FROM HUMAN RESOURCE MANAGEMENT (HRM) TO ALGORITHMIC GOVERNANCE: THE CHANGING DISCRETION AND ROLE STRAIN OF LINE MANAGERS

Abstract

Line managers once held wide latitude over hiring, appraisal, scheduling, and discipline. That latitude is narrowing. As organizations adopt algorithmic HR systems, decisions once anchored in supervisory judgment are increasingly pre-structured, scored, or overridden by software. This paper pursues two objectives: first, to examine how algorithmic management and HR algorithms reconfigure the discretionary authority of line managers across core decision domains; second, to analyze the role strain managers experience mediating between algorithmic outputs and the employees who live with their consequences. Drawing on an integrative review of recent empirical and theoretical literature, the paper finds that discretion is not simply removed but redistributed unevenly across recruitment, performance management, and scheduling, producing a manager accountable for outcomes they no longer fully controls This mismatch generates measurable strain: ambiguity about where authority sits, ethical unease about opaque scoring logic, and a residual burden of explaining decisions the manager did not make. The paper proposes a conceptual pathway linking algorithmic input to discretion compression to role strain, and closes with implications for organizations designing human-AI collaborative HR systems