Where Bangladesh can lead in AI

The artificial intelligence race has declared its winners at the foundation level. Companies such as OpenAI, Google, and Anthropic are currently leading the frontier LLM and other model space with billions in capital and computational resources. For countries like ours, Bangladesh, the target should be not competing with these giants but building advantages where local knowledge and practical application matter most. In fact, we can also look for export in some areas. Three distinct areas can come as our savior in the next AI age: software-as-a-service applications for local and global market, AI-integrated hardware devices starting with local market and exporting in similar global markets, and structured adoption and efficiency development for local enterprises and people.

The SaaS success template: India has demonstrated this approach's feasibility. Freshworks, founded in Chennai, became the first Indian SaaS company listed on NASDAQ and now generates US $713 million annually. The Indian SaaS ecosystem is projected to reach US $50 billion by 2030. Bangladesh has SAAS like EzyCourse, founded by Md Sadek Hossain from Sylhet. The bootstrapped startup serves over 1,800 creators globally with US $1.5 million in trailing revenue, proving Bangladeshi founders can compete internationally. Bangladesh has been SAAS companies leading in the global economy in different sector. Going forward, there are many AI SAAS ideas that we can pursue.

Domain-specific applications emerge across every business vertical. Export garment manufacturers face compliance documentation that consumes 15-20 per cent of operational costs. AI-powered systems can be built that will understand both WRAP standards and local labour regulations reduce this overhead to under 5 per cent. Legal chambers processing land disputes or commercial contracts see 40-60 per cent time savings through AI-assisted document drafting that handles Bangla legal terminology alongside English requirements.

Right now, customer service outsourcing generates significant IT industry revenue annually for Bangladesh. Innovations such as AI workflow systems trained on local linguistic patterns outperform generic global solutions by 35-40 per cent accuracy rates.

The hardware integration scope: AI-integrated IoT devices offer manufacturing advantages for Bangladesh. For example, Xiaomi's platform connects over 822 million devices worldwide, while the Chinese platform Tuya supports global smart appliance manufacturers. These companies embed AI into practical problems rather than building underlying models. On the other hand, American firm Samsara provides fleet management that reduces fuel costs. One Indian startup that is a good example here is Stellapps which monitors milk quality from farm to processing.

Bangladesh's textile and RMG industry present immediate applications. Computer vision based AI systems can detect stitching defects before garments reach quality control. Again, there can be vibration sensors can predict compressor failures in dyeing machines. If industry experts think deeply, we can adapt AI massively to boost RMG productivity. The country's retail and hospitality sectors can benefit from smart energy management systems that account for load shedding and voltage fluctuations common in the local grid.

Agriculture cooperatives can deploy sensor networks that monitor cold storage temperatures for vegetables or track humidity levels in grain storage. Private hospitals facing staff shortages can install bed monitoring systems that alert nurses to patient movements or vital sign changes, even there are solutions for doctors that will help them give better prescription and history of patients in one go. These can be built locally integrating foundation models.

The technical barriers are manageable. Companies can source sensors from established suppliers, integrate open-source AI models for edge computing, and focus on the crucial calibration work that requires local knowledge. Dhaka's traffic patterns, monsoon humidity levels, and power grid characteristics all generate data that generic global solutions cannot handle effectively.

Enterprise AI adoption as economic strategy: Bangladesh's startup ecosystem includes over 1,000 ventures, but the economic impact lies in enabling existing enterprises to adopt AI. Most micro, small, and medium enterprises operate on paper records, creating productivity improvement potential. In our neighbouring countries, government initiatives have moved thousands of small manufacturers online through subsidised tools and training programmes. China has equipped rural cooperatives with AI-powered crop advisory systems and demand forecasting tools through provincial development programmes.

Bangladesh can adapt these approaches through existing institutional networks. Chambers of commerce and industry associations already have established relationships with member companies. Enterprise adoption transforms productivity at scale. Data suggests that AI-powered inventory systems reduce working capital requirements for textile manufacturers while cutting stockout losses. Customer communication platforms handle max routine inquiries automatically, allowing staff to focus on complex problems. Supply chain forecasting algorithms prevent good amount of revenue losses that come from demand miscalculation during seasonal peaks. Specific implementations around the world already show immediate results.

The integration advantage: The global pattern is clear to us. Companies like Freshworks, Samsara, and Xiaomi built billion-dollar businesses by embedding AI into domain-specific problems rather than competing on foundational research.

Bangladesh does possess some comparative advantages: a technically capable workforce comfortable with English and Bangla, competitive manufacturing costs, and domestic testing markets.

Time for national coordination: The window for establishing leadership in applied AI is closing soon. Countries which will be building expertise now in software integration, hardware deployment, and enterprise adoption will create advantage for the next AI world that will compound over time. Those that delay face importing solutions designed elsewhere rather than building local capabilities.

Bangladesh may not control the foundation models, but it can control how those models are applied. Building the integration capability now means shaping industries, creating jobs, and positioning local firms in global value chains. We require a coordinated national strategy aligning government policy, educational institutions, and private sector investment around these three domains. Foundation models belong to the Silicon Valleys, but the applications layer that determines how AI improves human productivity remains open for competition. The country that owns the integration between artificial intelligence and real-world problems will capture the economic benefits of the AI revolution. For Bangladesh, the choice is between building that integration capability now or watching others do it instead.

rummank@gmail.com