Matthew Call

Recent workplace trends reveal that workers frequently discuss and engage in deliberate underperformance, underscoring the growing relevance of intentional underperformance at work. Although various disciplines have long studied purposeful reductions in work effort, these investigations have remained largely siloed, hindering conceptual clarity. In this scoping review, we integrate perspectives from management, social and educational psychology, and economics to establish a unified conceptualization of intentional underperformance (i.e., the deliberate suppression of task contributions, such that contributions fall below a relevant benchmark). In doing so, we make five primary contributions to the performance literature. First, we review and consolidate 36 related constructs to develop an umbrella conceptualization that can promote cumulative scientific understanding. Second, based on our review, we present an organized view of the antecedents and proximal motives of intentional underperformance. Third, we introduce the Intentional Underperformance Framework, a two-by-two that organizes forms of intentional underperformance, and organize the associated outcomes of these different forms. Fourth, we identify cross-disciplinary patterns in operationalizations, summarizing prevailing methods and their implications. Fifth, we outline a research agenda to guide future inquiry into when, why, and how intentional underperformance arises, as well as how organizations can constructively intervene. By integrating disconnected literatures and promoting a shared language, this review provides a foundation for more integrative theoretical and empirical inquiries. Ultimately, we aim to equip scholars and practitioners with a clearer, more comprehensive understanding of intentional underperformance in today’s workplace.

Read full publication

Today’s businesses must transform at unprecedented speed and scale. Digital disruption, shifting customer expectations, regulatory pressures, and technological advances compress what once unfolded over years into months. Organizations navigate continuous, overlapping transformations while maintaining operational excellence. The question isn’t whether to change, but how to build the organizational capability to do it faster and more effectively than the competition.

Read full publication

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.

Read full publication