Standard Setting and Peer Innovation in the Artificial Intelligence Field: Evidence from China

Recent research has extended the influence of standard setting to non-standard-setters, yet this influence within the emerging context of artificial intelligence (AI) remains underexplored. To address this gap, we investigate how AI standard setting affects the AI innovation of peers in the same industry as standard-setting firms. Considering AI-specific characteristics, we integrate and reinterpret the two roles of standards—coordination and construction—arguing that AI standards coordinate new markets with prominent scale economies and network effects while constructing a favorable normative environment for AI innovation. Using panel data on Chinese publicly listed firms (2007–2023), our difference-in-differences analysis reveals a positive relationship between AI standard setting and peer AI innovation, which weakens with increasing industry concentration but strengthens with greater AI scale, media visibility, and media favorability. Heterogeneity analyses show more pronounced peer effects in high-tech industries, state-owned enterprises, and firms with low digital affiliations. Further analyses indicate that fewer drafters and the firm’s higher ranking within a standard enhance peer innovation, while its participation in multiple standards concurrently reduces it. This study not only enriches research on standard setting and AI diffusion but also provides insights for policy-making.