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SINCE its emergence as an independent nation, Bangladesh has relied heavily on agriculture as the bedrock of its economy. To this day, the sector continues to employ more than a third of the national workforce. Recent figures from Statista (2025) indicate that 36.86 per cent of the country’s working population remains engaged in agriculture. Yet, despite this central role, the sector is beset with enduring challenges — low productivity, inefficient supply chains, volatile prices and restricted market access chief among them. These obstacles have long impeded the ability of agricultural entrepreneurs to evolve beyond mere subsistence and embrace a more market-oriented model. Against the backdrop of a global digital shift, a pressing question now emerges: are agri-entrepreneurs in Bangladesh prepared to adopt artificial intelligence for strategic marketing?

Artificial Intelligence is no longer a distant concept confined to academic journals or futuristic labs. In modern agriculture, it is already reshaping operations — introducing automation, data-driven decision-making and predictive insights that enhance productivity and profitability. Artificial intelligence-powered tools offer considerable promise for Bangladeshi agri-entrepreneurs. With predictive analytics, farmers can better anticipate market demand, monitor pricing patterns and decode consumer trends, enabling them to align production and distribution strategies with real-time data. Moreover, artificial intelligence allows for nuanced customer segmentation — distinguishing, for instance, between urban retail buyers and wholesale rural markets. Even logistics, long a pain point for rural producers, can be revolutionised through intelligent systems that reduce post-harvest losses and streamline supply chains.

While such developments may appear out of reach in Bangladesh, they are already taking root in other parts of Asia. China, in particular, has made notable strides through initiatives like ‘rural taobao,’ developed by Alibaba. This programme has provided farmers with AI-enhanced tools for direct-to-consumer engagement, dramatically increasing both market access and income in remote regions. In comparison, Bangladesh’s digital farming initiatives — iFarmer and Krishi Network being notable examples — show considerable potential but remain disjointed. Though these platforms connect farmers with finance, advisory services and market data, they lack the comprehensive, AI-integrated ecosystems seen in China. The technology exists, the interest is growing, yet overall readiness remains uncertain.

The reasons for this hesitancy are multifaceted. Perhaps the most significant barrier is digital illiteracy. As Dr Shahana Esmh noted in a 2022 study, ‘Without digital literacy, AI tools are useless to rural farmers who cannot interpret or trust what the technology is telling them.’ Most smallholder farmers in Bangladesh have limited, if any, experience with data platforms, AI dashboards, or mobile applications that require understanding of analytics or predictive charts. This digital unfamiliarity is further exacerbated by infrastructural shortcomings. Many rural regions suffer from poor internet connectivity, rendering even the most sophisticated technologies inaccessible.

Affordability also poses a major obstacle. Advanced technologies come at a cost that many smallholders simply cannot shoulder. Amina Binte Karim, who runs an agri-tech startup in Rajshahi, aptly remarked, ‘Most rural farmers cannot afford a system they barely understand and do not see immediate returns from.’ The lack of supportive policy compounds the problem. A 2023 report by the Bangladesh Centre for Advanced Studies highlights the dearth of government incentives in this domain. There is minimal state-led investment in rural digital infrastructure, little to no support for AI-focused agricultural research, and a near-total absence of programmes designed to upskill farmers in digital literacy. In contrast, China’s progress has been underpinned by robust state intervention: strategic investments in rural connectivity, subsidies for e-commerce platforms, and nationwide training initiatives. As Dr Qiang Li of JD Agriculture remarked at a global forum, ‘Our strength was not just technology — it was our ability to make that technology usable by everyone, even a 60-year-old farmer in a remote village.’

For Bangladesh to harness artificial intelligence in agriculture meaningfully, a coordinated, inclusive strategy is imperative. To begin with, the formulation of a National Digital Agriculture Policy is long overdue. Such a policy must encourage private sector involvement, fund artificial intelligence-centric agricultural research and prioritise investment in rural infrastructure. Equally vital is the localisation of technology. This involves developing interfaces in Bangla, incorporating voice commands, and simplifying tools for users with minimal literacy. Research underscores the importance of local language innovation, noting that such adaptations significantly enhance adoption rates, especially when paired with intuitive design.

Furthermore, digital literacy must be placed at the heart of any technological transformation. Government agencies, non-profits and private enterprises need to collaborate to offer practical training, demonstration projects, and peer-led learning models. Farmers are more likely to trust a technology when they see a neighbour benefit from it. Additionally, expanding broadband infrastructure in rural areas must be treated as a national development priority, with subsidies extended to telecom operators willing to venture into under-served zones. Supporting innovation from within is also essential. Establishing startup incubators focused on artificial intelligence applications in agriculture could nurture homegrown solutions. These incubators should provide seed capital, mentorship and access to markets. Finally, a centralised, open-access agri-data platform must be developed — one that offers real-time updates on market prices, soil health, pest outbreaks and weather patterns, accessible to all stakeholders from policymakers to the smallest landholders.

Ultimately, artificial intelligence-enhanced strategic marketing is no longer a distant ideal — it is a practical necessity. The agricultural landscape globally is undergoing a rapid transformation and data is now as critical as water or fertiliser. Should Bangladesh fail to embrace this shift, its agri-sector risks falling further behind, left mired in inefficiencies while neighbouring economies surge ahead. China’s journey is not merely instructive — it is a workable model. As Dr Wei aptly put it, ‘The future of farming lies in the hands of those who combine data with soil.’ Bangladesh possesses the soil and the human resources. What remains is the infrastructure, the vision, and the will to act. The moment for deliberation has passed. The imperative now is action.

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Kazi Md Samiul Hoq is BBA student at the North South University.