Application of Artificial Intelligence in Strengthening Financial Management amongst Administrators in Vocational Enterprises Institutes in Abuja, Nigeria
Abstract
This study examined the application of Artificial Intelligence (AI) in strengthening financial management practices among administrators in Vocational Enterprises Institutes (VEIs) in Abuja, Nigeria. The study was guided by two objectives: to determine the extent of AI application in financial management and to identify factors hindering its adoption. A cross-sectional descriptive survey design was adopted, allowing data collection from all administrators at a single point in time. The study population consisted of 54 administrators across six VEIs in Abuja, including 6 principals, 12 vice principals, and 36 heads of departments, and a census approach was used to ensure full participation. Data were collected using a structured questionnaire divided into sections on demographic information, extent of AI application, and hindering factors, rated on a five-point Likert scale. The instrument was validated by three experts and pilot-tested, yielding Cronbach’s alpha coefficients of 0.86 for AI application items, 0.83 for hindering factors, and 0.88 overall, indicating strong reliability. Data analysis involved descriptive statistics (mean and standard deviation) to address the research questions, and Analysis of Variance (ANOVA) to test the null hypotheses at a 0.05 significance level. Findings revealed a low extent of AI application in financial management among administrators, with inadequate infrastructure, insufficient training, lack of funding, and poor technical support identified as major hindrances. Additionally, there were no significant differences among principals, vice principals, and heads of departments regarding both the extent of AI application and the factors hindering its use. The study recommended that the Federal Capital Territory Administration through the Department of Mass Education implement programs to enhance AI usage in budgeting, record-keeping, and financial decision-making, and invest in ICT infrastructure, training, funding, and technical support to mitigate barriers to AI integration in VEIs.
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