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How AI helps telcos improve connected experiences

As Artificial Intelligence (AI) promises to transform telecoms, CUJO AI reveals how AI-driven solutions and approaches can add value and help improve connected experiences and telco networks and operations.

December 5, 2023

4 Min Read

AI-driven solutions and approaches can outperform traditional telecom methods in a number of areas and provide tangible benefits to network providers. In this article, Santeri Kangas, CTO at CUJO AI, discusses the role AI can play in telecoms to improve connected experiences.

Kangas lays out the limitations of traditional telco solutions and where AI can step in. Further, he elaborates on the relevance of telco strategies for integrating AI into their operations. Kangas also reveals several key aspects that telcos might overlook when implementing AI.

Finally, he looks ahead into what AI applications we can expect to see in telecoms in the near-term.

CUJO AI offers machine learning (AI) solutions to telcos. What role do they play in a telco’s operations?

Our AI plays a key role in identifying devices, which are becoming more obfuscated. Identifiers such as MAC addresses are becoming increasingly unreliable, while network service providers need to accurately recognize devices to maintain telemetry and value-added services, such as parental controls. Our AI also accurately detects the device’s type and model, which helps telcos improve customer care and resolve issues more efficiently by knowing what devices are on a network.

Telcos use our AI-driven security to reduce malicious activities on their network and protect customers. These models observe devices in real-world conditions, detect abnormal behaviour, and identify malicious endpoints, such as phishing sites. These capabilities are very important, as our data from tens of millions of networks shows that over 62% of users* try to access a malicious website at least once a month.

What can AI do that traditional telco solutions struggle to?

AI allows telcos to do a lot more, but it is a question of getting the data first. Our AI models provide insights from various devices and applications. Telcos can use them to develop secondary algorithms for specific purposes. For example, if an AI model has all the necessary data, it can automatically address many customer issues to save customer service time and reduce calls. The cost savings, scale, and types of issues that can be addressed proactively is well beyond any traditional solution.

How does AI help improve the connected experience?

Significantly. It allows the telco to automate issue detection and resolution, personalize services, and reliably measure the quality of service. A typical scenario where AI transforms the connected experience is a customer working from home. They need their network to prioritize work-related tasks, and an AI can optimize the best connectivity for that user's specific devices and services. For example, if the AI system identified a work laptop being used for a video call, it would automatically give network priority to this device over other activities, like children streaming entertainment in another room.

Do telcos have an AI integration strategy? Or do they struggle to use and understand solutions like yours?

First of all, AI is no longer a tech issue, it is a leadership question. AI is relatively easy to implement, the pipelines and infrastructure are already there. The real barrier to entry is the data strategy, the investment in the data strategy, and the platforms that fuel the algorithms you want to put in place.

What telcos struggle with is data aggregation, since they usually have many data sources. Collecting the relevant data and getting it to a place where it is in a consumable format – consolidated, filtered, with features extracted and cleaned – is the bulk of the work needed to start using AI.

Most Tier-1 carriers understand the value of having all their data in a consumable format, but we don’t see that from smaller network service providers. In general, large telcos have more advanced data strategies and even teams of data scientists, while smaller providers usually don’t have these resources. They are more likely to approach AI as an isolated project, where large telcos have an understanding that the problem is multidimensional, and that AI can have multiple uses.

What’s a major thing that most telcos ignore when it comes to AI?

In general, they are under-investing in this area. Telcos have massive amounts of data, and AI is easily accessible. The key is to make the data consumable for the AI, which is 80% of the work, then the leadership needs to ask the right questions and act on the insights they get.

Data ownership is also extremely important. In many cases you will need to get to the raw data, and if you are just using a limited service that gives you access to some derivative data, your AI capabilities will be limited.

When you look 1-2 years into the future, what uses of AI in telco do you foresee?

I think in this short time frame, major providers will continue making their data easily usable for AI systems. We might see the first telcos capable of leveraging all the information they have, just as large tech companies are doing today. Hopefully, telcos will have a strategy to use that consumable data and work with regulators to leverage it for use cases that they need.Large Language Models will likely enhance customer service operations.

Looking further ahead, telcos that effectively integrate AI will gain a substantial competitive edge: their network quality, customer service effectiveness, and customer satisfaction will improve. AI will be the key to improving the NPS and cost-effectiveness of a provider and enhancing their value-added services.


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