Artificial Intelligence Adoption and Digital Governance as Determinants of Public Administration Performance: A Case Study of Selected Federal and State Public Institutions in Nigeria

Abstract

The rapid advancement of Artificial Intelligence (AI) and digital governance technologies has transformed public administration by enhancing efficiency, transparency, accountability, and service delivery. This study examined the impact of AI adoption and digital governance on public administration performance using a quantitative research approach. Data were collected from 386 respondents comprising public servants, ICT administrators, policymakers, and service users through structured questionnaires. Descriptive statistics, Pearson correlation analysis, multiple regression, and Structural Equation Modeling (SEM) were employed for data analysis. The findings revealed a high level of AI utilization among respondents and positive perceptions of digital governance implementation. Correlation analysis showed significant positive relationships among AI adoption, digital governance, administrative efficiency, transparency, accountability, service delivery, and citizen satisfaction. Regression results indicated that AI adoption and digital governance jointly explained 68.7% of the variation in public administration performance, with AI adoption exerting the strongest influence. SEM results further demonstrated that AI adoption significantly improved administrative efficiency and transparency, while digital governance enhanced accountability. Administrative efficiency positively influenced service delivery, which subsequently increased citizen satisfaction. The study concludes that AI-enabled digital governance is a strategic tool for modernizing public administration and improving governance outcomes. The study recommends increased investment in digital infrastructure, capacity building, AI governance frameworks, and institutional reforms to maximize the benefits of intelligent public administration systems.

Also available @ https://doi.org/10.5281/zenodo.20689957