Telco Trends: Why the Industry Needs AI

• • industry trends, Smart Home

As a broadband installer, you are likely affected by the growing field of Artificial Intelligence (AI) technology. Every time you wire a media distribution enclosure for a customer, you are powering the potential for AI in their home. You can also be supported by AI – or you will be. AI may even become a revenue stream that keeps the telecommunications industry vibrant.

AI is a term used to describe machines, which include computers, that carry out tasks by processing information in an “intelligent” way. For example, by making a decision based on a set of circumstances. Virtual assistants like the Amazon Echo and Google Home are examples of AI that are currently popular.

Another term that is often used to describe AI is machine learning or ML. Machine learning is a subset of AI in which machines – generally some type of software – process data and improve their own capabilities.

What jobs does AI do?

There are many ways that AI can support the work you do. The most obvious application is customer service. Chatbots are a form of AI already widely used for online customer service. Expect to see more telcos use them in the future.

Another promising application for AI in telecommunications is network management. As broadband and wireless networks become more complex, it becomes more difficult to manage them through manual processes.

AI can monitor and make decisions about traffic flow on the network, and it can monitor network security at a scale not possible by other means. AI also has the potential to be predictive in network capacity planning. With AI running routine inspection and monitoring of the network, telcos can deliver better service to their customers and utilize their IT staff more effectively.

AI network management can be delivered via self-organizing networks (SONs), software-defined networks (SDNs), or network function virtualization (NFV). Self-organizing networks are used primarily in wireless networks. They are automated networks able to organize and optimize their performance.

SDNs and NFV are also technologies that support network automation. SDN is a structure in which the control software is separate from the physical infrastructure. NFV is essentially creating software to replace the devices that make up the physical network. This includes virtual routers and switches. They often work together, with SDN functioning as an intelligent control center for the NFV.

There’s one AI tool that might become your next assistant. IBM has a specialized network tool called Watson Field Service Advisor. This tool can process data from multiple sources – support databases, knowledge centers, inventory and network logistics, service manuals, field notes – and produce recommendations you can use in service calls. Watson continues to learn from each call, which is an example of machine learning in action.

While AI has the potential to serve the telecommunications industry, telcos also have the ability to serve – and profit from – this growing field of intelligence. AI needs information, lots of it, which is why data is now considered the world’s most valuable resource. And that wired connection you install into your customers’ homes and offices can collect billions of bytes of data each day. AI that uses analytics tools can transform that data into information that other organizations are willing to pay for. Telcos can monetize that resource by selling raw data or AI-acquired insights.

AI is still in its infancy, and sometimes the results of an AI project can be comical. Take, for example, the AI that was trained to name paint colors. Can you imagine your customers showing off their new Burf Pink accent wall? Not likely.

You won’t see robots making service calls anytime soon, but there is no doubt that AI will soon be a big part of telecommunications.