The Advancement of Artificial Intelligence in Telecommunications

Telecom Business Review | Saturday, October 01, 2022

This is an exciting time for the telecom industry, but board directors and C-suite executives must keep the road ahead to artificial intelligence in mind.

FREMONT, CA: The telecom industry is experiencing more innovation due to artificial intelligence (AI) and the internet of things (IoT). Telecoms are also fueling growth with AI rather than simply offering essential services like telephony, internet, mobile capability, and network connectivity. According to Fortune Business Insights, the IoT age will enhance the growth of telecom providers by more than 25 percent between 2021 and 2028.

The sheer volume of data reservoirs tapped by telecom companies includes mobile devices, networks, geo-location intelligence, customer profiles and log behaviors, services and service utilization, sales data from customer communications, billing, contracts, and telecom companies adding AI capabilities. The source areas for data aggregation and intelligence mining are virtually limitless. The design, development, and deployment of AI innovations in this industry are fascinating because they allow for the creation of an intelligent customer profile by combining all service and usage habits into an AI model to forecast future share of wallet, upsell opportunities, and churn.

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Utilizing AI enables telecom firms to obtain actionable insights, deliver a better customer experience, enhance operations, and raise net new or renewal revenue.

APPLICATIONS OF AI

Network Optimization: IDC reports that 63.5 percent of telecom companies actively utilize AI to enhance network infrastructure. AI has long existed in network optimization, particularly in cyber security domains, allowing communication service (telco) providers to optimize and navigate network traffic quickly. Using AI monitoring systems, telecom providers can automatically reroute traffic if they can forecast network anomalies (behaviors that deviate from the norm) and rectify problems before they occur. Self-optimizing networks in telecom businesses are expanding at a CAGR of more than 50 percent, making this a lucrative industry.

For instance, Nokia launched its own machine learning-based AVA platform, a cloud-based network management solution that enables more efficient capacity planning. Additionally, it forecasts service degradations on cell sites up to seven days beforehand.

Innovative alliances are increasingly being developed. For instance, eleven-x, a global provider of wireless Smart City solutions, has partnered with SaskTel, an industry-leading Canadian telecommunications company, to optimize Information and Communications Technology networks in Saskatchewan. SaskTel can build and enhance robust AI solutions by combining its expertise as a telecommunications provider with startups such as eleven-x with strong AI foundations.

Robotic Process Automation: Robotic Process Automation (RPA) is a type of business process automation technology based on AI that improves operational efficiency by enabling telco operators to more efficiently manage their back-office operations and handle large volumes of repetitive and rules-based tasks, such as order fulfillment, workforce management, and mundane data entry. Also, the RPA industry is anticipated to reach 13 billion USD by 2030, with nearly universal adoption anticipated over the following five years.

RPA can simplify telecom operations and generate recurring income streams by providing quick, high-quality, and inexpensive services.

One of the innovative areas focuses on streamlining sales order processing efficiently by utilizing a well-structured workflow in Salesforce. There are requirements to push in more accurate and accessible customer data sourced from areas such as email, company, demographics, personal interests, psychographic profiling (communication style), relationships (social connectivity ties in socially visible interaction networks), etc. When united, these areas can gather and enable collective intelligence to improve revenue acceleration in innovative ways. Companies such as IntroHive are market leaders in this use case. They provide an AI-powered SaaS platform that enables businesses to realize the full value of their relationships and underutilize data across the enterprise to increase revenues, employee productivity, and customer experience management.

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