AI in Telecommunications: Top Challenges and Solutions

Max Liul, Data Science Specialist

There are many challenges in adding AI to your telecom strategy. Learn how to face those challenges by reading this article.

AI in telecommunications

Defined as communication that takes place from a distance, the telecommunications industry is what allows modern users to connect via phone, conferencing software, and more. As with many other industries, the last decade has brought a new push to implement artificial intelligence, or AI, to streamline processes and create better user experience.

In particular, telecom companies would do well to consider instating a robust AI technology strategy in order to improve overall client satisfaction, raise retention, enable self-service, reduce operating costs, and better maintain equipment. Like anything worth doing, though, implementation of an artificial intelligence technology strategy does not come without its challenges. Keep reading to learn some of the challenges common to the industry, as well as to review optimal solutions.

Current State of AI in the Telecom Market

Artificial intelligence in telecom is projected to complete a radical growth cycle of nearly fifty percent by the end of this year, ending as a $2.5 billion industry. Major companies like IBM, Microsoft, Intel, Cisco, and NVIDIA have begun utilizing technologies like machine learning and deep learning and natural language processing to ensure that they stay competitive in their respective market sectors.

These companies are finding a variety of applications for this software, with some of the most commonly used being customer analytics, network security, network optimization, self-diagnostics, virtual assistance, and more.

Types of AI Most Commonly Used by Telecommunications Companies

As mentioned above, there are three major types of AI technology that telecommunications companies are implementing en masse. The first is what’s known as machine learning. Machine learning is the branch of artificial intelligence that utilizes data and algorithms trained by various datasets. Deep learning, on the other hand, is a slightly more advanced variation of machine learning, in which computers utilize algorithms to mimic human thought patterns and neural pathways.

Finally, there is natural language processing, or NLP, which denotes the ability of a computer to understand human language as it is spoken and written. In other words, this work, rooted in the field of linguistics, seeks to allow computers to understand the meaning behind human tone and word choice, in order to more quickly assist with the intended outcome.

Ways to Utilize Artificial Intelligence in the Telecommunications Industry

Various telecom companies are adding artificial intelligence to their business strategies via any number of the types of AI we mentioned above. Continue on to hear about some more specific market applications that are being implemented in today’s telecom industry.

AI in telecommunications

Customer Service and Satisfaction

With what seems like everyone in the world holding some type of communication device, it’s easy to imagine how many requests for help telecommunications companies receive regularly. Whether it’s individual clients having trouble connecting their personal devices or corporate clients needing help navigating complex systems, it’s important to ensure that those clients can get access to help at the drop of a hat.

However, it’s nearly impossible to run a help center without some level of artificial intelligence. Could you imagine how many people you would have to hire to answer every single question that comes in? Artificial intelligence is able to act as a gatekeeper, and answer simple queries independently, while escalating the more challenging ones to human helpers.

Because of the speed that this allows users to get the information they desire, adding artificial intelligence to your telecom strategy by way of chatbots, or other customer-service-related features, can lead to an uptick in client satisfaction ratings. In fact, when Vodafone implemented theirs, they noted a 68% increase in client satisfaction.

Predictive Maintenance

Predictive maintenance is a pretty straightforward term. It refers to the ability of a computer to detect and predict when maintenance may be needed in a technical setup, in order to provide early warning to the engineers who monitor it.

This decreases the cost of maintenance teams in the short-term, because rather than requiring a full team to offer round-the-clock monitoring, you can trust that your computer will alert you when maintenance is required somewhere in your network. This allows ops teams to offer a proactive response, rather than a reactive response. Beyond all, it goes without saying that preventing these disruptions holds a positive impact on overall budget and user experience–your project managers will thank you!

Automatic Problem Resolution

On the flip side of automatic problem detection lies automatic problem resolution. With the type of broad-scale visibility that only computers are able to have, artificial intelligence can ensure that problems like network outages are handled quickly and efficiently, ensuring less downtime for your product and less angry customers for your support team.

Fraud Detection

Horrifyingly, over 59 million Americans reported losing money as the result of phone scams in 2021, with an average loss of close to five hundred dollars. While the industry had previously handled this incredible volume of problems manually, artificial intelligence brings with it a new approach.

Because fraud patterns change regularly, an adaptive, artificial intelligence strategy allows companies to rest easier, knowing that their clients are being offered constant vigilance. For example, after implementing artificial intelligence, Bell Canada experienced a 150% improvement in the time it took to detect fraud losses, and was able to begin banking patterns to prevent fraud loss in future transactions.

Benefits of Integrating AI Into Your Telecommunications Strategy

If the above examples did not convince you that artificial intelligence is integral to your telecommunications strategy, then consider the following:

  • Consider the mass amount of data generated by the telecom industry. Further consider the very prescient needs of every company to reduce operating costs. With artificial intelligence, telecommunications companies can manage data and data sources in real-time without having to fund data processing positions.
  • Another very real issue that exists within the telecom industry is the maintenance of mobile tower operations. Rather than having teams of people run twenty-four hour maintenance on mobile towers, AI can be deployed to page engineers of problems that need to be solved before they arise.
  • With an increasing need to offer personal connections to customers, artificial intelligence can help the telecommunications industry keep up with the times by allowing virtual assistance to manage consumer engagement.
  • It’s worth a reminder that predictive analytics can help with more than just hardware and software maintenance. Marketing teams in the telecommunications field will be grateful for the way that AI is able to automate market segmentation, lifetime value predictions, and even much of the lead generation process.
AI in telecommunications

Challenges of Using AI in the Telecom Industry

Despite all of these pressing reasons to adopt artificial intelligence in your telecommunications business, there are a variety of challenges that must be considered. Namely, there is a tremendous lack of resources for those looking to implement artificial intelligence strategies. From lack of qualified network engineers to lack of tools, there is certainly a learning curve that must be considered.
While this may seem overwhelming, artificial intelligence is all about incremental change. In other words, you can drive your company to success using AI with mere baby steps. Consider implementing more comfortable strategies with lower barriers first, like virtual assistants for your customer service team. Once your company builds trust in that technology, move on to the next, more advanced step.

At the end of the day, the worst thing that a business could do is remain inactive as it pertains to artificial intelligence in the telecommunications industry. As this market continues to multiply exponentially over the coming years, those who don’t begin to develop at least a cursory understanding of the work that they will be up against will be left in the dust by their more innovative, tech-savvier counterparts.

Forecast of AI in the Telecom Market

Just as it did from 2017 - 2022, the global AI market in the telecommunications sector is projected to grow by another 50%. (Talk about a steady industry!) This would represent a growth of multiple billions of dollars.

Most experts predict that the technologies used for customer service and predictive maintenance will continue to grow in efficiency and complexity, and will require network engineers with a strong mathematics background who will be capable of collaborating with the machines to create long-term processes that replicate human thought and action.

Consider taking some steps to train your team now, rather than later. Work with your operations department to determine the right places to begin implementing AI, as well as places of interest to target in the future. Continue to learn as much as you can, and offer your employees the chance to learn alongside you. Trust between humans and artificial intelligence systems must be developed in order for this relationship to be effective–ensure that you speak candidly with your team about opportunities for upskilling to address these new and exciting challenges.

Finally, because AI relies on good data to do its job, take the time now to invest in your current data infrastructure and ensure it is in optimal shape for your future artificial intelligence adoption.

Trust Integrio to Lead Your Company Through the Challenge of Adopting an AI Strategy in the Telecommunications Market

The team at Integrio offers customized enterprise solutions, and has been helping clients implement their technology strategies for more than two decades. We offer a variety of tailor-made telecommunications services, handled by experts in the telecommunications field and the technology strategy field alike.

We can design and implement software to complement your existing network or even create a telecom management system that offers deeper organization and end-to-end security. When it comes down to it, if you’re looking for experts in your field, who are talented in assisting companies through the process of digital transformation, look no further than Integrio.


AI in Telecommunications: Top Challenges and Solutions Current State of AI in the Telecom Market Types of AI Most Commonly Used by Telecommunications Companies Ways to Utilize Artificial Intelligence in the Telecommunications IndustryBenefits of Integrating AI into Your Telecommunications StrategyForecast of AI in the Telecom Market

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