Artificial intelligence (AI) is rapidly transforming the telecommunications industry, driving operational efficiencies, optimising network performance, and significantly enhancing customer sxperience (CX), writes Mirza Bukva, head of telecom partnerships Africa at Infobip.
By harnessing machine learning, natural language processing, and real-time data analytics, telecom companies are collaborating with cloud communication platforms, evolving from traditional service providers into tech-driven innovators—often referred to as “techcos.” This shift opens up new revenue streams, positioning telecom operators as key players in the digital economy.
AI enhances customer experience
At the forefront of AI’s influence is the way it improves customer interactions. By analysing vast amounts of data, AI personalises engagements through tailored recommendations and promotions, predicts maintenance needs such as customer interactions and feedback to identify trends or potential issues, and proactively manages services.
AI-powered virtual assistants and chatbots offer customers quicker resolutions and a more reliable service, provide 24/7 support, and improve customer satisfaction and loyalty.
Optimising network operations
AI-driven network solutions are reducing congestion and enhancing operational efficiency. Advanced AI algorithms monitor large volumes of real-time network data, enabling telcos to identify potential issues, predict failures, and optimise traffic flow. For example, AI can automatically adjust network settings to redirect traffic during periods of congestion or equipment failure, minimising disruptions.
AI-driven network optimisation extends to energy management as well, where it adjusts power consumption based on predicted peak usage times, contributing to more sustainable operations.
Driving innovation
AI is also driving innovation within telecoms, fostering new services and business models. With the integration of AI and 5G networks, telcos are expanding into industries like healthcare, agriculture, and logistics, offering smart IoT applications that manage resources in sectors such as smart cities and energy grids.
This creates opportunities for telcos to venture into new markets and provide cutting-edge services, like smart home solutions and AI-based IoT integrations that meet the evolving demands of the digital economy.
Improving decision-making
AI’s ability to process and analyse customer data in real time enables telcos to make informed strategic decisions. The data-driven insights from AI allow operators to anticipate customer needs and market trends.
With 65% of customers reporting higher satisfaction from AI-powered interactions, telcos can create more engaging and predictive CX journeys, resulting in increased Average Revenue Per User (ARPU) through smarter upselling and cross-selling initiatives.
Addressing key challenges
AI is also instrumental in solving some of the persistent challenges faced by Mobile Network Operators (MNOs):
- Network Congestion: AI predicts and manages traffic patterns, dynamically adjusting resources to prevent congestion and ensure efficient network performance.
- Competition: Predictive analytics help MNOs understand market trends and customer preferences, enabling them to offer personalised services that stay ahead of competitors.
- Churn: By analysing customer behaviour, AI identifies potential churn risks, allowing operators to implement targeted promotions and improve customer support, thereby retaining customers.
- Fraud: AI’s sophisticated algorithms detect and prevent fraudulent activities in real time, protecting the network and its users. AI’s fraud detection is already highly successful, with over 90% of companies reporting real-time fraud prevention.
- Sustainability: AI contributes to sustainable practices by optimising energy use in network operations, adjusting power consumption based on anticipated peak usage times.
Monetising AI in telecommunications
The integration of AI presents a wealth of monetisation opportunities for telecommunications companies. AI-driven services such as advanced analytics, network management tools, and personalised customer experiences not only attract new customers but also enhance retention among existing users. Internally, AI-powered tools streamline processes, reduce operational costs, boost efficiency, and drive profitability.
For instance, conversational AI chatbots automate routine enquiries, such as balance checks, top-ups, and FAQs, significantly lowering customer service costs. These tools handle high volumes of interactions simultaneously, ensuring faster response times and freeing agents to address complex issues.
Predictive AI analytics further drive revenue by enabling precise upselling and cross-selling opportunities, such as recommending data plan upgrades to customers approaching their limits.
Telecom leaders around the world have harnessed AI through Communication Platforms as a Service (CPaaS) solutions. These innovations allow customers to perform actions like bill payments, subscription management, and support queries via messaging platforms like WhatsApp and RCS, simplifying customer interactions and driving engagement.
Notably, McKinsey’s research highlights the financial advantages of AI adoption, with AI-leading companies achieving a five-year revenue CAGR 2,1-times higher than their peers and delivering a total return to shareholders 2,5-times greater. This underscores the transformative potential of AI for telcos striving to remain competitive and profitable.
Preparing for AI integration
Before integrating AI, MNOs need to carefully consider several critical factors:
- Data Privacy and Security: Compliance with data protection regulations is essential, ensuring customer data is handled securely.
- Technical Expertise: Telecom companies need to either build or acquire expertise in AI and data science to manage AI integration effectively.
- Infrastructure Compatibility: Assessing and upgrading existing infrastructure is crucial to support AI technologies.
- Change Management: As AI becomes integral to operations, staff training, process adaptation, and alignment of business strategies with AI capabilities are necessary.
Overcoming barriers to AI adoption
Despite the benefits, several factors hold back some MNOs from adopting AI. The investment required for AI technology, including infrastructure upgrades and skilled personnel, can be prohibitive due to high initial costs. Integrating AI into existing systems and processes presents complex implementation challenges.
Managing the vast amounts of data generated by telecom networks, particularly with legacy systems, can be daunting. Additionally, navigating the regulatory landscape concerning data privacy and AI ethics adds to the complexity. Organisational inertia and resistance to change further slow-down the adoption of new technologies.
By addressing these challenges, telecom operators can effectively leverage AI to transform their operations, enhance customer experiences, and unlock new revenue opportunities while boosting efficiency and fostering customer loyalty. The future of telecommunications is undeniably intertwined with AI, promising a more efficient, innovative, and customer-centric industry.