Determinants of artificial intelligence startups: evidence from 150 countries

Purpose This paper aims to explore how the ability of the national entrepreneurship ecosystem to complement macro country-level characteristics and meso industrial-level structures helps promote artificial intelligence (AI) startup activities. This study seeks to understand the potential impact of country and industrial factors on AI startups in both developed and developing countries. Design/methodology/approach Using a panel data set based on multiple dimensions and multiple indicators of multiple database sources, this study examines the determinant factors of AI on the outcomes of startup firms, a topic on which there is currently insufficient research. Findings The results of the fixed-effect panel Poisson regression analysis reveal how country characteristics and industrial structures contribute to AI startup in both developed and developing countries. In addition, the findings indicate that in a predictable AI environment, country characteristics and industrial structures have significantly different effects on AI startups between developed and developing countries. Practical implications The findings of the study provide useful insights for AI startup managers in both developed and developing countries to identify ways to improve AI startup success. Originality/value To the best of the authors’ knowledge, this is one of the first studies providing empirical evidence about how countries can access proprietary digital-related technologies and capabilities to facilitate AI startup growth in both developed and developing economies.