Bangladesh vs. The Machines: A Nation Built on Labor Meets the Age of AI

Bangladesh built its modern economy on human labor: ready-made garments, a large freelancing workforce, and a mostly informal jobs base. Artificial intelligence and automation now target that routine, low-wage work. This paper asks how exposed the country is, and whether its policy response matches the threat. Using a qualitative secondary-data design, it applies the Acemoglu-Restrepo task-based model of automation to peer-reviewed studies, institutional reports, and field journalism, with each headline figure cross-validated across independent sources. A 2024 factory study records an average 30.58 percent workforce reduction where automation has arrived, concentrated in cutting and sweater lines. The displacement falls hardest on women, whose share of garment work fell from 85 percent in 1991 to 57 percent in 2023. A national AI policy exists only in draft, leaving a gap between a projected 5.38 million jobs at risk by 2041 and any enacted protection. The task-based lens explains why a labor-surplus economy with weak reinstatement capacity sits in the displacement zone, and why reskilling and industrial policy will decide the outcome.