Opening the gates: how public data reduces entry barriers and fuels AI entrepreneurship activity in China

Can public data, as important public resources, effectively drive artificial intelligence (AI) entrepreneurship activity? This study examines the impact of public data openness on AI entrepreneurship activity using a DID model based on panel data from prefecture-level (and above) cities in China from 2007 to 2024. The study finds that public data openness significantly promotes entrepreneurial activities in the field of artificial intelligence. This promotional effect is intrinsically driven by the scale of data supply, which empirically validates the theoretical prediction that enriched factor supply lowers entrepreneurial entry barriers. Furthermore, the study identifies key moderating mechanisms: public data acts as a substitute for labour and interacts synergistically with financial capital, making its impact more pronounced in regions with high labour costs and advanced financial development. Finally, heterogeneity analysis reveals that the positive effect is stronger in regions characterised by higher factor agglomeration, greater policy stability, and more advanced digital infrastructure.