Telecom's Demand for Data Science and AI

In today's world, telecom is becoming more and more digital. Voice conversations are transmitted digitally, data services are frequently more important and profitable than voice services, and more and more of the industry's infrastructure is digital and software-driven every year. Additionally, the customer service and back-office processes of the telecom sector are experiencing digital transformation.

The importance of data science and AI to the sector is growing as it develops. Massive volumes of data are produced by telecom firms' infrastructure, network, and customer service operations. Data science is now so widely used in telecom because of this. Data science and AI in telecom give operators the capabilities to analyze such data and apply it for a variety of purposes, including boosting dependability, cutting costs, and enhancing customer experience.

The Demand for Data Science and AI in Telecom

The massive influx of data generated in the telecom industry means that the demand for data scientists is only increasing. Research by Analytics Insight reveals skyrocketing growth in big data is dominated by the telecommunications and IT industry, with a 33 percent share of the overall market. To put that in perspective, the organization predicts that spending on big data in telecom will grow from $59 billion in 2019 to over $105 billion in 2023. Along with that, comes the demand for qualified professionals in the field, with over four million job openings expected by 2023.

COVID-19 Driving the Demand for Data Science and AI in Telecom

While the Internet of Things (IoT), the rollout of 5G, and increasing consumer pressure for personalized services have been driving the demand for data science in telecom in recent years, the COVID-19 pandemic has put it into hyperdrive. The need for reliable connectivity has never been so apparent to virtually every industry that relies on digital communications — from schools, healthcare and pharma, government agencies, to the global supply chain. With reduced staff, limited access to facilities like call centers and data centers, the telecom industry is increasingly adopting data science, AI, and automation to ensure that critical communications in this new remote world stay smooth during the crisis. On top of that, by leveraging data analytics, telecom companies respond faster to rapidly today’s changing environments and requirements — even without COVID as the primary driver.

How Companies Can Leverage Data Science and AI in Telecom

While there is no limit to how telecom companies can employ data science and AI in their respective businesses, here are a few that are already in place.

1. Network Security

Telecoms are a super attractive target for cybercriminals. After all, they provide a connection to just about everything in today’s digital world through complex, global networks. They also store massive amounts of highly sensitive data. Through data science, companies can view events in real-time, identify security anomalies, and perform predictive analysis to determine where vulnerabilities are and how to mitigate them proactively. Further, by leveraging machine learning in telecom, companies can analyze threat patterns to stop them before they become too widespread.

2. Fraud Mitigation

Not only are telecom networks vulnerable to cybercrime, but their customers are, too. And it is only getting worse during the pandemic. Fraud is so rampant in the telecom industry that a study by the Communications Fraud Control Association (CFCA) reported that fraud cost the global industry a whopping $29 billion in 2018 alone. By leveraging big data in telecom, companies can analyze real-time data to identify the source of fraudulent transactions and correlate those with historical activity to prevent future counterfeit actions.

3. Network Optimization

As more of us rely on network connectivity, especially during COVID-19 shutdowns, telecoms need to ensure that speed and performance are always in top shape. To do this, they are leveraging data science, AI, and machine learning algorithms to identify patterns in data that help them to detect and predict irregularities before customers experience any service degradation.

4. Customer Experience

There are two important aspects to this – personalization and snappy resolve of any issues customers may be experiencing. Telecoms use data science, AI, and analytics to determine what customers want based on their historical interactions and preferences. Telecoms also leverage AI to provide speedy and smart customer service through intuitive self-service menus, chatbots, and natural language processing (NLP) enabled by machine learning.

5. Robotics Process Automation (RPA)

RPA has many applications in telecom to automate repetitive tasks to save labor and costs, reduce errors, and speed up operations. CustomerThink, a global online community of business and thought leaders that regularly weigh in on customer-centric strategies, identifies several ways RPA can enable telecom companies through RPA, including:

• Network management
• Invoice & purchase order processing
• Customer onboarding/offboarding
• Efficiently responding to partner queries
• Manual sales order processing
• Data transformation
• Expense Control
• First call resolution (FCR)
• Debt Collection

6. Supply Chain Management

When the global shortage of toilet paper in the beginning of the COVID-19 pandemic became reality for people sheltering-in-place, it was attributed to so-called hoarders. While hoarding may have contributed, the disruption in the global supply chain was at the core of this problem. Telecoms, which are the global supply chain's backbone, needed to become more responsive to this disruption. Through big data analytics, data science, AI, and automation, telecom companies were able to adapt to this sudden shift in demand to fix the stresses on the supply chain.

7. Business Operations

Besides the customers that rely upon telecoms for literally everything in today’s digital economy, telecom companies are increasingly using data science and AI for their internal operations. Like how these companies have stepped up to the plate to enable distance learning for schools across the globe during the shutdown, they need to enable their employees in these difficult times. Many are doing so by offering online upskilling options to their employees so they stay engaged and on top of the latest digital skills to keep the world connected and safe. Re-enter AI and data science in telecom.

An Evolving Story

While this is hardly an exhaustive list of how big data in telecom is changing the industry, it is a good start. AI and data science in telecom are here to stay, and companies need qualified professionals to continue shaping the future of communications. If you’re interested in joining in on this exciting effort, upskilling online — while backing critical telecom infrastructure and services — is a great way to go.

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