Telecoms and Artificial Intelligence
Telecommunication companies face growing demand from clients for better customer experience as well as a wider range of digitalized products and services. By leveraging AI solutions, telecoms can benefit from the vast amounts of user data collected over years of operations. Such data is observed from devices, networks, user profiles, geolocations, mobile applications, service, and billing data. The Big Data is thus analyzed using AI techniques to spot trends and provide actionable insights in order to boost revenues, and improve cost structures, customer experience, and overall operations.
The value of AI applications in the telecom industry is great and many telecommunication companies have started to leverage their investments in four areas: Network Optimization, Preventive Maintenance, Virtual Assistants, and Robotic Process Automation.
Telecommunication service companies use AI solutions to build so-called Self-Organizing Networks (SONs), which give operators the possibility to automate the network-optimizing processes based on traffic information by region or time zone. Advanced algorithms are integrated to screen for patterns within large and unstructured data sets, enabling companies to both detect and predict network anomalies, to proactively fix the problem before the end-user is negatively impacted.
AI techniques for predictive analytics unfold much potential within data utilization activities, as algorithms accompanied with machine learning techniques can forecast future results on historical data. In turn, this means that telecoms can integrate data-driven insights into daily operations to monitor the state of equipment, predict hard asset failures based on patterns and hence quickly fix the problem. In the short term, network automation and intelligence will allow companies to integrate so-called root cause analysis and prediction of failures. However, from the longer-term perspective, these technologies will allow telecommunication services providers to underpin strategic goals, such as enhancing customer experience and efficient dealing with operational issues.
Conversational AI platforms are revolutionizing the current state of customer support. Such virtual assistances or chatbots are used to automate and scale one-on-one conversations extremely efficiently, as statistics suggest that in 2022 the technology will allow businesses to cut as much as $8 billion of operating expenses. For telecom companies, virtual assistants can help to deal with thousands of support requests for equipment installation, troubleshooting, maintenance and other inquiries.
Robotic Process Automation
Customers of telecom companies engage in millions of daily transactions, which are subject to human error. Process automation using robotics is one of the AI-driven solutions to solve the problem of repetitive, daily tasks such as back-office operations and large volumes of rules-based actions. By streamlining the execution of time and labor extensive processes such as billing, data entry, workforce management and order fulfilment, the solution can dramatically cut operating costs and free-up labor for more value-creating tasks.
Hence, we can suggest that the state of telecommunications services delivery is on its path to a radical change. The next generation of telecom providers will have to increase their capital expenditure, and risking short-term advantages to seize and benefit from the untapped growth opportunities in the foreseeable future. On the backbone of the pandemic, customers’ behavior has jumped 5-10 years ahead, to which telecom providers had to quickly adapt and improve the scope of services within both well-served and underserved regions.
Changes in operations caused by the wider usage of Big Data pushed telecom operators to deploy advanced analytical tools, AI and automation at scale to improve the economics of business and unlock new revenue streams, which in turn will boost business growth.
Currently, it is observed that telecommunication companies are starting to segment themselves into 3 primary business models, which are different in the nature.
Which assumes providing a wide range of diverse digital products and services. This model requires establishing operations in adjacent industries such as financial services, IT services, energy, professional services to create a diversified portfolio of digital products, where the endpoint of strategic development is to become big tech firm with telecommunication operations and financial license, to benefit from upselling and cross-selling opportunities, which may enhance revenue in the range of 2.5-4.0%.
Operational and infrastructure led
The model assumes that the company focuses solely on providing telecom services that capture the value of data and optimize the cost of running the telecommunications network. Incumbents operating under such a model will be required to focus on efficiency and low-cost or make hefty investments in 5G and other capabilities to achieve structural advantages. From the long-term perspective, implementing operational and infrastructure-led model will allow telcos to achieve cost saving in the following fields: network rollout and asset optimization, predictive maintenance and field force labor optimization, which according to field studies may cut business’s costs in the range of 5.0-10.0%.
Which from its name assumes concentrating operating activities on customer orientation, to deliver fully digital experience, including customer care. To succeed under this model, telecoms must emphasize on certain client segment and ace it. Providing excellent services personalization, managing churn rates, optimizing the pricing of digital products and services, and adapting AI-powered customer service solutions may provide the company with a competitive edge among other industry incumbents and enhance revenue generation in the range of 3.5-7.5%.
As business digitalization trend continues to unfold at the great pace, global telecoms are projected to increase capital expenditures by 3% annually for the next 3-5 years, to meet the market urge for fully digital products and services, faster internet connectivity, as well as Big Data and AI-powered solutions.