AI-Driven Human Resource Management in Bangladesh's Public Sector: An Investigation on Readiness, Barriers, and Implementation Strategies

Abstract

The objective of this study is to investigate whether the public sector of the emergent economy of Bangladesh is ready for artificial intelligence (AI) adoption for human resource management (HRM) use.  Design/Methodology: A cross-sectional quantitative survey was administered to 400 government officials (IT specialists, HR managers, and administrative directors) drawn from 12 ministries and 8 autonomous bodies through stratified proportion sampling. The psychometric quality of the instrument was verified by the Cronbach α (0.87–0.98), KMO (0.842), Bartlett test (χ² = 4213.6, p < 0.001), and CFA. The analytical techniques utilized included regression, moderation analysis, and Harman’s test. Results: The complete model accounted for 61.2% of the variance in AI-HRM implementation (R2 = 0.612; Adjusted R2 = 0.601; F(5, 394) = 124.36, p < 0.001). AI readiness was a positive predictor of implementation (β = 0.412, p < 0.001) whereas perceived barriers (β = –0.284, p < 0.001, reverse-coded) had a significant negative effect. The association between readiness and implementation was impacted by institutional support. The uniqueness of this study is that it combines the four theories of TOE, TAM, DOI, and Institutional Theory into one explanatory model and provides a phased, governance-led roadmap for AI-HRM diffusion in South Asian bureaucracies.