2021 Vision: 5 Emerging AI Trends in Telco

Published on
May 5, 2021
Ana Banaynal
Account Manager

Next to food and medicine, connectivity is one of the most in-demand commodities today, especially during the pandemic. Government-imposed lockdowns and the fear of contracting the virus moved almost everything and everyone online, which made it clear that the telecom industry is among the most patterned to human activities.

As voice and data usage skyrocketed, telecommunications companies (telcos) are forced to address demands for increased network reliability and better service. Artificial Intelligence (AI) is said to help address similar challenges for many industries, but the idea is always being brushed off, until now.

Predicted to provide $15.7 trillion of global economic growth by 2030, AI is the top priority for many businesses, and telcos who invest in it are able to respond better to the demands of today’s society, and beyond. Here’s how: 

Predictive Maintenance

Maintaining cell towers on the field is no easy task. Now, imagine if half of these towers break down at the same time. It’s a horrifying situation that can be prevented. Using AI, telcos can collect and analyze data for quick response and anticipate such incidents.

For instance, AT&T detects network issues in real-time to enhance incident management and is able to predict potential issues based on patterns. Another way they stay on top of their network is by deploying vision AI on the field using drones to capture and analyze video data on cell towers. Equipment defects, corrosion, or other anomalies are detected to drive proactive repairs or maintenance, so outages can be prevented.

Fraud Detection

In any business, fraud is a huge problem. For telcos, the introduction of 5G not only speeds up the data highway but also makes network security difficult to implement and more vulnerable to fraudsters. Accenture partnered with IBM to help telcos detect and address fraud in real-time. They cited, as an example, that the suspicious use of roaming costly services can be mitigated by notifying the network subscriber and verifying the incident to stop the fraudster from using data.

Training what “normal” behaviors are enables AI systems to identify otherwise fraudulent activities, including the creation of fake accounts, breach of privacy, and other security-threatening behaviors.

Internal Process Automation

Telcos have massive amounts of data in their hands, which are the building blocks in training machine learning models and implementing IoT solutions to take care of manual processes such as identifying transaction types (new accounts, data upgrades, billing inquiries, etc.), providing data plan quotations, and other prescriptive, rule-based tasks. 

AI can be trained to create personalized recommendations, too. As such, routing customers to the right data products and services is faster and more efficient, allowing teams to focus on sales and crafting better customer experiences. One thing to note here, though, is that AI will only augment, and not completely take away the human workforce.

Network Analytics

As mentioned above, telcos have access to truckloads of data, which, when consumed by AI, can generate meaningful and actionable insights. This level of business intelligence allows forward-thinking providers to generate new income streams, as well as optimize existing network services. In today's world where work, school, shopping, and leisure depend heavily on connectivity, customers will certainly delight in consistent, good-quality connection.

Moreover, AI empowers telcos to make data-driven decisions addressing the demand for better network performance and services, whilst reducing downtimes and cost, especially when sending technical resources on-field and answering an influx of calls from dissatisfied, irate customers. 

Customer Service and Satisfaction

Speaking of calls, the most popular AI use case in the telco sector is perhaps improving customer service and satisfaction. The traditional customer service call centers are inefficient, especially when the question only requires a simple, straightforward answer. Where one-on-one conversations with an agent aren’t necessary, chatbots can fill in. They are easy to manage and helpful to the overall customer service process.

With machine learning algorithms, today’s virtual assistant chatbots have become more efficient. in helping customers do basic troubleshooting, and answer common questions, or refer them to human agents for more complex queries.

According to Harvard Business Review, telco Centurylink saw the benefit of implementing their AI-agent Angie, which handles around 30,000 emails a month, classifies leads, and routes them to the sales department. They found that 99% of the time, Angie interprets customer emails correctly, leaving only 1% to be routed to human agents.

Furthermore, the amount of customer data gathered from multiple touchpoints (mobile, web, and social media) enables telcos to improve and personalize the customer experience. 

The demands and challenges the telecommunications industry face today make Artificial Intelligence a must-have. As customers seek faster issue-resolution, reliable connectivity, and better customer service, those who respond now and invest in AI will thrive in the new normal, hyperconnected world.

This article is an installment of our Vision 2021 series, where we tackle insights on Vision AI disruption across industries.

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