AI For Telecommunications Industry

MWC 2025 concluded with a primary focus on Artificial Intelligence (AI). Vendors, operators, and service providers presented AI use cases and outlined their future strategies.

What are the implications of AI for the telecommunications industry?

AI refers to the ability of machines, to mimic human intelligence. This includes creating algorithms and models that empower machines to execute tasks that typically require human intelligence.

The impact of AI in telecommunications is rapidly growing, as MNOs actively explores the potential of these advanced technologies. AI is proving to be a transformative force, driving improvements in operational efficiency, enhancing customer satisfaction, and fostering innovation within the sector.

With its powerful capabilities in data mining, processing, and analysis, many telecommunications companies are already adopting AI. Key areas where AI and Machine Learning (ML) are making a difference include:

• Machine Learning (ML): A subfield of AI, where systems leverage data to continuously improve their performance in specific tasks.
• General AI (GEN AI): A more advanced, yet theoretical, form of AI that could potentially handle any intellectual task a human can perform.

The scope for AI in the telecommunications industry is vast and promises a bright future. From network optimization to customer service, AI is proving to be a vital tool, significantly advancing the industry. Adopting AI is no longer a futuristic goal, but a strategic necessity for MNOs who wish to stay competitive. By implementing AI, MNOs can boost efficiency, improve the customer experience, and create more resilient and flexible business models.

Here are some of the primary ways AI is transforming telecommunications:

• Network Optimization: AI solutions, such as ML algorithms, can predict and address network issues before they arise, ensuring network reliability, reducing downtime, and optimizing traffic during peak times.
• Customer Experience: AI personalizes customer interactions by analyzing data to tailor services, while AI-powered chatbots provide 24/7 support. Sentiment analysis tools evaluate feedback to further enhance service quality.
• Predictive Maintenance: AI monitors equipment in real time to predict and prevent hardware failures, reducing operational costs and preventing service interruptions.
• Fraud Detection: AI can identify unusual patterns in data usage or call activity to detect and prevent fraudulent activity, such as identity theft or SIM cloning.
• Process Automation: Robotic Process Automation (RPA) automates routine tasks like billing and customer onboarding, streamlining operations and reducing human error.
• Enhanced Data Analytics: AI enables telecom companies to analyze large datasets, improving decision-making related to pricing, user behavior, and business strategies.
• New Revenue Streams: AI enables telecom operators to offer innovative services such as IoT connectivity and smart city solutions, diversifying their revenue streams.

At Banglalink, we are integrating AI into our practices and introducing AI-powered services for end users.

We have deployed bots for customer service and internal use.

AI-based social media sentiment analysis and VOC on customer care channels help us understand customer pain points and issues. We enable anomaly detection on network and platform dashboards, monitoring over 100 dashboards and 500+ platforms with AI. Soon, a self-healing network bot will handle basic L1 O&M interventions.

AI has transformed our sales and marketing channels, predicting churners and stock needs for our sales partners. Customized offers for customers are already available, and soon we will launch micro-segmented personalized offers and customer communication.

For customer complaint handling, AI assists in complaint triage and L1 CC handling, with a bot identifying issues and aiding agents with basic problems.

We have trained our AI system. The AI will replace internal libraries, with traditional library searches being replaced by CoPilot. 

We optimize our network using an AI-driven self-organized network tool and introduced AI for energy efficiency, adjusting carriers and computing based on customer habits, patterns, and traffic.

Our Network team uses AI-driven 2G and 4G Network Capacity Planning Bot. Tasks that previously took weeks can now be completed in ten minutes, significantly enhancing voice quality and reducing call blocking experienced by end users.

Our bots can understand English, Bangla, and Banglish text and conversation. We are capable of serving our customers with AI in their preferred form and language.

We work on user and entity behavior analytics. With the help of machine learning, we aim to enhance our control over user activities and respond to cyber security attacks promptly.

Process automation is another area where we extensively utilize AI. Processing large datasets requires significant time and necessitates a well-organized and precise framework. To address challenges and identify issues, we have implemented AI solutions. AI has already replaced labor-intensive processes, identified and resolved problems, and manages daily operational tasks.  

In-house GEN AI development is costly and time-consuming. Instead, we partnered with industry leaders to combine their platforms with our local capabilities. Our goal is to provide AI as a Service to customers. We aim to enhance our digital capabilities with AI to meet our customers' needs. We have high ambitions and hope to soon have AI interacting with customers on various channels to assist with their daily needs.

We plan to expand our AI capabilities and introduce robots for verbal interactions with customers. Currently, REN and MyBL engage with users, and soon H-AI will also be deployed. ZORA from Star Trek will no longer be the only system responding to  inquiries. However, it is still too early for us to develop technology similar to DATA from Star Trek.