Research on the impact of artificial intelligence innovation on enterprise competitiveness

Purpose This study examines the nonlinear impact of AI innovation on enterprise competitiveness and its underlying mechanisms. Design/methodology/approach Using a sample of Chinese A-share listed companies (2012–2022) and patent-based AI innovation metrics, we employ robustness tests, mediation and moderation analyses and heterogeneity checks. Findings Results reveal an inverted U-shaped relationship between AI innovation and enterprise competitiveness. At initial stages, AI innovation significantly boosts competitiveness; however, beyond a critical threshold, the marginal benefits diminish and can become negative. Substantive innovation, which requires higher capital investment, is relatively less efficient in improving competitiveness compared with strategic innovation. Mechanism analysis shows that AI innovation affects enterprise competitiveness through three inverted U-shaped channels: enhancing innovation efficiency, optimizing labor structure and improving governance structure. Heterogeneity analysis reveals that the issuance of the “Notice on the New Generation Artificial Intelligence Development Plan” facilitates faster attainment and maintenance of competitive advantage. Enterprises in high AI innovation industries, with higher risk-taking capacity and lower agency costs, benefit more from AI innovation. Further moderation analysis identifies that regional innovation levels, marketization indices, financing constraints and average managerial age significantly influence the AI innovation–competitiveness relationship. Practical implications The findings guide enterprises in digital transformation and AI strategy, and inform AI patent policy. Originality/value This study integrates enterprise-level AI innovation with competitiveness, revealing nonlinear effects, multiple mediating channels and the conditional role of policy and firm characteristics.