This study examines the determinants of Artificial Intelligence (AI) adoption within Bangladesh’s Public Financial Management (PFM) system and investigates how digital divide factors shape institutional readiness for AI-enabled reforms. Using quantitative data from 120 officials across major PFM agencies, the study assesses digital infrastructure, human capital, data governance, interoperability, innovation culture, and institutional conditions influencing AI uptake. Descriptive statistics, correlation analysis, and multiple regression were used to analyze relationships among variables. The findings show that AI adoption is driven primarily by internal institutional capabilities, with PFM performance, system interoperability, innovation culture, and human capital emerging as significant predictors. In contrast, regulatory frameworks, political support, financial capacity, and institutional readiness were not statistically significant, indicating that structural enablers alone do not translate into effective AI use without complementary operational capacities. The study contributes to AI adoption theory by demonstrating that AI readiness in developing-country PFM systems is a socio-technical process shaped more by organizational culture and system integration than by policy conditions. These insights offer practical guidance for policymakers seeking to advance Bangladesh’s digital transformation agenda and highlight priority areas for investment, including capacity-building, interoperability, and innovation-driven institutional environments.
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