The value of Artificial intelligence (AI) for mobile operators may be one of the less widely discussed uses of AI. It could, however, be considerable in areas like predicting demand patterns and anomalies in dense urban areas, proactive maintenance and improved planning, and – believe it or not – call centres.
An important area for MNOs to harness AI is to power chatbots and digital assistants, as a way to transform their relationship with customers, reduce spending on call centres and improve user satisfaction. Telecom Italia, for instance, recently outlined how it would replace some customer service staff with chatbots as a result of an AI partnership with Microsoft, though it did not give numbers. It has been engaged in a broader headcount reduction over the past year.
It said its Microsoft deal would be an important component of its DigiTIM program of digital transformation and would help simplify and enhance its relationship with its users.
Some operators have downplayed the threat to jobs from automated networks and customer interactions, but Telenor expects to cut 20% of jobs as a result of operations automation, while MTS in Russia plans to cut almost 10% of its 11,000 customer service positions this year, replacing them with chatbots.
Telefónica is also using Microsoft technology to underpin its Aura digital assistant, which will answer customer queries, while Vodafone and Orange are working on chatbots and assistants with IBM and its Watson AI platform. IBM is also pushing Watson as an enabler of automated network management and operations.
At the same time as enhancing customer interaction, predicting demand patterns and improving maintenance, AI looks like playing a part in the continuing development of one of the most talked-about technological advances in mobile communications of recent years: SON. Last month, at the Zero Touch & Carrier Automation Congress, Telefónica said it was planning to increase its investment in automation tools, including a “cognitive self-optimizing network (SON)” technology based on AI.
This would see Telefónica making an early move towards what Rethink Technology Research, in its recent report about AI-driven SON, regards as a third generation of SON tools.
The first focused on self-organizing more than self-optimizing and was largely concerned with housekeeping activities like automatic neighbour relations. The second added a wider range of capabilities, including many aspects of optimization, and extended SON systems beyond the RAN – into end-to-end networks and taking account of virtualization and cloud platforms. The third brings AI into play to enhance the performance, flexibility and value of SON still further.
Juan Carlos Garcia, Telefónica’s director of technology and architecture, told the conference: “The next step for 5G will be moving to a cognitive SON where AI and deep learning algorithms will be necessary to improve the efficiency of SON activities in our networks.” Most of the work will take place between 2021 and 2025, in tandem with 5G roll-out in many of the operator’s territories. That will include automation and programmability of core and transport networks, not just the RAN, while all these elements will be virtualized over time.
The upshot of this and other activity is the distinct possibility that, while AI in mobile communications may not be stealing the AI headlines, it could indeed have as significant an effect on mobile communications as it is expected to in the much higher-profile areas of factories and healthcare.
Advising our clients on managing the (potential) 5G future is a very strong part of our business and how operators and their partners will make 5G pay is one of the questions we are most often asked. So could AI be the answer? Could it enhance network efficiency? Could it enable more functionality at less cost? Could the new services enabled offer new staff opportunities as well as removing others?
Whatever is claimed, our aim is to get at the reality. That’s why we are looking forward to assessing the real-world viability of AI as an enabler of cost-efficient and effective 5G and, through our collaborative work with research groups and 5G projects, reporting back from the 5G frontline on what is – and isn’t – likely to work.