This study examined the relationship between accounting staff demographic variables and the adoption of Artificial Intelligence (AI)-enabled platforms in public sector accounting within the Ministry of Finance, Ebonyi State, Nigeria. Anchored on the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the study adopted a descriptive survey research design. A structured questionnaire was administered to a sample of 300 accounting staff, selected through stratified random sampling from a population of 412 staff members. Data were analysed using descriptive statistics, chi-square test, one-way Analysis of Variance (ANOVA), and multiple regression analysis. Findings revealed that gender exerts no statistically significant influence on AI platform adoption (χ² = 3.418, p = .490 > .05), whereas educational qualification (F = 22.471, p = .000 < .05) and work experience (β = .412, t = 6.047, p = .000) significantly predict AI adoption behaviours. The study concludes that human capital characteristics, particularly educational attainment and professional experience, are critical enablers of AI platform integration in public sector accounting. The findings carry significant implications for human capital development policies, digital transformation agendas, and public financial management reform in Ebonyi State and comparable sub-national governments across Nigeria and the broader African context.
OYEWOLE OLUBUKOLA SARAH AE-FUNAI (Mon,) studied this question.