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Banglalink, driven by a vision to become a leading digital service provider, is committed to innovation in both solutions and operational approaches. While exploring uncharted territories carries inherent risks, it also presents significant opportunities that are essential for maintaining a competitive edge as a market challenger. Embracing a high level of agility and a growth-oriented mindset, Banglalink fosters an environment where employees are encouraged to "learn & grow." This approach allows the company to capitalize on the latest technologies and trends, accelerating its progress and market presence.

In this journey towards digital transformation, Banglalink finds AI as a transformative force. In sectors like telecommunications, where vast data and repetitive processes are the norm, AI’s potential goes beyond automation. It offers opportunities to make routine tasks more engaging, foster a forward-thinking workplace culture, and produce meaningful insights from big data that drive growth. Telecom operators like Banglalink in Bangladesh demonstrate how AI is not only reshaping the workplace but also challenging employees to step up their game.

 

The New Age of Work: From Repetition to Innovation

AI has paved the way for a dynamic workplace where tasks previously considered mundane or repetitive now have a new edge. While some employees view this change as an opportunity, others who prefer stability and routine tasks may feel uncertain. In an AI-driven work culture, fast learners who embrace new technology quickly are finding greater value and relevance in their roles. On the other hand, employees who have relied on repetitive work as a source of job security might feel at risk, as AI redefines what’s essential in the workplace.

This shift is not about replacing humans with AI; rather, it’s about enhancing human capability to work smarter, faster, and more creatively. AI-powered platforms can manage routine workflows, allowing employees to focus on complex problem-solving and creativity, ultimately resulting in a more engaging work environment.

 

Transforming Big Data into Meaningful Insights

Telecom operators like Banglalink handle massive amounts of data daily, from customer interactions to network usage and device connections. Traditionally, data processing focused on generating metrics and reports, often lacking actionable insights. AI, however, brings this data to life with advanced analytics, helping employees visualize patterns and trends that inform strategic decisions.

For example, AI algorithms can predict network congestion points or highlight recurring customer service issues, enabling employees to address these proactively. The transition from static reports to dynamic, real-time data insights makes every day work feel more impactful, tying employees' roles more closely to the company’s success.

 

Case Study: AI-Driven Change in Banglalink

A recent milestone at Banglalink involved the use of AI for network-wide 2G channel dimensioning—a process that traditionally requires weeks of effort from a dedicated zone engineers. Thanks to AI, this complex task was completed in just few hours. The task involved scanning 32.4million data points from almost 80% sites of the network. Proper transceivers were filtered afterwards, and after execution almost 3.5% traffic channels are increased, at zero expense. This is a prime example of how AI can be used to harness more capacity from a well optimized network.

Of course, a significant factor in the success of Banglalink’s AI-driven initiatives lies in selecting the appropriate machine learning model and training with the appropriate duration of data. These models which are being developed fully in-house will certainly play a crucial role in predicting network usage, capacity, power saving, and potential customer complains, enabling better resource allocation and optimized service delivery.

AI models vary in complexity and suitability depending on the type of data and the target to be achieved. Old telecom operators like Banglalink are big data mines, and over the years the technology wing has stored quite a big amount of network data which are generated at all nodes. These datasets are structured from the beginning, making it a very ideal case to be used in AI models. Recent AI models have developed significantly using the power of GPUs to process terabytes of data. Also, the more training data can be provided the more accurate the results of the model will be. For example, to identify a potential customer base you no longer need to send a team to the physical spot at the first place – using proper clustering models more efficient to identify the user-behavior. Another example is anomaly detection. In mega cities like Dhaka, new high-rise building are creating blocking in front of mobile towers hampering the coverage. Early detection of such cases can help operators relocate the towers at the beginning of the problem. Using the large dataset of previous cases, it’s easy for Banglalink to train the model for detecting such cases. Another important job is forecasting the traffic – based on different clutters, time and day variations. Various forecasting models are available. But to deal with both seasonality and transient nature, we need to do trials with multiple models and the input duration can vary from weeks to few years. Below shown the input data selection criteria of just one segment used for channel dimensioning, the same continue for other branches of the tree:

One of the main benefits of in-house AI model development is the control Banglalink possess over the data and the flexibility in tuning all the hyper-parameters at their own need. Every network is different and has their own type of customer base. In-house team can wield the power of AI based on their internal needs. Telecom networks are an ever changing domain, where new technologies are emerging every decades – significantly changing the traffic patterns. Previously voice traffic was dominant, now data traffic is the future and between this video streaming traffic consumes the majority. To adapt the network with these continuous changes, engineers need to up their skills continuously. Even then, the checkpoints of solving a problem, each time new generations arrive keep arising. It was much easier to become a telco engineer in last decade, but now we can’t say the same for all cases. Also, it’s difficult for human to solve all issues in full efficiency, which is not the cases for machines. This case study highlights the potential of AI to streamline workflows, allowing employees to accomplish more in less time while ensuring accuracy.

 

Embracing a Culture of Innovation with AI

AI is more than just a tool—it’s a catalyst for a culture of innovation. By automating routine tasks, AI allows employees to focus on creative and strategic work, making their roles more rewarding. Fast learners who are unafraid of new technology thrive in this environment, while those who have relied on repetitive tasks for security may feel uncertain. However, for all employees, AI serves as an assistant, not a replacement, empowering them to excel in smarter, faster ways.

As Banglalink’s case illustrates, AI can revolutionize how employees approach their work, making even the most mundane tasks meaningful and contributing to an innovative, resilient workforce. With the right implementation, AI can be a powerful ally in transforming workplace culture, driving productivity, and making work truly rewarding.

 

Model developed by

Faisal Mohsin

Radio Service Lead Engineer

 

Contributed by

Hasnat Reza Mahbub Alam

Director,

Network Strategy and Performance

 

Sponsored by

Huseyin Turker

CTIO