Telecom operators are building new products and services on top of existing systems in order to better serve their customers. This is increasing the complexity of the existing networks, thus making the management of these networks difficult for telcos. This is where artificial intelligence (AI) comes in.

Adding AI to networks helps telcos to get ahead of service issues, reduce manual tasks and improve their operational efficiency. This also allows service providers to redirect resources towards creating a more unique customer experience. Service providers today are striving to make their networks adaptive in nature and AI-driven automation can enable them to achieve this. AI helps enhance network efficiency, cut down opex, and improve the quality and speed of services.

A look at some of the recent use cases of AI in the telecom industry…

AI and customer support

Telcos can enhance their customer support operations through AI. To this end, they have been deploying AI-based chatbots that take care of the routine customer queries and provide quick redressal to customers. These virtual assistants help address the large number of support requests for installation, troubleshooting and maintenance, which often overwhelm customer service centres. Using AI, operators can implement self-service capabilities that show customers how to install and operate their own devices. Further, AI helps telcos improve their customer relations by identifying the unique needs of customers and leveraging this information to provide personalised experience. AI can also enable operators to forecast the demand more accurately, anticipate the network load, and adjust capacity and throughput automatically. According to Juniper Research, AI-based virtual assistants can potentially cut business expenses by as much as $8 billion annually by 2022.

Given the potential advantages of AI for telcos in this field, operators across the globe are deploying AI to streamline their customer support operations. For instance, Vodafone has introduced a chatbot called TOBi to handle a range of customer service questions. The chatbot provides quick responses to simple customer queries, thereby reducing the grievance redressal time.

AI for network optimisation and predictive maintenance

Another use case of AI in the telecom sector is network optimisation. AI is helping operators build self-optimising networks, which enable them to automatically optimise network quality based on region and time zone-based traffic information. By deploying AI-based applications, operators can effectively identify patterns in data traffic, and accordingly perform predictive analysis on the gathered data to detect any kind of network anomalies. This enables them to proactively fix problems before customers are negatively impacted.

Further, AI-driven predictive analytics helps telcos provide better services by utilising data, sophisticated algorithms and machine learning techniques to predict future results based on historical data. Going forward, network automation and intelligence will enable telcos to address issues by performing root cause analysis. Moreover, AI-based predictive solutions will also allow them to adopt better-informed strategies and business plans to effectively address the emerging business needs and improve the customer experience.

Given the benefits of the technology, operators across the globe are exploring AI systems to monitor the state of equipment, identify patterns that predict failure and perform maintenance on a preemptive basis. For instance, AT&T has deployed AI-based drones to carry out the routine monitoring of its cell sites. The company then performs an analysis on the video data captured by the drones for tech support and maintenance of its cell towers. As per a recent IDC study, 63.5 per cent of operators are actively investing in AI systems to improve their infrastructure.

AI-driven robotic process automation

AI-based robotic process automation enables telcos to efficiently manage their backend operations by automating large volumes of repetitive and rule-based actions. This allows telcos to streamline the execution of labour-intensive and time-exhaustive processes such as billing, data entry, workforce management and order fulfillment. As a result, the telcos can direct their human resources to other more productive and complex tasks. According to a recent survey conducted by Deloitte, 40 per cent of the telecom, media and tech executives said that they had garnered substantial benefits from cognitive technologies. Of this, 25 per cent claimed to have invested $10 million or more in such technologies. Further, over 75 per cent respondents expect cognitive computing to substantially transform their companies within the next three years.


Recent industry initiatives

In July 2020, Orange and Google Cloud announced a strategic partnership to accelerate the transformation of Orange’s IT infrastructure and the development of future cloud services, in particular edge computing. The agreement reinforces Orange’s commitment to drive its internal transformation through the innovative and widespread use of AI in order to improve its operational efficiency and enhance customer experience. As per the agreement, Google will provide its know-how in cloud technologies, analytics and AI tools, as well as proven digital Orange and Google Cloud have also agreed to jointly create an innovation lab and a centre of excellence that will both foster innovation and growth. The innovation lab will enable new industry solution development based on data and AI within the broader framework of the evolving 5G/edge computing ecosystem. The centre will provide training in data, AI and cloud services to several thousand Orange employees.

Meanwhile, Bharti Airtel renewed its agreement with Ericsson to provide pan-India managed network operations through the Ericsson Operations Engine. The three-year deal will see Airtel launch the Ericsson Operation Engine during 2020. Ericsson will deploy the latest automation, machine learning and AI technologies to enhance Airtel’s mobile network performance and customer experience. Ericsson will also manage Airtel’s network operations centre and field maintenance activities across India. Further, it will provide network optimisation services, combining multi-vendor networks expertise with its machine learning/AI-enabled cognitive software suite. This will help deliver a better customer experience and improve the return on Airtel’s deployed network assets.

The way forward

AI-based applications are increasingly enabling telcos to better manage, optimise, monitor and maintain their elaborate network infrastructure. Going forward, AI is expected to see much deeper penetration in the telecommunications sector. As per a recent BCG study, AI will become central to the telcos’ transformation as it will help deliver superior performance in the short and long term. It will help telecom companies better cope with the fluctuating demand levels, adjust to supply chain disruptions, and adapt to sharp shifts in consumer confidence and priorities.

While telcos across the globe have started deploying AI, the level of adoption varies. In the long run, only those that are able to tap the full potential of the technology will be able to sustain in the market.