtual assistants, often known as chatbots, can automate the processing of consumer inquiries.

Long wait times are the scourge of effective customer service, and human-operated contact centers are particularly susceptible to them. Chatbots can quickly react to many client inquiries by reducing discussions to simple questions. This, together with the ability to provide uninterrupted service 24 hours a day, seven days a week, significantly affects customer satisfaction. For instance, Vodafone's customer satisfaction increased by 68 percent after the introduction of TOBi.

Human operators are becoming less necessary as virtual assistants advance and become better at handling increasingly complex requests. This can significantly reduce expenses for businesses.

Fraud detection and prevention: The market for fraud detection and prevention reached $20.98 billion in 2020, with a projected CAGR of 15.4 percent from 2021 to 2028. Despite this, harmful assaults on corporations still result in annual losses of about $3.6 billion.

Given the superior analytic capabilities of AI, it is not surprising that many industries, including telecom, find it helpful in combating fraud. The greatest benefit of AI-powered fraud analytics is its capacity to avoid fraud entirely. Fraud is prevented as soon as the system detects suspicious activity. All of this is performed automatically, making the likelihood of missing an attack extremely remote.

Robotics-assisted process automation (RPA): RPA is a sort of digital transformation dependent on the application of AI. Telcos can use RPA to automate data entry, order processing, billing, and other time- and labor-intensive back-office processes. This permits employees to focus on more critical tasks and reduces the number of errors associated with manual labor. Consequently, the offices operate more efficiently, their employees are more productive, and their customers receive error-free service.

With so much to gain, it's not surprising that more than 53 percent of organizations have already begun implementing RPA. Furthermore, it is anticipated that this percentage will increase to 72 percent within the next two years and that within five years, RPA will be adopted by nearly all businesses.

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