Does Government AI Readiness Improve Human Resource Management Efficiency in The Public Sector?

Abstract

The research purpose determined for this study focuses on investigating whether and to what extent AI readiness levels of public sector institutions affect their HRM efficiency. In doing so, the secondary objective for this research concentrated on observing the heterogeneity determined by national differences at the global level. This research used panel data from 45 countries selected based on the data available for their AI readiness index from Oxford Insights per annum, and their government effectiveness from the World Bank indices per annum. The data was then statistically examined using the multi-linear regression (MLR) model. Information was also gathered by reviewing literature on the research problem. The findings obtained from the research revealed that AI readiness is directly responsible for the HRM efficiency level retained by the public sector organizations. However, there were notable discrepancies when observing the effects of total AI readiness scores, the technology sector, and data and infrastructure, which were excluded from the model. Nonetheless, the findings rejected the null hypothesis for this research, implying that HRM efficiency is indeed affected by the AI readiness of public organizations. The findings obtained from this research can be used to develop policy decisions that focus on strengthening AI readiness and accomplishing maturity levels, while also focusing on HRM efficiency enhancement strategies. Considering each HRM dimension in alignment with the drivers identified through the AI readiness framework will be highly beneficial in this regard. This research is a novel approach to utilize 45-country panel data spanning 4 years (from 2020 and 2023), further deconstructing AI readiness into ten distinct dimensions.