Innovators are starting to introduce the potential opportunities for artificial intelligence (AI) in telecom. Agents are being freed up for more complex customer requests by virtual agents able to handle routine questions, invoice payments, and order inquiries. This is just the beginning of how AI in telecom is poised to disrupt customer interactions, security vulnerabilities, and data insights.
There are two major trends currently shaping AI: the growing acceptance of unsupervised models and explainability. While these can seem contradictory, they each offer critical innovative opportunities. Here’s an explanation of each:
Unsupervised models are increasingly being embraced by regulatory bodies. One of the major influences for this development is the awareness that cybercriminals are tapping into unsupervised models, so it makes sense to utilize the technology available to combat their efforts. Unsupervised models have always been a trickier sell because it can be challenging to explain why a particular pattern was detected, especially in cases where it’s harder to even see a pattern that the AI machine is seeing.
Experts say that trying to tap into AI without the power of unsupervised models essentially limits its effectiveness. The curiosity of this type of AI is necessary to identify real-time patterns. AI in telecom should increasingly see a clear path to innovation as regulators embrace this area of modeling.
Explainability is emerging as an important area of AI because of the growing influence of regulations like the European Union’s General Data Protection Regulation (GDPR) that require businesses to be able to explain to a customer why a particular action was taken, a certain score was given, or a rating was issued. Companies also recognize the influence explainability has on their customer satisfaction levels.
With all of the advances that machine learning has made, customers are often still met with little in the way of answers when attempting to understand a company’s actions. There’s a need for better transparency surrounding how AI in telecom is treating customer data and making decisions based on that data.
These two concepts appear to be contradictory as innovators unleash the power of unsupervised modeling, which can be harder to trace, but both are important for the better understanding of data and predictive insights. As unsupervised modeling grows in influence, it will demand better tools for explainability to support good customer service.
For more information about the role of AI in telecom and how it might impact your enterprise in the future, contact us at AMD Communications. We can talk with you about harnessing the latest innovations in machine learning and AI for better customer insights and improved service.