Artificial Intelligence Leadership and Innovation Efficiency: Evidence of Underutilized Human Capital

This study examines how artificial intelligence (AI) leadership shapes the relationship between technological integration, human capabilities, and innovation activity within organizations, addressing the broader question of whether innovation outcomes are driven by human capital or by AI-enabled efficiency gains. Using a structured survey of 3,079 respondents across industries and regions, the study applies exploratory and confirmatory factor analysis and structural equation modelling to test the proposed relationships. The results indicate that AI leadership has a strong positive effect on in-novation activity while simultaneously exerting a significant negative effect on human capabilities, with no statistically significant relationship between human capabilities and innovation activity. The findings do not support a mediation mechanism, sug-gesting that innovation outcomes can emerge independently of human capability en-gagement. This pattern indicates a structural misalignment in the innovation produc-tion process, where technological inputs are efficiently translated into outputs while human capital remains underutilized. From an economic perspective, the results indi-cate a shift toward efficiency-driven innovation systems, where productivity gains are achieved primarily through AI-enabled processes. The study contributes to the litera-ture by challenging assumptions of human–AI complementarity and by highlighting the importance of leadership in shaping the allocation and integration of technological and human resources.