The telecommunications industry has progressed from landline telephones to dial-up internet connections. Te­chno­lo­­gies such as artificial intelligence (AI) ha­ve helped in this transition. Today, AI has become central to the digital transformation of telcos, as it aids the delivery of superi­or performance in the short and long terms.

In India, telecom service providers have been warming up to the idea of automating telecom networks by leveraging cutting-edge technologies such as AI. AI enables the telecom industry to focus on benefiting customers with better services and building strong relationships with them for business growth. Further, the technology simplifies and expands the mining process for data aggregation and collective intelligence in order to help en­terprises. In addition, businesses can use AI solutions to manage the design, deve­lop­ment and deployment of AI innovations for better results. Even during the Covid-19 pandemic, when maintaining physical networks was a huge challenge, telcos that had already introduced some level of network automation benefited, making the industry realise how important it is to automate networks and build a future-rea­dy ecosystem.

Market dynamics

According to a report by Acumen Rese­arch and Consulting, titled “Network Au­tomation Market Size, Share, Analysis Re­port and Region Forecast, 2022 – 2030”, the global network automation ma­r­­­­k­et amounted to $3,957 million in 2021 and is estimated to reach $28,408 million by 2030, at a significant compound annual growth rate of 24.6 per cent from 2022 to 2030. Enterprise networks are currently under pressure, with more users, devices and applications relying on them for essential connectivity to a wide range of endpoints. In response, organisations are increasingly showing interest in new net­work architectures and advanced management tools that leverage AI to create self-driving or autonomous networks.

Automation has played an important role in maintaining IT operations during the pandemic. Meanwhile, in order to ma­­in­tain their foothold in the network auto­mation landscape, the competitive strategy of the current market leaders has been quite aggressive, mainly driven by their acquisitions of various start-ups and solution vendors in the market. Key players in the market aim to deliver highly secure, au­tomated, software-defined and intellige­nt platforms to their customers. The strategic priorities of these companies include in­creasing the value of their networks, accelerating their pace of innovation and transforming their business models.

Potential uses cases

The telecom industry is leveraging the potential of AI to analyse and work out the large volume of big data. It helps in gaining competitive and useful insights in or­der to improve business processes, operations and user experience; and increase sal­es and revenue through the introduction of new improved services and products in the telecom industry. Moreover, when it comes to 5G networks, AI is no longer a lu­xury but a necessity for tackling the tremendous complexity that comes with 5G. AI, along with the data and au­tomation capabilities that come with it, supports the diverse ecosystem of evolving networks in a way that humans alone cannot manage.

The future scope of AI in the telecommunication industry looks promising. Its potential use cases include the following.

Network optimisation

Network optimisation is a common use case of AI. It helps in building different self-optimising networks in the telecom industry. These allow operators to auto­ma­tically optimise the network quality based on traffic information by region and time zone.

AI in the telecom industry uses advan­ced algorithms to look for patterns within data, enabling telecom organisations to both detect and predict network anomalies. Furthermore, AI is used to optimise and configure various networks to make it easy for end users to leverage the advantages of stable network performance.

Preventive maintenance

AI-enabled predictive analytics is helping the telecom industry offer better services and products to customers using relevant data. Sophisticated AI algorithms and machine learning (ML) are used in the telecom industry to predict results based on historical data. This means operators can use data-driven insights to monitor the state of equipment and anticipate failure based on patterns. Implementing AI in telecom also allows communications service providers (CSPs) to proactively fix problems with communications hardware, such as cell towers, power lines, data centre servers and even set-top boxes in customers’ homes.

Real-time analytics

The telecom sector is witnessing a huge transformation from 3G and 4G to 5G connections for its customers. It is a challenge for telecom businesses to me­et users’ changing requirements. Real-time analytics, with the help of AI tools, helps in creating the best and most user-centric versions of particular services and products.

Virtual assistants and chatbots

Using AI-enabled chatbots and virtual assistants, businesses can deliver round-the-clock support and assistance to customers without any waiting time. AI adoption in telecom helps service centres contend with the overwhelming number of support requests for installation, set-up, troubleshooting and maintenance. Using AI, operators can implement self-service capabilities showing customers how to install and operate their own devices.

Moving to automated networks

Acknowledging these benefits, telcos in India are investing heavily in automation. With the shift to cloud and the fast moving landscape, organisations are becoming inc­reasingly dependent on the success of their networks. AI has the powerful ability to unify and make sense of a wide range of data from diverse sources such as devices, networks, mobile applications, geolocation, detailed customer profiles, service us­age and bills. Using AI-driven data analysis, te­le­­coms can increase their rate of subscri­ber growth and ARPUs through smart up­selling and cross-selling of their services. By anticipating cu­stomer needs using real-time analysis, telecoms can make the right offer at the right time over the right channel.

Bharti Airtel has partnered with Aviat Networks Limited for wireless multiband radio solutions. Aviat’s multiband vendor-agnostic feature enables traffic aggregation from multiple links, which in turn reduces network congestion and provides better speeds to customers. Airtel will de­ploy unique dual-channel E-band radios to augment its existing installed micro­wave network as well as new greenfield lin­ks, to support its accelerated 5G network build-out. Moreover, over the past two years, Air­tel has entered into partnerships with IBM, Red Hat, Cisco and Eric­sson to mo­dernise its network and en­able automation. Recently, Airtel renewed its agreement with Ericsson to provide pan-Indian managed network operations th­rou­gh the Ericsson Operations Engine. Under the partnership, Ericsson will deploy the latest automation, ML and AI technologies to enhance Airtel’s mobile network perfor­ma­nce and customer experience (CX). The operator has also dep­loyed Avanseus’s predictive maintenance (PdM) solution ac­ross its operations. Avanseus’s PdM applies AI analytics principles to Airtel’s network data to uncover actionable operational insights.

In a similar move, Reliance Jio has part­nered with Guavus to leverage the latter’s AI-based solutions in order to provide real-time CX and predictive analytics that would enable Jio to automate network troubleshooting and garner key marketing insights. This will help Jio offer superior service to its customers, while addressing critical service operations through intelligent automation.

Further, Vodafone Idea Limited (Vi) has selected Cisco for its network automa­ti­on systems, seeking to boost user experience and accelerate the launch of new services on its 4G and future 5G networks. Mo­reover, Vi has automated its IT infrastructure and operations end-to-end by adopting the Red Hat Ansible Automation Platform. Besides, the telco has partnered with Nokia to deploy over 5,500 time division long term evolution massive multiple input multiple output cells in the 2500 MHz spectrum band in eight service areas – Mumbai, Kolkata, Gujarat, Haryana, Ut­t­ar Pradesh (East), Uttar Pradesh (West), the rest of Bengal and Andhra Pradesh.

Meanwhile, state-owned Bharat San­ch­ar Nigam Limited (BSNL) has partne­red with Nokia for industrial automation solutions. In a move towards automation, BSNL has signed an MoU with Cie­na. Under the MoU, Ciena’s 5G network sol­utions will add scale and enable network automation in order to support a new age of mo­bile connectivity at BSNL.

Summing up

AI plays an essential role in digital transformation across all verticals. The crucial integration of AI technology with the telecom industry will help, assist and guide CSPs in delivering, managing, optimising and maintaining the telecom infrastructure necessary today and in the futu­­re. Moreover, increasing demand for a sa­fer, smarter healthcare system with intent-based networking technology, the growing need to detect and identify old hardware, compliance issues, storage issues, and the increasing need for zero-touch provisioning and unified network visibility, are the key factors driving the growth of the network automation market.

Going forward, as big data tools and applications become more available and so­phisticated, the future of AI in the telecom industry will continue to develop. Em­ploying AI, telecom companies can co­ntinue accelerating growth in this hi­gh­ly competitive space.

Anand Kumar Sah