The global economy is rapidly entering an era shaped by artificial intelligence (AI). According to estimates from international research bodies, AI could contribute more than 15 trillion US dollars to global economic output by 2030. This transformation is expected to have the deepest impact on developing countries, which risk falling far behind in global competition if they fail to adopt and adapt new technologies in time.
For Bangladesh, the question of AI is no longer theoretical. The real issue is whether AI will remain a fashionable buzzword, or whether it will bring tangible changes to productivity, public services, and governance. The answer depends on a series of difficult but unavoidable policy and investment decisions that must be made now.
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Why AI matters for Bangladesh’s economy
Bangladesh’s economic structure remains heavily dependent on labour-intensive sectors. While this model has delivered steady growth, productivity levels are relatively low, and pressure on public and private services is rising. AI has the potential to address both challenges simultaneously: boosting productivity and enabling better services with limited resources.
Studies and pilot projects suggest that AI applications could reduce time and costs in public services by 20–30 per cent. In agriculture, crop forecasting and early disease detection could cut losses by 10–15 per cent. In banking and financial services, fraud detection efficiency could improve by as much as 30–40 per cent. However, these benefits cannot be achieved by merely importing AI tools; they must be adapted to Bangladesh’s local economic, social, and institutional realities.
Data abundance, readiness deficit
On paper, Bangladesh possesses vast amounts of data. There are more than 180 million national identity records, over 170 million mobile connections, and more than 70 million users of mobile financial services. In addition, health, education, and social protection systems generate millions of records each year. In terms of volume, this represents a significant national asset. Yet much of this data is not usable for AI.
Three structural problems stand out. First is fragmentation: government data systems remain largely siloed. Research indicates that 60–70 per cent of public-sector data is not interoperable across ministries or agencies. Second is quality and updating: many datasets are not regularly updated, undermining the accuracy of AI-based predictions. Third is weak data governance: without clear legal and ethical frameworks for data use, large-scale AI deployment becomes risky and contentious.
Cloud, computing, and infrastructure constraints
The most expensive component of AI development globally is computing power. Training even a medium-sized AI model requires high-performance graphics processing units (GPUs), sustained electricity supply, advanced cooling systems, and scalable cloud infrastructure.
Bangladesh has a national data centre and a growing number of private data centres, but AI-grade GPU capacity remains limited. As a result, large AI projects rely heavily on foreign cloud services. This dependence increases costs and raises concerns over data sovereignty. Currently, roughly 30 per cent of AI computing relies on domestic infrastructure, while about 70 per cent depends on foreign cloud providers.
Skills, policy, and governance gaps
Each year, Bangladesh produces between 20,000 and 25,000 IT graduates, and more than a thousand technology start-ups are active. Despite this, the number of AI engineers capable of solving real-world problems remains very small. Experts estimate that the country has only one-fifth to one-quarter of the skilled AI workforce it currently needs. Advanced research capacity is also still underdeveloped.
Policy and regulation present another critical gap. While Europe has adopted risk-based AI legislation, the United States has issued sector-specific guidelines, and many Asian countries have formulated national AI strategies, Bangladesh lacks a comprehensive AI policy. Data protection laws await effective implementation, and ethical guidelines for government use of AI remain unclear. Without a robust policy framework, AI risks becoming an unregulated technology that ultimately harms citizens.
Where quick gains are possible
Despite these challenges, several sectors could see rapid benefits from AI adoption. Agricultural losses could be reduced by 10–15 per cent, healthcare screening efficiency could rise by 25–30 per cent, disaster forecasting lead times could be extended, and urban traffic congestion could fall by 15–20 per cent.
Snapshot of Bangladesh’s AI readiness
| Area | Current situation | Key challenge |
|---|---|---|
| Data | Large volumes available | Fragmentation and quality |
| Computing | Limited GPU capacity | High cost |
| Cloud | Heavy foreign reliance | Data sovereignty |
| Human resources | Large IT workforce | Skills gap in AI |
| Policy | Partial frameworks | No comprehensive AI strategy |
Ultimately, numbers tell a clearer story than rhetoric. Bangladesh has data, but it is not fully prepared; interest, but limited infrastructure; manpower, but incomplete skills. The opportunity to shape an AI-driven future still exists, but it will not remain open indefinitely. Bangladesh has begun its journey into the AI era—the pressing question is whether it will proceed with clear strategy, realistic assessment, and timely action.
Dr Touhid Bhuiya is an information technology specialist and Professor at Washington University of Science and Technology.