Governance configurations driving AI innovation: A comparative analysis from 40 countries

Artificial intelligence (AI) innovation is a central driver of technological and social transformation, yet effective governance of AI remains unresolved. Prior studies emphasize single elements or linear effects, overlooking how governance configurations jointly shape technological innovation outcomes. This study addresses the question of how distinct governance patterns drive AI innovation across countries. Drawing on Ostrom's Institutional Analysis and Development (IAD) framework, we conceptualize AI governance as an interplay of actors, resources, and environments. Using fuzzy-set qualitative comparative analysis (fsQCA) to analyze 40 national cases, we find that no single condition is necessary for high AI innovation. However, open access to data and algorithms, along with international participation, consistently underpins high levels of technological innovation. Three equifinal governance pathways are identified, a government-led model under resource-environment resonance, a market-driven model under resource aggregation, and a multi-actor collaborative model under information openness. These findings advance institutional theory in digital technology governance and provide differentiated policy pathways for fostering AI innovation.