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AI in Telecom

How AI Is Changing the Telecom Landscape

In the era of IoT, 5G and broadband, the telecommunications industry is expanding as a major hub for technology innovation – and there’s no slowdown in sight. Growth is expected to continue at a rapid rate to meet the wants and needs of modern customers. Service providers are expected to provide an excellent customer experience and the latest technology, all while growing revenue. 

Telecom service providers have been collecting and analyzing user data for many years. The information they collect isn’t just standard call and text records. They have access to a plethora of additional intel like device and network information, server logs, browsing history, billing data, social, web, and mobile application use, and location history. This provides lots (and lots…and lots) of information and insight about a customer’s habits. All of that data is tied to our phones, and all of our phones are tied to our hands. Historically, most of this mountain of information has been collected, copied, then ignored and ultimately discarded.

What’cha Gonna Do With All That…Data?

Using the power of artificial intelligence (AI), organizations are now able to process and analyze considerable amounts of data in short amounts of time by using advanced algorithms. Themes and patterns within the information are now being discovered, and data-driven strategic plans are being put into place to create an enhanced customer experience and improve operational efficiencies.

In a Harvard Business Review article, 250 executives familiar with their companies’ use of cognitive technologies were surveyed. At 51%, the top benefit for the use of AI was to enhance features and performance of existing products, followed by 36% wanting to free up staff to focus on creativity. The majority of the execs weren’t even looking at automation to replace employees or reduce headcount – only 22% mentioned the possibility.¹

Businesses have found creative and innovative ways to implement this amazing and growing technology into everyday operations. Some of the most productive uses for AI in telecom are listed below:

Chatbots and Virtual Assistants

Nearly every large-scale teleco uses artificial intelligence and machine learning with chatbots and virtual assistants. Service providers are usually saddled with a massive number of tickets for troubleshooting, maintenance, configuration, and installation. Using keywords and account history, virtual assistants can automate and scale immediate responses to support requests, which reduces expenses and improves customer satisfaction. The ability to handle a simple problem in just a few minutes is typically what’s expected of voice service providers today – a seemingly impossible task without this technology.

Call Recording Analytics 

By 2024, 75% of work conversations will be recorded.² Innovative companies are using AI to find patterns in these recorded interactions. The technology uses natural language processing and voice recognition to listen for keywords and phrases – some software platforms can even understand the tone of a conversation. All of these voice, video, and chat logs can be analyzed to uncover trends and create insights. There is also technology available that can link recordings directly to your CRM data, so you know exactly what was said when and who said it. 

AI can provide written transcripts of recorded calls using a voice-to-text function. Manually, these processes are too difficult, time-consuming, and error-prone to even attempt.

Data-Driven Decisions and Predictive Customer Analytics

Predictive analytics help the industry improve service by utilizing data, algorithms, and machine learning to predict future results according to historical data. Telecom leadership can make swift and knowledgeable business decisions using the evidence AI has collected and analyzed. This saves time, improves margins, optimizes revenue, reduces churn, and helps predict a customer’s lifetime value.³ Using past data is the best way for organizations to improve their understanding of future customer behavior and trends. 

Predictive Maintenance

Predictive analytics can also be used for a company’s physical infrastructure. These data-driven predictions are used to oversee equipment and monitor networks to anticipate outages or failures based on past patterns. 

Implementing AI also allows service providers to proactively fix issues with their hardware such as cell towers, power lines, and data centers. In the short term, network automation and intelligence will enable better root-cause analysis and prediction of problems. In the long term, the technology will establish more strategic goals, like creating new experiences and dealing efficiently with evolving business needs.

Fraud Detection 

Have you ever gotten a call from your credit card company while on vacation asking if charges are valid? No one is actually sitting online, looking at your account and wondering why there’s a charge from Cabo. Algorithms learn what an account’s typical operation looks like so it can quickly identify outliers and anomalies. It can even trigger an immediate response to investigate account activity when there might be a breach. These powerful AI capabilities are crucial in promptly detecting illegal access, theft, suspicious or fraudulent activity, and other deviations that could compromise the customer’s account and private information. 

Can AI replace HI?

Wonder if AI will quickly replace HI (human intelligence)? According to the above-mentioned HBR feature, the short answer is no. For most of the companies reviewed, reducing headcount or replacing administrative employees wasn’t the intended outcome when integrating AI. Many companies will upskill and reskill staff who may be affected by the transformation to higher-paying and more innovative positions. Continued education within the company is the best way to retain great employees and improve engagement and employee experience. 


  1.  Artificial Intelligence for the Real World
  2.  Dubber
  3. The Amazing Ways Telecom Companies Use AI And Machine Learning
  4. AI in Telecommunications: 6 Common Applications




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