How the telecoms industry can get the best out of AI

The increasing complexity of telecom networks and services and the exponential growth in the amount of data generated have gone beyond the capacity of manual calculation. Telecom operators therefore are increasingly compelled to embrace AI to help them properly manage their networks, services, and customers. This Intelligence monthly briefing aims to separate noise from truth about AI and discuss how the communications industry can benefit from AI while avoiding potential pitfalls.

(Here we are sharing the opening section of this Intelligence special briefing to look into how the telecoms industry can best position itself vis-à-vis the ascendancy of artificial intelligence.The full version of the report is available for free to download here.)

What is AI and what does it mean for telecoms?

About a year ago the Intelligence team attended an industry event on the future of digital economy and the sectors closely interact with it. A panelist from the banking industry told the audience a story of his experience introducing AI to his team. One of his analysts commented after listening to the primer, “we have been doing this data analysis stuff for decades, and you suddenly started calling it artificial intelligence?”

In a way, the analyst was not wrong. The banking sector, as well as other industries, has been working with information since Day One. This includes acquiring, recording, organising, analysing, retrieving, presenting, and sharing of information. Earlier such tasks were primarily undertaken by human beings, like our analyst in the bank, assisted by specialised tools. But in recent years, the role that computers play in information processing has been expanding fast. Two main factors have contributed to the change.

First and foremost is the increasing availability of data. From medical diagnosis to instant trading in the financial markets, advancements in technology have made it possible for industry operators to access and extract data previously unattainable. This is further helped by the reducing cost of storing data. The exponential growth of available data is probably manifested most visibly in none other than the communications industry itself, which is powering many of the other sectors. This is a curse and a blessing. While the data available to us has vastly increased and has made advanced data analysis possible, it has also quickly made it impossible to manually process all of it.

The second main factor that has help enhance the role of machines in information processing is the growing computing power of the machines themselves. For over 50 years, the trajectory of the advancement of computing power has vindicated what Gordon Moore predicted in 1965 (which he updated a decade later). There is a broad recognition in academia and in industry that Moore’s Law is slowing down, while some even claim its end is in sight. Meanwhile, new approaches to keep computational advances going are being explored, including designing chips for specialised use cases, with Microsoft, Google, and China’s Baidu being the leading companies to do so. Unconventional technologies such as quantum computing, carbon nanotube transistors, and spintronics are being developed and invested in. In other words, computing power at our disposal, with reduced cost, has been growing, and is likely to continue to grow in the foreseeable future.

These two main factors, combined with other advances in technology, especially in software and algorithms, have driven computers to the forefront of information processing. In that sense, our bank analyst was right with the “intelligence” part but failed to appreciate the “artificial” bit.

AI for telecoms is artificial intelligence for a special purpose, or what the professionals call “applied AI”. To compare with the other two types of AI works, “strong AI”, which aims to develop a computer that thinks just like a human being, and “cognitive simulation”, which aims to understand and simulate how human brains work, applied AI has achieved the biggest successes. From medical diagnosis to credit line decisions, from climate models to camera designs, applied AI tools have equalled and often outperformed the best human experts. So is the case when it comes to telecoms.

The following sections of the report will examine how AI has helped deliver values for the telecoms ecosystem and where further improvements are to be made. It includes the following:

  • What AI can do and is doing for telecoms
  • New telecoms territories for AI to explore
  • Key challenges AI for telecoms is facing
  • An interview with Mark Beccue, Principal Analyst at Tractica, on topics related to AI for telecoms.

The full version of the report is available for free to download here.


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