Exploring cross-national divide in government adoption of artificial intelligence: Insights from explainable artificial intelligence techniques

Abstract

Despite the recognized potential of artificial intelligence (AI) to improve governance, a significant divide in AI adoption exists among governments globally. However, little is known about the underlying causes behind the divide, hindering effective strategies to bridge it. Drawing on the AI capability concept and the Technology-Organization-Environment (TOE) framework, this study employs Explainable Artificial Intelligence (XAI) models to analyze the multifaceted factors influencing AI adoption by governments worldwide. The results underscore the critical roles of internet security and internet usage within the technological dimension, regulatory quality, government effectiveness, government expenditure, rule of law, and corruption control within the organizational dimension, and globalization, median age and GDP per capita within the environmental dimension. Notably, our analysis explores the intricate effects of these variables on government AI adoption, identifying inflection points where their impacts undergo significant shifts in magnitude and direction. This nuanced exploration provides a comprehensive understanding of government AI adoption globally and illustrates targeted strategies for governments to bridge the AI adoption divide, making theoretical, methodological and practical implications.