Bangladesh needs AI revolution to shape future economies
Engr. Seaam Bin Masud :
“We can’t just build bigger – we shall have to build smarter, that’s where Artificial Intelligence (AI) steps in, and where our work finds its purpose.”
Engr. Seaam Bin Masud said “Artificial Intelligence (AI) is not just about automation—it’s about shaping future economies, optimizing public services, and addressing sustainability challenges.”
In an exclusive conversation with The New Nation recently he said as AI rapidly redefines how the world works; and experts globally are also calling for greater participation from developing nations.
Engr. Seaam has over 14 years of leadership experience in facilities and infrastructure management across education, telecom, and energy sectors, and is currently focused on smart infrastructure innovation. His applied research aims to help both developed and developing nations unlock AI’s full potential in public service delivery and sustainability.
His work integrates AI, machine learning, and block chain into infrastructure systems.
During the conversation, he shares his insights on the role of AI in global development, including how countries like Bangladesh can leapfrog through technology transfer and local innovation.
Q1. How do you define AI in practical terms, especially for developing nations?
Seaam: AI, at its core, is about building systems that can process data, learn from it, and make decisions—often better or faster than humans can. For developing nations, this doesn’t mean humanoid robots or cutting-edge lab experiments.
It means practical solutions like crop monitoring through machine vision, traffic optimization using predictive analytics, or automating building maintenance through smart sensors. It’s about solving local problems with scalable, adaptive technologies.
Q2. In what ways can AI contribute to economic growth in countries like Bangladesh?
Seaam: AI can significantly enhance productivity, reduce resource waste, and improve decision-making across industries. In agriculture, AI-powered tools can predict pest outbreaks or suggest optimal planting times. In manufacturing, predictive maintenance can reduce downtime. I’ve led digital transformation initiatives in facilities management, where AI reduced energy costs and improved system uptime. These efficiency gains translate directly into GDP growth and competitiveness.
Q3. What challenges do you see in transferring AI technologies from developed nations to countries like Bangladesh?
Seaam: The transfer isn’t just technical—it’s also institutional. Challenges include data scarcity, lack of regulatory frameworks, and limited local AI talent. But it’s not insurmountable.
One model I support is “localized adaptation”—where core AI models from abroad are tailored with local datasets and use cases. Cross-border collaboration, open-source platforms, and public-private partnerships are essential to accelerate responsible tech transfer.
Q4. There’s a lot of talk about AI and jobs. Will it create opportunities or eliminate them?
Seaam: Both side. AI will automate repetitive tasks, but it will also create new roles in data management, system integration, ethics, and oversight. For example, when I implemented an AI-assisted CMMS (Computerized Maintenance Management System), we retrained technicians to manage digital dashboards and IoT systems.
So yes, some jobs will be displaced—but smarter planning can ensure that even more are created.
Q5. In your experience, what sectors are most ripe for AI implementation in Bangladesh?
Seaam: Education, healthcare, logistics, energy, agriculture, and urban planning. Each has unique bottlenecks that AI can help solve. My work has particularly focused on infrastructure—using AI for predictive maintenance, asset tracking, and energy optimization. In cities, AI can support waste management or smart traffic control.
The potential is vast—but it requires ecosystem alignment. “Our goal is to advance digital infrastructure systems that can reduce energy costs, improve safety, and help prevent disasters through intelligent forecasting, these are systems that can benefit not just the U.S., but also developing nations like Bangladesh.”
Q6. What’s the role of policy and leadership in enabling AI adoption?
Seaam: Visionary leadership is critical. We need policies that promote ethical AI use, ensure data privacy, and invest in STEM education. Government incentives can attract global AI firms while nurturing local startups. I’ve been involved in advocacy for AI literacy in FM (Facilities Management) sectors, which often get overlooked in digital policy discussions.
Long-term success demands inclusive, human-centered AI policy frameworks.With global urbanization growing faster and infrastructure challenges mounting AI is at the forefront of designing a smarter, greener built environment. AI experts aim is to build not just facilities, but a better future.
Q7. How can young professionals in developing countries prepare themselves for the AI-driven future?
Seaam: Start by understanding the basics: data, algorithms, and real-world applications. Online courses, community projects, and local hackathons are great entry points. But equally important is domain knowledge—understanding how AI can apply to sectors like construction, energy, or logistics. I always tell emerging engineers: become translators between real-world problems and algorithmic thinking.
AI is not a distant frontier; it’s a present reality with transformative potential. The key lies in smart adaptation, cross-sector collaboration, and human-centered design. For countries like Bangladesh, the AI revolution is not just about catching up—it’s about leapfrogging into a more inclusive and efficient future.
Engr. Seaam began his journey from the Military Institute of Science and Technology (MIST), Mirpur, Dhaka Cantonment, where he received a Bachelor of Science in Civil Engineering. In the past decade, he has worked with some of the most recognized organizations globally—Chevron, Robi Axiata Ltd., Aga Khan Development Network—and has been an integral player throughout his career in facilities and maintenance management including preventive maintenance, oversight of capital projects, energy-saving programs and establishment of computerized maintenance management systems (CMMS).
He is pursuing an M.S. in Information Technology Project Management at Wilmington University, devoting his expertise to cutting-edge research that integrates AI, blockchain, and machine learning into facilities operations. His work directly supports energy conservation, predictive maintenance, and public safety in mission-critical environments such as schools, hospitals, and utilities.
Seaam’s research works have been published in several international scholarly journals focused on AI, blockchain and smart infrastructure. He has also served as a member of editorial and review boards for several international journals, has reviewed more than a dozen articles for scientific journals, and has authored several case studies in his expertise field.
(The author is a US-based Bangladeshi born engineer and AI researcher who holds Master’s in Information Technology Project Management from Wilmington University, Delwar state in USA).