Artificial Intelligence and Human Resources Accounting of Manufacturing Companies in Nigeria
DOI:
https://doi.org/10.61143/umyu-jafr.8(1)2025.018Keywords:
Artificial Intelligence, Human Resource Accounting, Machine Learning, Process Automation, Predictive AnalyticsAbstract
This study examined the effect of three Artificial Intelligence (AI) components; Machine Learning, Process Automation, and Predictive Analytics, on Human Resource Accounting (HRA) practices in selected manufacturing firms in Benin City, Edo State, Nigeria. A survey research design was employed to collect primary data from a population of 412 employees across Bendel Feed and Flour Mill Ltd, Nosak Distilleries Ltd, and Presco Plc. Using Taro Yamane’s formula at a 5% margin of error, a sample size of 203 was determined. Stratified random sampling ensured representation across key departments, including human resources, accounting/finance, and operations. Data were collected using a structured and validated questionnaire, with reliability confirmed through a pilot study yielding Cronbach’s alpha values above 0.70. The study adopted a model that specified Human Resource Accounting as the dependent variable and the three AI components as independent variables. Responses were measured on a 5-point Likert scale. Data analysis was conducted using SPSS version 25, applying descriptive statistics and paired samples t-tests. Results revealed that Machine Learning, Process Automation, and Predictive Analytics each had a positive and statistically significant effect on HRA, with Machine Learning exerting the strongest influence. The findings affirm that AI integration enhances the measurement, recognition, and reporting of human capital. The study concludes that AI-driven tools improve the strategic application of HRA and recommends targeted AI training for HR and accounting professionals to ensure effective and sustainable use of these technologies in the manufacturing sector.
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