How Internet Providers Are Using AI and Data Analytics To Help Customers

Explore how AI and data analytics are revolutionizing internet providers' approaches to customer satisfaction and service efficiency!

9 Min Read
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AI has often been hailed as a revolutionary force that will make activities across industries more efficient while cutting costs.

But AI uses data analytics to reach conclusions, and consumers are understandably nervous about what that would mean to them.

However, privacy and data protection concerns are addressed by legislation, and there may be many benefits to consumers when internet providers use AI and big data.

You may find that AI is actually doing less than you expected in this field at present. But it’s showing promise and may ultimately lead to lower costs and better service for internet providers’ customers. 

According to Tomas Novosad from NetSpeed Canada, here are some of the benefits you may already be experiencing, along with the challenges ISPs are facing as they move towards AI-based efficiency.

Canadian ISPs and AI

1. Keeping Remote Areas Connected

People living in remote areas must often rely on satellites to stay connected. However, this technology can be unreliable. The University of Waterloo partnered with the National Research Council of Canada to investigate how AI might help to mitigate this issue.

They leveraged machine learning and AI to develop a better approach to monitoring satellite network performance. The result, they say, allows for more effective detection of anomalies, allowing them to be addressed before real problems arise.

2. Bell: Optimising Service Teams, Automating Processes

As Canada’s largest ISP, it’s no surprise that Bell has been working on applying AI to interpret big data in a quest for greater efficiency. It has already implemented a virtual manager that coordinates Bell’s customer operations department.

Company technologists say that there’s simply too much incoming data for traditional dashboarding to be effective in managing and prioritising outputs. Bell reports that it has experienced better sales and lower customer churn since implementing AI in this area.

The secret, says a Bell representative, is a combination of predictive analytics and the ability to make better use of real-time data.

Robotic process automation (RPA) development is still under development, but the company hopes to reach a point where resources are deployed and workflows are activated based on predictions and real time needs. For example, AI can be used to predict service level changes such as high demand and respond accordingly.

3. Rogers Invests Billions in AI to Combat Outages

In July 2022, Rogers clients experienced a service failure lasting 19 hours, causing havoc that extended from grounded flights to people being unable to call emergency services.

In the same month, Rogers announced that it would invest C$10 billion into artificial intelligence solutions, testing, and oversight to prevent the recurrence of the disastrous outage.

Other than mentioning its AI-powered virtual assistant (chatbot), Rogers has so far been relatively silent on the specific ways it is using AI. It would be safe to assume that it is working on functionality similar to Bell’s – predictive analytics and real-time monitoring that can pick up impending issues before they become serious problems.

On an interesting side note, Rogers has also been exploring other AI applications, including its use in wildfire-detection cameras and the regulation of traffic lights to prevent traffic congestion.

ISPs, AI, and Big Data: a 2024 Perspective

Towards Autonomous Networks

According to industry insiders, ISPs around the world are facing challenges in reaching the ultimate goal towards which they are working: fully autonomous networks.

A primary concern is that if AI is implemented too quickly, errors and oversights may occur and these could impact millions of subscribers.

Obstacles currently include a lack of preparedness and in-house skills, as well as data that is not configured in such a way that AI can properly analyse it. Altering this presents a challenge, potentially calling for a full cloud architecture transformation.

Despite these challenges, ISPs have made progress. Although few of them are publishing details on how close they are to autonomous AI-run networks, it remains an industry talking-point. 

Load Balancing

Broadband usage demand consists of rapidly changing spikes and dives. They occur too rapidly for the human mind to process, but AI is already being used to identify them.

So far, there’s still uncertainty about allowing AI to make network adjustments on auto. AI is still pre-programmed and basically consists of a series of algorithms.

The fear is that even a small error in programming could be magnified, triggering out-of-control responses that would be hard to undo. All the same, AI load monitoring capabilities are already an improvement.

As AI learns and improves under human guidance, we continue to move closer to a situation in which fluctuating internet speeds will be less of an issue for consumers.

AI in Customer Service

Before you assume this is just about chatbots, and give up in disgust, there’s more to AI in customer service than just that.

Admittedly, there’s common consensus that most customers would rather talk to a human, but if your inquiry is a routine one, there’s no reason why a chatbot can’t handle it. If that reduces costs for your ISP, it may mean you see fewer price increases!

Leaving the almost-universal hatred of “talking to a bot” aside, there are other ways that AI can improve customer service – and you may already be experiencing its benefits.

In the past, making a routine enquiry would have meant navigating a range of menus and links to “resources.”

AI can simplify this process by attempting to interpret your request. Besides this, it can be used to route your calls while, behind the scenes, company representatives may be using internally-trained private AI to find answers to your questions.

In addition, AI could be working to help customer service representatives to analyse your past interactions. This allows you to resume the conversation you last had without having to go through all the preceding steps involved in explaining your issue.

And, of course, that chatbot that persistently misinterprets your needs is learning all the time. Much as you hate it right now, a time may come when it’s able to handle just about any inquiry.

ISPs, Big Data, Machine Learning, and You: The Future

For ISPs, their employees, and their customers, AI has already affected day-to-day routines and the results that flow from them. We can expect much more in the near future as ISPs work to integrate AI into almost every aspect of their operations.

If you’re an employee, this could be bad news. AI-related job-cuts across industries are already a reality. However, as a consumer, advances in AI and machine learning could ultimately lead to better service reliability and lower costs.

As for that chatbot, perhaps we shouldn’t hate it quite so much. As long as you can still access human support with relative ease, it could be helping you to keep internet access affordable.

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