Artificial Intelligence in Practice

29Verizon: Using Machine Learning To Assess Service Quality

Verizon started life as one of the “baby Bells”, coming into existence initially as Bell Atlantic when the US Justice Department forced the breaking up of the Bell telephone conglomerate in 1984.

Today, as Verizon Communications, it is one of the largest communication technology companies in the world. It is the No. 1 provider of wireless subscription services in the United States¹ and it offers high-speed fibre optic broadband services to millions of US subscribers through its Fios service.²

Until recently, Verizon's main source of data on how well the network was running and the quality of service experienced by its users came from customer feedback.

It now monitors traffic and data across its network and uses machine learning to understand how service quality is affected by usage spikes, as well as external factors such as the weather and changing customer habits.

Verizon brought additional machine learning expertise into the business through its acquisition of Yahoo! in 2017.

What Problem Is Artificial Intelligence Helping To Solve?

Monitoring a network of the scale of Verizon's to understand where faults and outages occur takes a monumental amount of effort.

Traditionally, this has been done through customer feedback –essentially waiting for something to go wrong and the complaints about poor service to start flooding in.

It was only possible to react to problems after they occur – meaning that even if Verizon ...