Star Advantage: Employee Value Creation and Capture in the Age of Artificial Intelligence
提出“AI特定马太效应”，认为生成式AI会扩大明星员工与普通员工的绩效差距，并分析个人AI工具增强员工议价能力、企业AI系统强化企业价值获取的机制，为组织平衡生产力与公平提供理论指导。
ABSTRACT The integration of generative artificial intelligence (AI) into knowledge work is fundamentally reshaping employee performance and value creation in ways that challenge conventional wisdom. Rather than performance disparities being reduced through AI adoption, we argue that they may increase as star employees leverage superior domain expertise and strategic AI deployment to widen performance gaps—a phenomenon we term the “AI‐specific Matthew Effect.” These performance transformations coincide with dramatic shifts in value appropriation dynamics: Personal AI tools will enhance employee bargaining power by enabling portable, high‐value outputs independent of organizational resources, whereas enterprise AI systems serve as novel isolating mechanisms that strengthen firm value capture. These developments necessitate a theoretical reconceptualization of strategic human capital frameworks. Accordingly, we introduce the AI‐specific Matthew Effect to explain how AI may intensify performance stratification, modeling how AI reconfigures value creation and capture between employees and firms, and extending foundational human capital theories to account for human–AI complementarity. Our integrative theoretical framework offers critical guidance for navigating this transformation, helping organizations balance productivity gains with workforce equity in an uncertain era of interdependent human and artificial intelligence.