Artificial Intelligence in Telecom: How Big, How Soon?

Artificial intelligence now is a “thing” like “computing” was once a thing. But it might be quite reasonable to assume that, in the not distant future, AI will be embedded into products, processes and venue as routinely as computing now is part of the background fabric.

In the communications business, that should range from customer-facing service to the operation of core networks, enhancing pricing and packaging decisions, service configuration, resource allocation, network management, energy efficiency, use of assets to simple routing decisions.

Commercial AI revenues are expected, by some, to climb from less than $1 billion to perhaps $5 billion by 2020. Revenues might reach $31 billion to $38 billion, up to perhaps $41 billion, globally, different forecasts suggest, by 2024 to 2025.

Some forecasts are more aggressive than that, calling for a U.S. market of perhaps $67 billion for robotics applications by 2025.

Humana, for example, using AI to assist agents in its call centers, to help agents predict customer behavior while on calls. Right now, AI sometimes provides a digital coach. In other cases, AI might handle an inbound call until escalation to a human agent is required.  

In the future, AI, with big data sets to work with, might go even further. Some are working on ways of using machine learning to directly handle inbound calls without agent intervention. Indeed, one premise of AI is that it can be used to automate any process.

“Amelia can, after two months of learning from her human colleagues, handle over 60 percent of support tickets on her own,” argue researchers at  Kairos Future.

It would be fair to note that researchers have been working on AI processes for half a century, including research into deep learning, machine learning, natural language processing (NLP), and computer vision, machine reasoning as well as core computing.




It is anecdotally worth noting that among the firms pushing to create commercial AI platforms are firms with huge exposure to consumer apps and business models, including Amazon, Microsoft, Google, IBM, Salesforce and Baidu.




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