AI for an efficient supply chain

In the realm of modern agricultural management, the role of a robust and efficiently managed supply chain in maintaining price stability cannot be overstated. From ensuring the timely movement of goods to prevent hoarding and market manipulation, an effective supply chain serves as the backbone of a well-functioning market. As seen in developed countries, well-integrated supply chains enable agricultural products to move directly from farms to consumers, improving market efficiency while ensuring fair prices for both producers and buyers. In Bangladesh, however, such an integrated system remains largely absent. Given the highly perishable nature of agricultural produce, inadequate storage, logistics and technological infrastructure continue to impede a smooth flow of goods from farms to markets. The resulting inefficiencies not only increase post-harvest losses but also widen the gap between farm-gate and retail prices. Dominance of multiple layers of intermediaries further compounds the problem, often depriving farmers of fair prices while forcing consumers to pay inflated prices.

Against this backdrop, the government's recent proposal to deploy an artificial intelligence (AI)-driven system to monitor supply chains and narrow the gap between farmers and consumers raises cautious optimism. The ambition to embrace data-driven policymaking is welcome. However, AI must not be viewed as a panacea for the structural weaknesses that afflict the supply chain. As per the proposal drafted by the Trading Corporation of Bangladesh (TCB), a digital platform will be created to integrate data from multiple government agencies, markets, logistics providers, warehouses, meteorological office and international commodity indices. By analysing this vast pool of information, the AI system would forecast prices, identify supply disruptions, detect abnormal market behaviour and facilitate more informed policy decisions.

The proposal's emphasis on connecting farmers directly with wholesalers, retailers, e-commerce platforms and government procurement systems is particularly noteworthy. Reducing unnecessary layers of intermediaries could increase farmers' incomes while lowering costs for consumers. An AI-powered monitoring mechanism could also strengthen the government's capacity to respond proactively to market disruptions. Early warning signals would enable the government to make timely decisions on imports, stock management, open-market sales and targeted subsidies. At the same time, the system could help identify unusual price instability arising from hoarding, supply manipulation or artificial market distortions.

However, technology alone cannot solve governance failure or infrastructure challenges. No matter how sophisticated, AI cannot by itself overcome the structural weaknesses that continue to plague the supply chains. For this initiative to succeed, substantial investment will be needed to develop cold-storage facilities across major agricultural hubs and improve transportation networks. Stronger market oversight will also be essential to curb the dominance of syndicates, hoarding and rent-seeking along transport routes. AI can identify where the supply chain is bleeding, but it cannot heal the wound on its own. Overcoming these challenges will ultimately require human intervention and political will. At the same time, the limitations of AI must not be overlooked.  Algorithms can produce flawed analyses and inaccurate forecasts. The most effective approach, therefore, would be to combine the speed and analytical power of machines with human judgment and oversight.